[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-74073":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":10,"languages":10,"totalLinesOfCode":10,"stars":11,"forks":12,"watchers":13,"openIssues":14,"contributorsCount":15,"subscribersCount":15,"size":15,"stars1d":16,"stars7d":17,"stars30d":18,"stars90d":15,"forks30d":15,"starsTrendScore":19,"compositeScore":20,"rankGlobal":10,"rankLanguage":10,"license":21,"archived":22,"fork":22,"defaultBranch":23,"hasWiki":24,"hasPages":22,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":35,"readmeContent":36,"aiSummary":37,"trendingCount":15,"starSnapshotCount":15,"syncStatus":38,"lastSyncTime":39,"discoverSource":40},74073,"awesome-prompts","ai-boost\u002Fawesome-prompts","ai-boost","Curated list of chatgpt prompts from the top-rated GPTs in the GPTs Store. Prompt Engineering, prompt attack & prompt protect. Advanced Prompt Engineering papers.","https:\u002F\u002Fawesomegpt.vip",null,8171,761,75,18,0,39,90,311,117,114.65,"GNU General Public License v3.0",false,"main",true,[26,27,28,29,30,31,32,33,34],"awesome","awesome-list","chatgpt","gpt4","gpts","gptstore","papers","prompt","prompt-engineering","2026-06-12 04:01:13","\u003Cdiv align=\"center\">\n  \u003Ch2 align=\"center\">Awesome Prompts 🪶\u003C\u002Fh2>\n  \u003Cp align=\"center\">\n    \u003Cimg width=\"650\" src=\"https:\u002F\u002Fraw.githubusercontent.com\u002Fai-boost\u002Fawesome-prompts\u002Fmain\u002Fassets\u002Fbanner.png\">\n  \u003C\u002Fp>\n  \u003Cp align=\"center\">Curated prompts, frameworks, and papers — with an engineering bias.\u003C\u002Fp>\n  \u003C!-- Keep these links. Translations will automatically update with the README. -->\n  \u003Cp align=\"center\">\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fde\u002Fai-boost\u002Fawesome-prompts\">Deutsch\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fen\u002Fai-boost\u002Fawesome-prompts\">English\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fes\u002Fai-boost\u002Fawesome-prompts\">Español\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Ffr\u002Fai-boost\u002Fawesome-prompts\">français\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fja\u002Fai-boost\u002Fawesome-prompts\">日本語\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fko\u002Fai-boost\u002Fawesome-prompts\">한국어\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fpt\u002Fai-boost\u002Fawesome-prompts\">Português\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fru\u002Fai-boost\u002Fawesome-prompts\">Русский\u003C\u002Fa> |\n    \u003Ca href=\"https:\u002F\u002Fzdoc.app\u002Fzh\u002Fai-boost\u002Fawesome-prompts\">中文\u003C\u002Fa>\n  \u003C\u002Fp>\n  \u003Cp align=\"center\">\n    \u003Ca href=\"https:\u002F\u002Fawesome.re\">\u003Cimg src=\"https:\u002F\u002Fawesome.re\u002Fbadge.svg\" alt=\"Awesome\" \u002F>\u003C\u002Fa>\n    \u003Ca href=\"http:\u002F\u002Fmakeapullrequest.com\">\u003Cimg src=\"https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FPRs-welcome-brightgreen.svg?style=flat-square\" alt=\"PRs Welcome\" \u002F>\u003C\u002Fa>\n  \u003C\u002Fp>\n\u003C\u002Fdiv>\n\n---\n\nThe prompt engineering world has split into two camps:\n\n- **Camp 1 — Prompt templates**: collect system prompts, share copy-paste recipes, curate persona prompts. Useful, but limited.\n- **Camp 2 — Prompt as engineering**: compile LM programs (DSPy), test and regress prompts (promptfoo), control generation structurally (Guidance), optimize prompts automatically (TextGrad, GEPA). This is where the long-term value is.\n\nThis repo covers both. The engineering camp gets more space.\n\n---\n\n## Table of Contents\n\n- [📋 Prompts](#prompts) — copy-paste ready\n  - [Coding & Development](#coding--development)\n  - [DevOps & SRE](#devops--sre)\n  - [Data Engineering](#data-engineering)\n  - [AI & ML](#ai--ml)\n  - [Product & Strategy](#product--strategy)\n  - [Project Management](#project-management)\n  - [Healthcare & Clinical](#healthcare--clinical)\n  - [Industrial & Automotive](#industrial--automotive)\n  - [Legal & Compliance](#legal--compliance)\n  - [Knowledge & Documentation](#knowledge--documentation)\n  - [Writing & Academic](#writing--academic)\n  - [Learning & Education](#learning--education)\n  - [Research & Analysis](#research--analysis)\n  - [Productivity & Tasks](#productivity--tasks)\n  - [Safety & Compliance](#safety--compliance)\n  - [Meta & Prompt Engineering](#meta--prompt-engineering)\n  - [Image, Video & Audio Generation](#image--video--audio-generation)\n  - [Creative & Role-play](#creative--role-play)\n  - [Game Development](#game-development)\n  - [Translation](#translation)\n  - [Legacy (2023 era)](#legacy-2023-era--kept-for-reference)\n- [🔬 Frameworks](#frameworks) — the engineering camp\n  - [Prompt Programming](#prompt-programming)\n  - [Automatic Prompt Optimization](#automatic-prompt-optimization)\n  - [Eval & Testing](#eval--testing)\n  - [Red Team & Security](#red-team--security)\n  - [Low-Code & Workflow Platforms](#low-code--workflow-platforms)\n- [🕵️ System Prompt Leaks](#system-prompt-leaks) — learn from production\n- [🧠 Prompt Engineering](#prompt-engineering) — techniques & defense\n- [🔭 Context Engineering](#context-engineering)\n- [🤖 Agent Ecosystem](#agent-ecosystem) — MCP, Skills, Harness\n- [📖 Official Guides](#official-guides)\n- [📄 Papers](#papers) — Foundations, Optimization, Reasoning, RAG, Agents, Multi-Agent, Safety, Self-Improving Agents, Tool Use, Evaluation, Memory, Multimodal\n- [🛠 Tools & Libraries](#tools--libraries)\n\n---\n\n## Prompts\n\nAll prompts are open — click, copy, use directly.\n\n### Coding & Development\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🤖 Agentic Coder | Plan-first coding agent — security checklist, test discipline, PR summary format (2025) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagentic_coder.txt) |\n| 🔍 Code Reviewer | Security-focused code reviewer — OWASP Top 10, severity grading, fix examples (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcode_reviewer_security.txt) |\n| 🕸 Multi-Agent Orchestrator | Central dispatch agent — task decomposition, parallel delegation, state tracking, error recovery (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmulti_agent_orchestrator.txt) |\n| 🧱 Agent Harness Designer | System prompt for designing reliable agent runtimes — tool minimization, approval gates, memory\u002Fcompaction, rollback, observability, evals; derived from OpenAI\u002FAnthropic harness guidance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_harness_designer.txt) |\n| ⚡ Agent Harness Performance Engineer | Cross-harness agent harness optimization — token economics, memory persistence hooks, continuous learning via instinct extraction, verification loops, parallelization, security scanning; based on affaan-m\u002Feverything-claude-code (Jan 2026, 182k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_harness_performance_engineer.txt) |\n| 📁 Agent Virtual Filesystem Architect | Unified virtual-filesystem layer for AI agents — mount topology, resource adapters, bash-tool surface, two-layer cache, snapshots\u002Fcloning, framework integration; based on strukto-ai\u002Fmirage (May 2026, 2149 stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_virtual_filesystem_architect.txt) |\n| ⚙️ Autonomous Software Factory Orchestrator | Chat-driven autonomous development orchestrator — human sets direction via lightweight messages, self-coordinating claws execute planning\u002Fbuild\u002Ftest\u002Freview\u002Fpush loops; notification routing (git\u002Ftmux\u002FGitHub\u002Flifecycle) kept strictly outside agent context windows; based on ultraworkers\u002Fclaw-code (Mar 2026, 191k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fautonomous_software_factory_orchestrator.txt) |\n| 🖥 Computer Use Operator | System prompt for browser\u002Fdesktop agents — observe → act → verify loops, least privilege, confirmation gates, phishing\u002Fprompt-injection resistance; derived from OpenAI's 2026 computer-use guidance | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcomputer_use_operator.txt) |\n| 🌐 Browser Harness Designer | Self-healing browser harness architect — direct CDP websocket, thin editable runtime, agent-generated helper layer, domain\u002Finteraction skill separation; based on browser-use\u002Fbrowser-harness (Apr 2026, 12k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fbrowser_harness_designer.txt) |\n| 🖥 Agent-Native CLI Designer | Agent-native CLI architect for GUI software — 7-phase SOP to wrap any GUI app into a stateful, agent-usable CLI with REPL + subcommand modes, backend integration, test planning, and SKILL.md generation; based on HKUDS\u002FCLI-Anything (Mar 2026, 34k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcli_anything_harness_designer.txt) |\n| 🧩 Agent Skill Designer | Prompt for packaging reusable agent skills — narrow scope, tool-aware workflow, safety rules, verification checklist, `SKILL.md` draft output; derived from Anthropic\u002FGoogle skill guidance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_skill_designer.txt) |\n| 🧠 Managed Agent Architect | Prompt for designing long-running managed-agent systems — brain\u002Fhands split, worker contracts, checkpoints, permission scoping, recovery; derived from Anthropic\u002FOpenAI 2026 harness guidance | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmanaged_agent_architect.txt) |\n| 🔌 Agent Protocol Advisor | Prompt for choosing MCP vs A2A vs simpler transports — protocol mapping, trust boundaries, ownership, retries, migration plan; derived from Google's 2026 protocol guide | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_protocol_advisor.txt) |\n| 🧮 Agentic Code Reasoner | Prompt for evidence-backed code reasoning — semi-formal reasoning chain, competing hypotheses, verification-first conclusions for complex code understanding (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagentic_code_reasoner.txt) |\n| 📨 Multi-Agent Communication Designer | Prompt for designing agent-to-agent message protocols — topology choice, message fields, conflict handling, graph\u002Fschema vs free-text tradeoffs (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmulti_agent_communication_designer.txt) |\n| 🕸 Multi-Agent Topology Selector | Prompt for choosing single\u002Fparallel\u002Fsequential\u002Fhierarchical\u002Fhybrid agent topologies — communication cost, ownership, failure controls, human review points (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmulti_agent_topology_selector.txt) |\n| 🤝 Agent Cooperation Designer | Prompt for designing cooperative multi-agent systems — shared objective, local roles, disagreement rules, anti-herding controls, evaluation signals (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_cooperation_designer.txt) |\n| 🎛 Vendor-Diverse Multi-Agent Ensemble Designer | Prompt for designing multi-agent ensembles that DELIBERATELY mix vendors (Claude \u002F GPT \u002F Gemini \u002F DeepSeek \u002F Qwen \u002F Llama) — role-to-vendor mapping for complementary inductive biases, disagreement-as-signal arbitration, vendor-correlated failure audit, monoculture controls, version pinning; based on MIT\u002FHarvard \"Multi-Agent LLM Systems for Clinical Diagnosis: The Impact of Vendor Diversity\" (arXiv 2603.04421, 2026) — generalised beyond clinical to any high-stakes ambiguous task | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fvendor_diverse_multi_agent_designer.txt) |\n| 🗄 SQL Assistant | Senior DB engineer — query writing (CTE-first), optimization (EXPLAIN-driven), schema design, multi-dialect (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsql_assistant.txt) |\n| 🐛 Debugging Agent | Systematic bug hunter — reproduce → observe → hypothesize → test → localize → fix; works for any language (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdebugging_agent.txt) |\n| 🎯 Disciplined Diagnostician | Disciplined diagnosis loop for hard bugs and performance regressions — feedback-loop construction, falsifiable hypotheses, instrumented probes, correct regression-test seams, cleanup protocol; based on mattpocock\u002Fskills (Feb 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdiagnose.txt) |\n| 🏗 System Design | Staff-level architect — clarifies requirements first, capacity estimation, component trade-offs, failure modes (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsystem_design.txt) |\n| 📐 Spec-Driven Development Architect | Spec-first system designer — structured mission\u002Ftech-stack\u002Froadmap\u002Frequirements\u002Fscenarios\u002Fvalidation packages; RFC 2119 discipline, delta specs for changes, small-phase decomposition; based on 2026 spec-driven development best practices (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fspec_driven_development_architect.txt) |\n| ⚡ Performance Profiler | Performance engineering expert — baseline → bottleneck analysis → impact-ranked optimization plan with code examples (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fperformance_profiler.txt) |\n| 🔧 Refactoring Coach | Refactoring specialist — diagnose code smells, sequence safe Fowler-catalog transforms, preserve behavior at every step (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Frefactoring_coach.txt) |\n| 🔗 API Integration Architect | Integration architect — pattern selection, auth, retry\u002Fbackoff, idempotency, observability for reliable system-to-system integrations (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fapi_integration_architect.txt) |\n| 🗃 Database Schema Designer | DB architect — entity modeling, normalization (1NF–3NF), index strategy, PostgreSQL DDL with migration notes (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdatabase_schema_designer.txt) |\n| 🧪 Test Strategy Architect | Testing architect — risk-based test pyramid, tooling, coverage targets by layer, 4-week implementation roadmap (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ftest_strategy_architect.txt) |\n| ⚡ Claude Artifacts | System prompt for generating rich Claude Artifacts (UI, interactive apps, code) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fclaude_artifacts_prompt.md) |\n| 💻 Professional Coder | Expert coding assistant — auto programming, project generation, any language | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002F%F0%9F%92%BBProfessional%20Coder.md) |\n| 🎨 Design System Spec Architect | Prompt for authoring DESIGN.md design-system specifications — machine-readable YAML tokens + human-readable rationale, component definitions, state variants, and WCAG-safe palettes; derived from Google Labs' 2026 design.md specification (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdesign_system_spec_architect.txt) |\n| 🎨 Generative UI Architect | Component-first, design-system-native UI generation — states, tokens, accessibility, responsive layouts, typed code output (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fgenerative_ui_architect.txt) |\n| 🎨 Open Design Orchestrator | Local-first, agent-agnostic design producer — skill-driven prototype\u002Fdeck workflows, 72+ brand-grade design systems, deterministic visual directions, five-dimensional self-critique, multi-modal export (HTML\u002FPDF\u002FPPTX\u002FMP4); based on nexu-io\u002Fopen-design (Apr 2026, 38k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fopen_design_orchestrator.txt) |\n| 🎨 Magazine Web Deck Designer | Single-file HTML horizontal-swipe deck architect — two locked visual styles (Editorial Magazine × Electric Ink vs Swiss Internationalism), WebGL hero backgrounds, 10–22 registered layout skeletons, locked theme presets, Motion One choreography, typography-first discipline; based on op7418\u002Fguizang-ppt-skill (Apr 2026, 8590 stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmagazine_web_deck_designer.txt) |\n| 🎨 Frontend Taste Engineer | Senior UI\u002FUX engineer that overrides default LLM biases toward generic UI — metric-based design rules (variance\u002Fdensity\u002Fmotion dials), anti-slop guardrails, CSS hardware acceleration, spring physics, liquid-glass refraction, and premium interaction states; based on Leonxlnx\u002Ftaste-skill (Apr 2026, 17.5k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ffrontend_taste_engineer.txt) |\n| 🖥 Frontend Developer | React\u002FVue\u002FAngular expert — component architecture, Core Web Vitals, WCAG 2.1, responsive design, TypeScript, performance budgets (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ffrontend_developer.txt) |\n| 🌐 Web Quality Auditor | Comprehensive frontend quality audit — Lighthouse-driven performance (Core Web Vitals), accessibility (WCAG 2.2 AA), technical SEO, and best practices; severity-graded findings with file:line citations and concrete fixes; based on addyosmani\u002Fweb-quality-skills (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fweb_quality_auditor.txt) |\n| 📲 Mobile App Builder | Native iOS (Swift\u002FSwiftUI) + Android (Kotlin\u002FJetpack Compose) + cross-platform (React Native\u002FFlutter) — offline-first, biometric auth, push notifications, app store deployment (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmobile_app_builder.txt) |\n| ⛓️ Solidity Smart Contract Engineer | Security-first Solidity — checks-effects-interactions, ERC-20\u002F721\u002F1155, UUPS\u002Fdiamond proxies, DeFi primitives, gas optimization, Foundry fuzz\u002Finvariant testing, L2 deployment (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsolidity_smart_contract_engineer.txt) |\n| ⚡ Solana Blockchain Architect | Production-grade Solana program design — Rust\u002FAnchor, account-model discipline, PDA derivation\u002FCPI safety, SPL Token\u002FToken-2022, compute-unit optimization, reinitialization defense, signer\u002Fowner validation, `solana-program-test` verification; based on solana-foundation\u002Fsolana-dev-skill (Mar 2026, 493 stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsolana_blockchain_architect.txt) |\n| 🧠 Emotion-Aware Engineering Partner | Senior coding partner grounded in Anthropic's 2026 emotion-vectors research — incremental delivery, honest uncertainty calibration, collaborative pushback, debugging transparency (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Femotion_aware_engineering_partner.txt) |\n| ✅ Verification Specialist | Adversarial validation agent — tries to break implementations across frontend, backend, CLI, mobile, data\u002FML, and infra; enforces command-backed PASS\u002FFAIL\u002FPARTIAL verdicts with adversarial probes (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fverification_specialist.txt) |\n| 🏛 Tech Debt Auditor | Whole-repo structural audit — nine-dimension debt sweep (architectural decay, consistency rot, type debt, test debt, dependency rot, performance hygiene, observability, security hygiene, documentation drift); forced orientation before judgment, mandatory `file:line` citations, required \"looks bad but is actually fine\" section; based on ksimback\u002Ftech-debt-skill (Apr 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ftech_debt_auditor.txt) |\n| 🎯 Andrej Karpathy Coding Guidelines | Concise behavioral guardrails against common LLM coding mistakes — think before coding, simplicity first, surgical changes only, goal-driven verification; derived from Andrej Karpathy's observations on LLM coding pitfalls (Jan 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fandrej_karpathy_coding_guidelines.txt) |\n| 🧰 Coding Agent System Prompt | Production-grade system prompt for CLI coding agents — identity, permission model, task execution discipline, code style constraints, risk-aware action, tool usage protocol, output efficiency; independently authored from patterns observed in Claude Code (Apr 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcoding_agent_system_prompt.txt) |\n| 📊 Technical Diagram Engineer | Production-quality SVG diagram generator — architecture, data flow, flowchart, sequence, agent\u002Fmemory, UML, ER, network topology; 7 visual styles, semantic arrow vocabulary, shape taxonomy, layout rules, AI\u002FAgent domain patterns; based on yizhiyanhua-ai\u002Ffireworks-tech-graph (Apr 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ftechnical_diagram_engineer.txt) |\n| 🧩 Claude Code Sub-Agent Designer | Designer prompt for Anthropic's Claude Code sub-agents — when to use sub-agent vs skill vs inline, kebab-case naming, routing description authoring, least-privilege tool allowlists, isolated context discipline, output-contract lock-in, routing stress test; based on Anthropic's Claude Code Sub-Agents docs (Feb 2026) and wshobson\u002Fagents + VoltAgent\u002Fawesome-claude-code-subagents (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fclaude_code_subagent_designer.txt) |\n| 🏛 Solution Architect | In-depth codebase study → concrete implementation plan — explores conventions, maps dependencies, presents multiple options with trade-offs, sequences reversible incremental steps, and surfaces open questions before any code is written; based on repowise-dev\u002Fclaude-code-prompts (Apr 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsolution_architect.txt) |\n| 🛠 Pragmatic Programmer | Classic software engineering principles as binding agent rules — DRY at knowledge level, orthogonality, tracer bullets, ruthless feedback, automation, broken windows; MUST\u002FSHOULD\u002FMUST NOT policy for code generation and review; based on Hunt & Thomas and ciembor\u002Fagent-rules-books (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fpragmatic_programmer.txt) |\n| 📓 AGENTS.md Author | Authoring prompt for the AGENTS.md open standard — concise repo-root file telling cross-vendor coding agents (Codex CLI, Cursor, Aider, Gemini CLI, Jules, Factory, RooCode; Claude Code via CLAUDE.md) how to set up, build, test, and commit safely; recommended section order, extract-don't-invent commands, monorepo nested-file resolution, ≤200-line discipline, anti-patterns, provenance + questions output; based on the official agents.md spec, OpenAI's Aug 2025 introduction, and Agentic AI Foundation \u002F Linux Foundation 2026 stewardship | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagents_md_author.txt) |\n| 🕸 Codebase Knowledge Graph Architect | Transform code, SQL schemas, infrastructure definitions, docs, and multimodal assets into a structured, queryable knowledge graph — AST-level entity extraction, God-node identification, surprising cross-module connections, design-rationale mining, architectural tension detection, and confidence-tagged edges (EXTRACTED \u002F INFERRED \u002F AMBIGUOUS); outputs GRAPH_REPORT.md, graph.json, and optional interactive visualization; supports incremental delta updates on commits; based on safishamsi\u002Fgraphify (Apr 2026, 44k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcodebase_knowledge_graph_architect.txt) |\n| 🏗 Parallel Codegen Architect | Architect generator\u002Fevaluator\u002Forchestrator harness patterns for sustained, large-scale code construction with parallel LLM sub-agents — compilers, interpreters, runtimes, parsers, type checkers, codemod systems; pre-condition test (decomposable artifact, testable interfaces, work-per-module repays coordination), strict role separation (orchestrator reads only summaries, never generator transcripts; evaluator is read-only on code and tests; sealed modules are immutable without explicit reopening), phased workflow (plan → parallel build → integration tiers → end-to-end → postmortem), checkpoint-resumable execution, anti-patterns refused (inter-generator chat, evaluator-rewrites-tests-to-pass, role conflation, unbounded parallelism); based on Anthropic's \"Building a C Compiler with Parallel Claudes\" (anthropic.com\u002Fengineering\u002Fbuilding-c-compiler, Feb 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fparallel_codegen_architect.txt) |\n| 🏭 Opinionated Agent Team Designer | Multi-role tooling system designer for AI coding agents — CEO \u002F Designer \u002F Eng Manager \u002F Release Manager \u002F Doc Engineer \u002F QA role definitions with explicit mandates and anti-scopes, review lattice (plan-review, code-review, pre-ship sign-off), slash-command invocation protocol, infrastructure roles (autoplan, guard, benchmark, learn, retro), team-mode shared configuration with silent auto-updates; opinionated over flexible, narrow over general, review over trust, explicit over implicit; based on garrytan\u002Fgstack (Mar 2026, 96k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fopinionated_agent_team_designer.txt) |\n| 🖥 Native-Feel Desktop Architect | Cross-platform desktop app architect that feels indistinguishable from native — four-layer architecture (native shell → system WebView → Node backend → Rust core), eight architectural tenets, WebKit\u002FWebView2 survival guide, 75-item ship audit, anti-patterns (Electron abstraction, Tauri control-loss, two UI codebases); based on yetone\u002Fnative-feel-skill (May 2026, 1.2k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fnative_feel_desktop_architect.txt) |\n\n### DevOps & SRE\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🚨 Incident Response Commander | Incident commander — SEV1-4 matrix, real-time coordination, blameless post-mortems, SLO\u002FSLI framework, stakeholder comms templates (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fincident_response_commander.md) |\n| 🛡 SRE | Site reliability engineer — SLO\u002Ferror budget framework, observability three pillars, golden signals, toil reduction, chaos engineering (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsre.md) |\n| ☁️ Cloud Architect | Senior cloud architect — multi-cloud (AWS\u002FAzure\u002FGCP), Well-Architected Framework, migration 6Rs, FinOps, zero-trust, disaster recovery, IaC (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcloud_architect.txt) |\n| ⎈ Kubernetes Specialist | K8s operations — cluster architecture, RBAC, network policies, GitOps (ArgoCD\u002FFlux), service mesh (Istio\u002FLinkerd), multi-tenancy, CIS Benchmark, cost optimization (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fkubernetes_specialist.txt) |\n| 🏗 Platform Engineer | Internal developer platform & AI infrastructure — IaC, multi-model serving, agent runtime, observability, cost optimization, GitOps, zero-trust (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fplatform_engineer_iac.txt) |\n| 🚀 Release Engineer | Production launch specialist — pre-launch checklists, feature flags, staged canary rollouts, rollback strategy, post-launch verification; based on addyosmani\u002Fagent-skills (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Frelease_engineer.txt) |\n\n### Data Engineering\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🔧 Data Engineer | Data pipeline specialist — Medallion Architecture (Bronze\u002FSilver\u002FGold), PySpark + Delta Lake, dbt contracts, Great Expectations, Kafka streaming (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdata_engineer.md) |\n| 📈 Analytics Engineer | Production data infrastructure — dimensional modeling, dbt, pipeline architecture, data quality testing, metrics definition (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fanalytics_engineer.txt) |\n| 🗄 Data Platform Architect | Enterprise data platform design — lakehouse architecture, data mesh, real-time streaming, AI\u002FML pipelines, governance, multi-cloud cost optimization (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FData_Platform_Architect.txt) |\n| 📊 Data Governance Architect | Enterprise data governance — policy frameworks, stewardship models, data catalogs, lineage tracking, privacy compliance, AI data standards (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FData_Governance_Architect.txt) |\n\n### AI & ML\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🤖 ML Systems Architect | Production ML design — data pipelines, training, inference, model evaluation, MLOps, monitoring, cost optimization, LLM fine-tuning (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fml_systems_architect.txt) |\n| 🧬 LLM Architect | LLM systems — fine-tuning (LoRA\u002FQLoRA\u002FRLHF\u002FDPO), RAG architecture, serving (vLLM\u002FTGI), quantization (GPTQ\u002FAWQ), safety guardrails, multi-model orchestration (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fllm_architect.txt) |\n| 🎙 Realtime Voice Agent Architect | Enterprise voice agent design — sub-1s TTFA, streaming STT→LLM→TTS, turn-taking, barge-in handling, voice-optimized prompts, confirmation gates (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Frealtime_voice_agent_architect.txt) |\n| 🎨 Multimodal Agent Designer | Cross-modal agent architecture — active perception, visual\u002Faudio grounding, token-efficient context management, modality-aware tool design, GUI automation (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmultimodal_agent_designer.txt) |\n| 🔍 Long-Horizon Multimodal Search Agent | Sustained visual-textual search across 100-turn horizons — file-based visual context management, progressive on-demand image loading, multi-hop visual reasoning, horizon drift prevention; based on LMM-Searcher (arXiv 2604.12890, April 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Flong_horizon_multimodal_search_agent.txt) |\n| ⚖️ AI Ethics Reviewer | Algorithmic ethics audit — fairness & bias, transparency, privacy, safety, accountability, societal impact, cross-cultural considerations, mitigation roadmap (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FAI_Ethics_Reviewer.txt) |\n| 🤖 MLOps Engineer | ML operations platform — feature stores, model registries, training pipelines, serving infrastructure, drift monitoring, experiment tracking, GPU optimization, LLM deployment (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FMLOps_Engineer.txt) |\n| 🦾 Embodied AI Developer | VLA systems, robotic agents, world-model-driven embodied intelligence — perception-action grounding, sim-to-real pipelines, cross-embodiment transfer, skill primitives, physical safety gates; derived from 2026 embodied-AI research (StarVLA, EmbodiedClaw, VLA-World) (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fembodied_ai_developer.txt) |\n| 📱 On-Device AI Deployment Architect | Privacy-first edge AI architect — hardware-aware model selection, quantization strategy (GGUF\u002FAWQ\u002FTurboQuant), inference engine tuning (MLX\u002Fllama.cpp\u002FOllama\u002FvLLM\u002FTensorRT-LLM), KV-cache optimization, SSD offloading, hybrid cloud-edge partitioning, thermal\u002Fpower management; based on llmfit, omlx, Rapid-MLX, ds4, apfel, and 2026 on-device AI ecosystem (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fon_device_ai_deployment_architect.txt) |\n| 🤖 Self-Improving Agent Architect | Closed learning loop agent design — experience-driven skill creation, autonomous improvement nudges, cross-session memory with user modeling, multi-platform gateway, scheduled automations, model-agnostic backends; based on NousResearch\u002Fhermes-agent (2026, 140k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fself_improving_agent_architect.txt) |\n| 🏢 Agentic Company Orchestrator | Zero-human-company multi-agent orchestration architect — org-chart design, heartbeat-driven execution, goal-aligned delegation, budget governance with hard stops, ticket-based task tracking, board approval gates, multi-company isolation, and portable company templates; based on paperclipai\u002Fpaperclip (Mar 2026, 64k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagentic_company_orchestrator.txt) |\n| 🔭 Open Deep Research Agent Architect | End-to-end design of an open-source deep research agent that competes with OpenAI Deep Research \u002F Gemini Deep Research \u002F Perplexity Pro — task contract, synthetic agentic data pipeline, on-policy RL with verifiable rewards, Light vs Heavy inference modes, typed evidence graph with triangulation, long-horizon planner with replan triggers, deployment topology with prefix caching, public-benchmark eval harness (xbench \u002F BrowseComp \u002F GAIA \u002F FRAMES), citation-honesty governance; based on Alibaba-NLP\u002FDeepResearch — Tongyi DeepResearch (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fopen_deep_research_agent_architect.txt) |\n| 🧪 Autonomous ML Research Agent | Self-directed experiment loop for ML research — fixed-time-budget training, single-file edit discipline, keep\u002Fdiscard decision gates, git-branch state management, overnight autonomy; reads code, forms hypotheses, runs experiments, logs results, and iterates without human intervention; based on karpathy\u002Fautoresearch (Mar 2026, 80k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fautonomous_ml_research_agent.txt) |\n| 🧪 Self-Distillation Code Generation Strategist | Decision strategist for the SSD recipe — when self-distillation is the right next training move and when it is not; precondition test on pass@k − pass@1 gap, minimal-recipe pipeline (sample → cross-entropy fine-tune on raw unverified samples, no reward model, no verifier, no RL), parallel verifier-aware arm, pre-declared anti-collapse battery (self-BLEU, length drift, pass@k diversity, style probe, safety\u002Frefusal drift), round-2 decision gate, per-difficulty slice reporting with CIs, GPU-hour Pareto comparison vs SFT-external \u002F DPO \u002F GRPO; refuses to recommend SSD on models whose pass@k − pass@1 gap is \u003C ~5 pp and refuses to ship gains without contamination-checked held-out slices; based on Apple's \"Self-Distillation Improves Code Generation\" (arXiv 2604.01193, April 2026; Qwen3-30B 42.4% → 55.3% pass@1 on LiveCodeBench v6, gains concentrate on hard problems) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fself_distillation_code_strategist.txt) |\n| ⚖️ Verifier Engineering Strategist | Designs, audits, and refuses verifier systems — the machinery that turns a model's output (final answer, intermediate step, tool call, agent trajectory) into a reward\u002Fselection\u002Fgating signal; per-workload type selection (rule-based → programmatic → ORM → PRM → LLM-as-judge → hybrid), explicit verifier hypothesis with target precision\u002Frecall on named slices, Math-Shepherd-style PRM data synthesis with held-out cross-policy evaluation, mandatory adversarial probe battery (length inflation, format mimicry, confidence-word spam, prompt injection via candidate), reward-vs-true-accuracy divergence monitor as the reward-hacking detector, verifier-policy co-adaptation cycle, infrastructure-noise separation, versioning + kill-switch protocols; refuses LLM-as-judge in RL without bounded bias, refuses in-distribution PRM accuracy as a deployment signal, refuses shared training\u002Feval verifier; based on the 2025–2026 verifier-augmented training trajectory (DeepSeek-R1 arXiv 2501.12948, Math-Shepherd arXiv 2312.08935, ProcessBench arXiv 2412.06559, Anthropic's Demystifying Evals \u002F Infrastructure Noise \u002F Eval Awareness 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fverifier_engineering_strategist.txt) |\n\n### Product & Strategy\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🧭 Product Manager | Full product lifecycle — discovery to launch; PRD template, RICE scoring, Now\u002FNext\u002FLater roadmap, GTM brief, outcome measurement (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fproduct_manager.md) |\n| 🧠 AI-Native Product Architect | AI-first product design — agentic workflows, generative UI, human-in-the-loop at the right level, self-improving loops, trust & transparency architecture (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fai_native_product_architect.txt) |\n| 🎯 UX Research Specialist | Research methodology and user insights — qualitative interviews, usability testing, survey design, metrics analysis, journey mapping, stakeholder communication (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fux_research_specialist.txt) |\n| 💼 CFO \u002F Financial Strategy | Chief Financial Officer driving capital allocation and enterprise value — FP&A, fundraising, M&A, pricing strategy, board reporting (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcfo_financial_strategy.txt) |\n| 📊 Sales Strategist | Sales leader optimizing pipeline, win rates, territory planning, deal acceleration — BANT\u002FMEDDIC, quota setting, GTM execution (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsales_strategist.txt) |\n| 💬 Customer Success Strategist | Account success leader maximizing lifetime value — health scoring, account planning, executive engagement, EBRs, retention & expansion, advocacy programs (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcustomer_success_strategist.txt) |\n| 🚀 Growth Hacker | Growth driver using data-driven experimentation — funnel optimization, viral loops, unit economics, A\u002FB testing, activation, retention, acquisition channels (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fgrowth_hacker.txt) |\n| ⚙️ Operations Manager | Ops leader optimizing processes, reducing costs, enabling scale — Lean, bottleneck analysis, cost structure, systems integration (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Foperations_manager.txt) |\n| 🔄 Change Management Leader | Organizational transformation and adoption — stakeholder alignment, communication strategy, training programs, adoption tracking, sustainment, cultural change (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fchange_management_leader.txt) |\n| 🎯 Recruitment Strategist | Talent acquisition leader building pipelines and optimizing hiring — sourcing, competency modeling, offer strategy, retention focus (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Frecruitment_strategist.txt) |\n| 💬 Community Manager | Community leader building engaged, healthy communities — moderation, engagement loops, advocacy programs, member lifecycle, culture building (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcommunity_manager.txt) |\n| 🎨 Brand Strategist | Brand building and reputation — positioning, messaging, visual identity, GEO (Generative Engine Optimization), crisis management, brand experience (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fbrand_strategist.txt) |\n| 👥 HR \u002F Talent Development | Talent development and performance — recruitment, onboarding, learning, career development, culture, DEI, engagement, retention (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fhr_talent_development.txt) |\n| 💰 Financial Advisor | Comprehensive wealth management — financial planning, investment strategy, risk management, tax optimization, estate planning, behavioral coaching (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ffinancial_advisor.txt) |\n| 🔍 SEO Specialist | Technical SEO, content strategy, link authority, SERP features — audit templates, keyword research, E-E-A-T, Core Web Vitals, AI search adaptation (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fseo_specialist.txt) |\n| 🎤 Developer Advocate | DevRel — DX audits, technical content, community building, product feedback loops, SDK adoption, conference talks, time-to-first-success tracking (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdeveloper_advocate.txt) |\n\n### Project Management\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🏃 Scrum Master | Certified Scrum Master — sprint ceremonies, impediment removal, team coaching, velocity tracking, retrospectives, scaling (SAFe\u002FLeSS\u002FNexus) (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fscrum_master.txt) |\n| 🚨 Project Recovery Specialist | Crisis project turnaround — root cause diagnosis, stakeholder realignment, scope reclamation, team rehabilitation, 30-60-90 day recovery plans (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FProject_Recovery_Specialist.txt) |\n| 🔄 Agile Transformation Lead | Enterprise agile transformation — operating model design, framework selection, product management integration, flow optimization, change management, technical practices (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FAgile_Transformation_Lead.txt) |\n| 📋 Technical Program Manager | Complex cross-functional program delivery — dependency modeling, critical path analysis, risk management, stakeholder alignment, resource planning, AI-augmented workflows (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FTechnical_Program_Manager.txt) |\n\n### Healthcare & Clinical\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🏥 Clinical Assistant | Differential diagnosis generator + SOAP note writer from transcripts\u002Fnotes — ICD-10\u002FCPT coding, diagnostic workup, HIPAA-compliant (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fclinical_assistant.txt) |\n| 🏥 Healthcare AI Architect | Clinical AI system design — safety-first architecture, multi-agent clinical reasoning, evidence stratification, uncertainty communication, HIPAA\u002FFDA compliance, MR-Bench evaluation (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fhealthcare_ai_architect.txt) |\n| 🔬 Clinical Research Coordinator | Clinical trial operations — GCP compliance, protocol design, site management, patient recruitment, safety reporting, decentralized trials, data integrity (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FClinical_Research_Coordinator.txt) |\n| 🏥 Health Informatics Specialist | Digital health system design — EHR integration, FHIR interoperability, clinical decision support, health data architecture, regulatory compliance (HIPAA\u002FFDA), AI in healthcare (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FHealth_Informatics_Specialist.txt) |\n| 🧬 Bioinformatics Engineer | Production-grade computational biology — NGS pipelines (FASTQ→BAM→VCF), single-cell\u002Fspatial transcriptomics, differential expression, variant calling, multi-omics integration; Snakemake\u002FNextflow workflows, Bioconductor statistical rigor, reproducible containerized environments; based on GPTomics\u002FbioSkills (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fbioinformatics_engineer.txt) |\n\n### Industrial & Automotive\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🚗 Automotive Functional Safety Architect | ISO 26262 safety architect — HARA with Cartesian malfunction analysis, ASIL decomposition, FSC\u002FTSC derivation, HW-SW interface design, ISO\u002FSAE 21434 cybersecurity concept, ISO 21448 SOTIF validation, GSN safety-case argument; every artifact paired with implicit reviewer gate; based on jherrodthomas\u002Fautomotive-skills-suite (May 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fautomotive_functional_safety_architect.txt) |\n| 🤖 Industrial Robotics Architect | ISO 10218 \u002F ISO\u002FTS 15066 \u002F ISO 3691-4 robotics architect — machinery safety lifecycle (ISO 12100 → ISO 13849 \u002F IEC 62061), cobot biomechanical limits and SSM\u002FPFL, AMR fleet safety with VDA 5050, ROS2 system architecture, IEC 62443 OT cybersecurity, FAT\u002FSAT V&V; every artifact paired with implicit reviewer gate; based on jherrodthomas\u002Frobotics-skills-suite (May 2026, 510 stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Findustrial_robotics_architect.txt) |\n| 🏭 Agentic CAD & Hardware Designer | Parametric CAD and hardware-design engineer — STEP-first build123d\u002FPython parts and assemblies, natural-language spec → CAD brief, enclosures\u002Ffixtures\u002Fjoints\u002Fmating, URDF\u002FSDF\u002FSRDF robotics descriptions, source-controlled geometry with validated exports; based on earthtojake\u002Ftext-to-cad (Apr 2026, 2952 stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagentic_cad_hardware_designer.txt) |\n\n### Legal & Compliance\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| ⚖️ Legal Analyst | Comprehensive legal research and contract analysis — IRAC methodology, regulatory compliance, litigation risk, IP strategy, M&A due diligence (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Flegal_analyst.txt) |\n| 🔒 Compliance Auditor | SOC 2, ISO 27001, HIPAA, PCI-DSS — gap assessment, evidence collection automation, policy templates, audit preparation, continuous compliance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcompliance_auditor.txt) |\n| 📋 Regulatory Affairs Specialist | Global regulatory strategy — FDA\u002FEMA\u002FNMPA pathways, QMS design, submission preparation, gap analysis, post-market surveillance, AI\u002FML compliance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FRegulatory_Affairs_Specialist.txt) |\n| ⚖️ Contract Negotiation Strategist | Complex deal negotiation — contract architecture, risk allocation, BATNA\u002FZOPA analysis, concession planning, cultural negotiation, AI-assisted contract analysis, M&A and licensing (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FContract_Negotiation_Strategist.txt) |\n\n### Knowledge & Documentation\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 📚 Knowledge Management Architect | Enterprise knowledge systems — information architecture, documentation standards, AI-powered search, RAG, discoverability, governance, maintenance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fknowledge_management_architect.txt) |\n| 📝 Technical Documentation Strategist | Comprehensive docs strategy — docs-as-code, AI-assisted writing, information architecture, developer experience, quality assurance, knowledge management integration (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FTechnical_Documentation_Strategist.txt) |\n| 🧠 Personal Knowledge Assistant | PKM system design — Zettelkasten, BASB, spaced repetition, AI reading assistants, semantic note-taking, knowledge synthesis, creativity pipelines (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FPersonal_Knowledge_Assistant.txt) |\n| 🗄 Knowledge Base Architect | Enterprise knowledge systems design — taxonomy, ontology, information architecture, semantic search, knowledge graphs, AI-augmented curation, content lifecycle governance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FKnowledge_Base_Architect.txt) |\n| 🔗 Personal Agent Brain Architect | Self-wiring knowledge brain for personal AI agents — entity-centric graph, hybrid search (exact → graph → vector), verbatim ingestion, self-maintenance dream cycle, skill-driven interface; based on garrytan\u002Fgbrain (Apr 2026, 14k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fpersonal_agent_brain_architect.txt) |\n\n### Writing & Academic\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| ✏️ All-around Writer | Professional writing in any style — essays, articles, fiction | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002F%E2%9C%8F%EF%B8%8FAll-around%20Writer%20%28Professional%20Version%29.md) |\n| 👌 Academic Assistant Pro | Academic writing with a professorial touch — papers, citations, analysis | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002F%F0%9F%91%8CAcademic%20Assistant%20Pro.md) |\n| 🖋 Literature Professor | Essay writing and literary analysis from a professor's perspective | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FLiterature_Professor.md) |\n| 📝 Technical Writer | Senior dev-docs writer — Stripe\u002FTwilio\u002FGoogle standards; blog posts, API docs, release notes, READMEs; no padding (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ftechnical_writer.txt) |\n| 📑 Academic Peer Reviewer | Comprehensive manuscript review — contribution assessment, methodology critique, reproducibility, ethics, constructive feedback, recommendation with confidence (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FAcademic_Peer_Reviewer.txt) |\n| 📄 Research Paper Proofreader | Claude Code\u002FCodex paper proofreading — two-phase detect-then-fix workflow, 9 review categories (language, clarity, structure, LaTeX, notation), severity-graded issues, anti-AI-slop rules; based on LimHyungTae\u002Fawesome-claudecode-paper-proofreading (Mar 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fresearch_paper_proofreader.txt) |\n| 🗣 Talk-Normal Enabler | System prompt that removes AI slop — direct, informative, no filler\u002Ffluff\u002Fsummary-stamps, no negation-based contrastive phrasing; 72–73% token reduction on GPT-4o-mini\u002FGPT-5.4 with zero information loss; based on hexiecs\u002Ftalk-normal (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Ftalk_normal_enabler.txt) |\n| ✍️ Humanizer | Writing editor that removes 29 signs of AI-generated text — detects inflated symbolism, promotional language, vague attributions, AI vocabulary, passive voice, filler phrases; supports voice calibration via writing samples; dual-pass audit workflow; based on blader\u002Fhumanizer (Jan 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fhumanizer.txt) |\n| 🎩 Agent Style Enforcer | Literature-backed technical-prose writing ruleset — 21 rules (12 canonical from Strunk & White\u002FOrwell\u002FPinker\u002FGopen & Swan + 9 field-observed from LLM output 2022–2026) with severity tiers, BAD\u002FGOOD examples, and escape hatch; drop-in for any AI agent producing `.md`, `.tex`, `.rst`, or source-code comments; based on yzhao062\u002Fagent-style (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_style_enforcer.txt) |\n| 🧬 Nature-Style Scientific Writer | Submission-grade scientific writing and figure architect for Nature-family journals — argument-first drafting, hourglass structure, section-specific templates (abstract\u002Fintroduction\u002Fresults\u002Fdiscussion), verb calibration, publication-quality Python\u002FR figure pipelines, data-availability ethics, and Chinese-author support; based on Yuan1z0825\u002Fnature-skills (Apr 2026, 7.3k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fnature_style_scientific_writer.txt) |\n\n### Learning & Education\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🦌 Mr. Ranedeer v2.7 | Fully customizable AI tutor — depth, learning style, tone, reasoning framework (updated Mar 2025) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FMr_Ranedeer.txt) |\n| 📗 All-around Teacher | Adaptive tutor — explains anything in 3 minutes, customized to your level | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002F%F0%9F%93%97All-around%20Teacher.md) |\n| 🚀 LearnOS PRO | Interactive learning assistant with dynamic, personalized explanations | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FLearnOS_PRO.txt) |\n| 🏛 Socratic Tutor | Guides students to understanding through questions, not answers — works for any subject (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsocratic_tutor.txt) |\n| 🧠 Adaptive Learning Designer | AI-driven personalized education — knowledge tracing, spaced repetition, intelligent tutoring, learning analytics, engagement design, ethical safeguards (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FAdaptive_Learning_Designer.txt) |\n\n### Research & Analysis\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🔬 Deep Research Agent | Multi-step research system prompt — plan, search, cross-check, synthesize (2025) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdeep_research.txt) |\n| 🧮 AI Co-Mathematician | Interactive research partner for open-ended mathematical discovery — ideation, literature bridging, computational exploration, conjecture formation, theorem proving, theory building; manages uncertainty, tracks dead ends, refines intent across turns; scored 48% on FrontierMath Tier 4; based on Google DeepMind's AI Co-Mathematician (arXiv 2605.06651, May 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fai_co_mathematician.txt) |\n| 📊 Data Analysis | Extract insights, flag anomalies, recommend specific visualizations | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdata_analysis.txt) |\n| 📈 Data Analyst | Senior analyst translating data into insights — SQL, A\u002FB testing, cohort analysis, metrics, visualization, statistical rigor, actionable recommendations (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdata_analyst.txt) |\n| 🧠 Reasoning Specialist | Structured thinking for complex problems — problem decomposition, CoT reasoning, hypothesis generation, multi-path exploration, confidence assessment (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Freasoning_specialist.txt) |\n| 🔍 Emotion-Aware Research Partner | Research collaborator grounded in Anthropic's 2026 emotion-vectors research — explicit confidence calibration, bias flagging, honest uncertainty, intellectual honesty over authoritative-sounding guesses (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Femotion_aware_research_partner.txt) |\n| 🎨 Multimodal Analyst | Vision-text-data integration — image analysis, document processing, chart interpretation, scene understanding, cross-modal reasoning (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmultimodal_analyst.txt) |\n| 🌐 Autonomous Web Agent | Long-horizon web research agent — search, browse, extract, verify, synthesize; tool discipline, confirmation gates, prompt-injection resistance (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fautonomous_web_agent.txt) |\n| 🗂 Structured Output Extractor | Schema-strict JSON extraction — type safety, null handling, multi-record, self-validation (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fstructured_output_extractor.txt) |\n| 📈 Investment Research Analyst | Senior equity analyst — business model assessment, financial health, competitive moat, valuation (DCF\u002Fcomps), bull\u002Fbear thesis (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Finvestment_research_analyst.txt) |\n| 🗺 Market Research Strategist | Market research director — market sizing (bottom-up + top-down), segmentation, competitive map, white-space opportunities, GTM recommendations (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmarket_research_strategist.txt) |\n\n### Productivity & Tasks\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| ✅ GTD Productivity Assistant | Full GTD system — capture, clarify, organize, reflect, weekly review; implicit task detection (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fproductivity_assistant_gtd.txt) |\n| 🎧 Customer Support Agent | Empathetic SaaS support agent — single-interaction resolution, tone calibration, escalation rules, no spin (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcustomer_support_agent.txt) |\n| 🎯 Deep Work Facilitator | Sustained focus system design — attention audit, time blocking, flow state engineering, digital environment design, cognitive load management, team protocols (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FDeep_Work_Facilitator.txt) |\n| 📅 Executive Operations Partner | C-suite support operations — calendar stewardship, strategic prioritization, communication management, meeting excellence, travel logistics, board coordination, AI-augmented executive enablement (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FExecutive_Operations_Partner.txt) |\n| 💼 Career Operations Agent | Strategic job-search system — 6-block evaluation, ATS-optimized CV deltas, STAR+Reflection interview prep, negotiation scripts, pipeline integrity; filter-not-spray philosophy with human-in-the-loop; based on santifer\u002Fcareer-ops (Apr 2026, 44k+ stars) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcareer_operations_agent.txt) |\n\n### Safety & Compliance\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| 🛡 Content Moderator | CoT-based content moderation — policy-driven ALLOW\u002FBLOCK classification with thinking trace and structured verdict (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcontent_moderator.txt) |\n| 🧱 Prompt Injection Guardian | Security-first browsing\u002Ffile agent prompt — treats external content as untrusted, enforces source tracing, confirmation gates, least privilege; derived from OpenAI's 2026 prompt injection guidance | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fprompt_injection_guardian.txt) |\n| 🧪 Computer Use Safety Tester | Red-team prompt for browser\u002Fdesktop agents — indirect injection, data exfiltration, domain confusion, unsafe confirmation skipping, long-horizon degradation; derived from OpenAI's 2026 safety guidance | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcomputer_use_safety_tester.txt) |\n| 🔐 Security Researcher | Threat modeling (STRIDE), vulnerability assessment, attack surface enumeration, exploit analysis, defense recommendations (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fsecurity_researcher.txt) |\n| ✅ QA Agent | Critical quality assurance — edge cases, error handling, security (OWASP), performance, integration, observability testing (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fqa_agent.txt) |\n| ♿ Accessibility Auditor | WCAG 2.2 AA auditor — screen reader testing, keyboard navigation, ARIA patterns, assistive tech, CI\u002FCD integration, legal compliance (ADA\u002FEAA\u002F508) (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Faccessibility_auditor.txt) |\n| 🎯 Threat Detection Engineer | SOC detection engineering — Sigma rules, SIEM (Splunk\u002FSentinel\u002FElastic), MITRE ATT&CK coverage mapping, threat hunting, detection-as-code CI\u002FCD (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fthreat_detection_engineer.txt) |\n| 🎯 Goal Drift Auditor | Prompt for stress-testing system prompts against multi-turn value-conflict attacks — privacy, security, boundaries, compliance; based on ICLR 2026 agent-drift research (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fgoal_drift_auditor.txt) |\n| 🕸 Agent Skill Supply-Chain Security Auditor | Supply-chain security audit for agent skill ecosystems — DDIPE poisoning detection, MCP schema hardening, cross-skill propagation analysis, provenance verification, least-privilege harness review; based on 2026 agent skill supply-chain attack research (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_skill_supply_chain_auditor.txt) |\n| 🎭 Agent Red Team Architect | End-to-end adversarial test architect for AI agent systems — kill-chain design, indirect injection, multi-turn escalation, cross-channel attacks, ecosystem propagation, automated red-team pipelines; based on Black Hat 2026, USENIX Security 2026, and OpenAI 2026 safety research (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_red_team_architect.txt) |\n| 🔐 Plan-Execute Safety Architect | Architectural plan-then-execute separation with formal safety guarantees — planner never acts, executor never plans, immutable plan artifacts, verification gates, least-privilege scoping; based on Parallax: Why AI Agents That Think Must Never Act (arXiv 2604.12986, April 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fplan_execute_safety_architect.txt) |\n| 🔓 Agent Permission Auto-Mode Architect | Two-layer permission classifier for agentic tools — fast heuristic filter + model-based risk scorer, read-vs-write auto-approval policies, blast-radius gates, user-override protocols, and audit-driven threshold tuning; based on Anthropic's Claude Code Auto Mode (Mar 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_permission_auto_mode_architect.txt) |\n| 🏛 OWASP Secure Application Architect | Staff-level security architect — threat-informed design, OWASP Top 10:2025, ASVS 5.0, LLM Top 10 2025, Agentic AI Security 2026, language-specific secure patterns for 20+ stacks; based on agamm\u002Fclaude-code-owasp (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fowasp_secure_application_architect.txt) |\n| 🛡 Cybersecurity Skill Architect | Production-grade cybersecurity skill architect for AI agents — agentskills.io standard with YAML frontmatter, five-framework cross-mapping (MITRE ATT&CK v18, NIST CSF 2.0, MITRE ATLAS v5.4, D3FEND v1.3, NIST AI RMF 1.0), progressive disclosure (~30-token frontmatter scan \u002F 500–2K-token full workflow), 26-domain coverage, structured When-to-Use\u002FPrerequisites\u002FWorkflow\u002FVerification\u002FOutput-Format; based on mukul975\u002FAnthropic-Cybersecurity-Skills (Feb 2026, 6.3k+ stars, 754 skills) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fcybersecurity_skill_architect.txt) |\n\n### Meta & Prompt Engineering\n\n| Name | Description | Prompt |\n|------|-------------|--------|\n| ⚡ Chain of Draft | Minimal reasoning scratchpad — 5 words per step, 92% fewer tokens vs CoT (arXiv 2502.18600) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fchain_of_draft.txt) |\n| 🗜 Prompt Compression Strategist | Production decision framework for *structural* prompt compression (LLMLingua \u002F LongLLMLingua \u002F LLMLingua-2 \u002F Selective Context \u002F RECOMP) — workload profiling, compressor-family selection by prompt structure, per-workload ratio sweeps with slice-level accuracy budgets, end-to-end latency break-even that includes compressor overhead, per-hardware-class measurement (no extrapolation), pre-compression audit (system-prompt trim \u002F few-shot reduction \u002F retrieval tightening \u002F prefix caching), feature-flag rollout with kill switch, no-compress carve-outs for structured-output and safety-critical prompts; based on \"Prompt Compression in the Wild\" (arXiv 2604.02985, ECIR 2026, 30K queries on 3 GPU classes; up to 18% speedup *only* when prompt\u002Fratio\u002Fhardware match) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fprompt_compression_strategist.txt) |\n| 🧠 Reasoning Model Prompting | Guide + templates for o1\u002Fo3\u002FClaude thinking\u002FGemini — what to do, what NOT to do, effort control (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Freasoning_model_prompting.txt) |\n| 💬 Disclosure Policy Designer | Side-by-Side (SxS) interleaved reasoning strategist — designs when an agent should reveal reasoning vs. keep it private in streaming interfaces; support-threshold gating, update-granularity ladders, silence-tax management, anti-filler rules, correction protocols for commitment bias; based on \"When to Think, When to Speak\" (arXiv 2605.03314, ICML 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fdisclosure_policy_designer.txt) |\n| ⚛ Meta Prompt | Meta-Expert orchestrates specialist sub-agents to solve complex problems | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fmeta_prompt.txt) |\n| 📓 Prompt Creator | Auto-generates high-quality prompts from a brief description | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002FPrompt%20Creater.md) |\n| 🧪 Eval & Benchmark Architect | Benchmark design, evaluation metrics, rubric development, failure mode analysis, continuous monitoring — regression testing, cost-effective evaluation (2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Feval_benchmark_architect.txt) |\n| 📏 Agent Eval Designer | Evaluation prompt for real-world agents — task suites, noise audits, reproducibility, intervention\u002Fsafety metrics, failure taxonomy; derived from Anthropic's 2026 eval guidance | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_eval_designer.txt) |\n| 🛡 Agent Reliability Engineer | Reliability-engineering prompt that separates reliability from capability — four-dimension scorecard (consistency, robustness, predictability, safety\u002Ffault-tolerance), 3D reliability surface R(k, ε, λ) with explicit operating envelopes, chaos-engineering plan with fault injection, harness-hardening checklist (environment-coupled loops, replan triggers, snapshots, typed error contracts, confirmation gates, budgets), pass@1-overestimates-by-20-40% guardrail, unsafe-success detection; based on \"Towards a Science of AI Agent Reliability\" (arXiv 2602.16666, 2026) and \"ReliabilityBench: Evaluating LLM Agent Reliability Under Production-Like Stress\" (arXiv 2601.06112, 2026) | [prompt](https:\u002F\u002Fgithub.com\u002Fai-boost\u002Fawesome-prompts\u002Fblob\u002Fmain\u002Fprompts\u002Fagent_reliability_engineer.txt) |\n| 🔎 Agent Trajectory Triage Specialist | Post-deployment trajectory sampling and triage prompt — three-dimensional signal taxonomy (interaction \u002F execution \u002F environment), cheap-rules-first extractors, diversified ranking, reviewer-feedback loop, explicit privacy-redaction step; designed to lift informative traces over random sampling without ground-truth labels; based on \"Signals: Trajectory Sampling ","awesome-prompts 是一个精选的聊天GPT提示列表，来源于GPT商店中评价最高的模型。该项目不仅汇集了各种可以直接复制粘贴使用的提示模板，还深入探讨了提示工程、提示攻击与防护等高级主题，并提供了相关研究论文。其核心功能在于通过精心设计的提示来优化与大语言模型的交互效果，特别强调了从工程角度出发的方法论和工具集。适合需要提升与AI对话质量的各种场景使用，包括但不限于软件开发、数据处理、产品管理、教育学习等领域。",2,"2026-06-11 03:48:41","high_star"]