{"id":51417120,"url":"https://github.com/bob798/ai-skill-kit","last_synced_at":"2026-07-04T20:30:39.114Z","repository":{"id":340784334,"uuid":"1167555460","full_name":"bob798/ai-skill-kit","owner":"bob798","description":"A curated library of reusable AI skills and prompt templates for LLMs and AI agents to enhance reasoning, productivity, and workflows.","archived":false,"fork":false,"pushed_at":"2026-05-22T10:32:15.000Z","size":179,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-05-22T16:51:17.455Z","etag":null,"topics":["agent-skills","ai","ai-agents","ai-skills","ai-tools","ai-workflows","automation","awesome-list","career-tools","job-search","llm","prompt-engineering","prompt-library","resume-optimization"],"latest_commit_sha":null,"homepage":"","language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/bob798.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-02-26T12:27:26.000Z","updated_at":"2026-05-22T10:32:18.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/bob798/ai-skill-kit","commit_stats":null,"previous_names":["bob798/skills","bob798/ai-skill-kit"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/bob798/ai-skill-kit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bob798%2Fai-skill-kit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bob798%2Fai-skill-kit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bob798%2Fai-skill-kit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bob798%2Fai-skill-kit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/bob798","download_url":"https://codeload.github.com/bob798/ai-skill-kit/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/bob798%2Fai-skill-kit/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":35135341,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-07-04T02:00:05.987Z","response_time":113,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["agent-skills","ai","ai-agents","ai-skills","ai-tools","ai-workflows","automation","awesome-list","career-tools","job-search","llm","prompt-engineering","prompt-library","resume-optimization"],"created_at":"2026-07-04T20:30:38.471Z","updated_at":"2026-07-04T20:30:39.108Z","avatar_url":"https://github.com/bob798.png","language":"Shell","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI Skill Kit\n\nA curated collection of reusable, structured **AI skills** — each is a complete methodology + prompt + workflow that helps LLMs perform complex tasks more effectively.\n\nNot just prompt snippets. Each skill is a **battle-tested playbook** with clear structure, ready to plug into any LLM workflow.\n\nDesigned for:\n\n- Claude / ChatGPT / Gemini / Open-source LLMs\n- AI Agents \u0026 Copilot-style assistants\n- Developers and knowledge workers\n\n\u003e **[中文版 README](README_CN.md)**\n\n---\n\n## What Makes This Different\n\n| | Prompt Collections | AI Skill Kit |\n|--|--|--|\n| Structure | One-liner prompts | Methodology + framework + examples |\n| Reusability | Copy-paste | Modular, plug into any workflow |\n| Quality control | Community contributed | Each skill tested and iterated |\n| Scope | Generic tasks | Domain-specific deep skills |\n\n---\n\n## Skill Categories\n\n```\nai-skill-kit/\n├── ai-engineering/     # RAG, Agent, Prompt, LLM debugging\n├── career/             # Interview, resume, capability profiling\n├── analysis/           # Decision making, product strategy, deep analysis\n├── learning/           # Structured learning paths, topic analysis\n├── creative/           # Writing, illustration, SVG generation\n├── development/        # Testing, evaluation, debugging\n└── workflow/           # Automation, statistics, weekly review\n```\n\n---\n\n## Skill Index\n\n### AI Engineering\n\n| Skill | Description |\n|------|------|\n| [rag-evaluator](ai-engineering/rag-evaluator) | Diagnose RAG pipeline issues across retrieval, generation, and consistency layers |\n| [prompt-optimizer](ai-engineering/prompt-optimizer) | Identify root causes of prompt failures and apply structured fixes |\n| [agent-designer](ai-engineering/agent-designer) | Design ReAct / Plan-Execute / Multi-Agent architectures with failure handling |\n| [llm-debugger](ai-engineering/llm-debugger) | Debug LLM apps in production: API errors, rate limits, token overflow, streaming |\n| [vector-db-guide](ai-engineering/vector-db-guide) | Vector DB selection and usage: Chroma, Milvus, pgvector, Qdrant compared |\n| [langchain-patterns](ai-engineering/langchain-patterns) | Core LangChain patterns: LCEL, RAG chain, memory, agents with real code |\n| [ai-solution-designer](ai-engineering/ai-solution-designer) | Design AI solutions with scenario evaluation, architecture, risk and ROI analysis |\n\n### Career\n\n| Skill | Description |\n|------|------|\n| [mock-interview](career/mock-interview) | Generate high-value interview questions with answer frameworks based on resume + JD |\n| [job-seeker-resume-cn](career/job-seeker-resume-cn) | Chinese resume optimization for general job market with platform algorithm strategies |\n| [ai-job-transition-resume](career/ai-job-transition-resume) | Resume optimization for AI engineer / AI pre-sales roles |\n| [ai-engineer-interviewer](career/ai-engineer-interviewer) | Conduct technical interviews for AI engineering positions with role-specific evaluation |\n| [interview-sparring](career/interview-sparring) | Diagnostic interview practice with dynamic weak-point identification and coaching |\n| [capability-miner](career/capability-miner) | Extract structured capability profiles from project memory and Git history |\n\n### Analysis\n\n| Skill | Description |\n|------|------|\n| [product-analysis](analysis/product-analysis) | Multi-dimensional product strategy analysis (user / solution / business / competition / risk) |\n| [decision-tree](analysis/decision-tree) | Structured decision making with explicit recommendations |\n| [deep-analysis](analysis/deep-analysis) | Multi-perspective Self-Debate: generate, critique, refine, loops until score \u003e= 8 |\n\n### Learning\n\n| Skill | Description |\n|------|------|\n| [learn-anything](learning/learn-anything) | Structured learning path for any technology or skill |\n| [atdf-analyzer](learning/atdf-analyzer) | Systematically analyze AI topics using 8-dimensional ATDF framework |\n\n### Creative\n\n| Skill | Description |\n|------|------|\n| [article-illustrator](creative/article-illustrator) | SVG illustrations for articles and visual communication |\n| [article-writer](creative/article-writer) | Structured article generation from notes, outlines, or rough content |\n| [svg-generator](creative/svg-generator) | User-goal-first SVG generation workflow |\n| [svg-to-png](creative/svg-to-png) | Reliable SVG to PNG conversion with tool fallbacks |\n| [knowledge-viz](creative/knowledge-viz) | Knowledge Dynamization Engine — turn abstract concepts into interactive dark-themed HTML experiences |\n| [iceberg-knowledge-map](creative/iceberg-knowledge-map) | Render any knowledge domain as an interactive iceberg: linear main-line on the surface, layered deep-dives below, relation graph at the bottom |\n| [frontend-design](creative/frontend-design) | Distinctive, production-grade frontend interfaces that avoid generic AI aesthetics |\n\n### Development\n\n| Skill | Description |\n|------|------|\n| [add-tests](development/add-tests) | Add unit tests to existing code, identify testable functions, and ensure all tests pass |\n| [test-audit](development/test-audit) | Full-dimension test audit (React/Next.js): Unit/API/Component/Security/Integration/E2E coverage analysis and auto-generation |\n| [ok-testaudit-nuxt](development/ok-testaudit-nuxt) | Test-coverage audit for Nuxt 3 + Vitest + Playwright frontends — gap analysis and missing-test generation aligned to real Nuxt conventions |\n| [ok-testaudit-server](development/ok-testaudit-server) | Test-coverage audit for Spring Boot + Spring AI backends — multi-tenant isolation \u0026 LLM tool-chain gaps, JUnit/Mockito/Testcontainers/WireMock |\n| [ok-itest](development/ok-itest) | Generate executable integration-test specs, skeletons, and PR reports for Spring Boot + Spring AI (WireMock + Testcontainers + tenant isolation) |\n| [eval-debug](development/eval-debug) | Analyze interview JSONL files for model quality and program logic debugging |\n| [rag-eval](development/rag-eval) | Analyze RAG experimental results, interpret metrics, and identify anomalies |\n\n### Workflow\n\n| Skill | Description |\n|------|------|\n| [cc-stats](workflow/cc-stats) | Generate Claude Code usage statistics and productivity insights |\n| [claude-scheduler](workflow/claude-scheduler) | Schedule Claude Code tasks using macOS launchd for persistent background execution |\n| [retro](workflow/retro) | Analyze recent conversations to identify repeated operations for automation |\n| [weekly-output](workflow/weekly-output) | Synthesize weekly notes using BASB, Zettelkasten, T-shape, and GTD frameworks |\n| [weekly-report](workflow/weekly-report) | Single-page weekly status report PNG + Markdown for stakeholder reporting |\n\n---\n\n## Usage\n\nEach skill folder contains a `SKILL.md` with the complete prompt and methodology. To use a skill:\n\n1. Open the `SKILL.md` file in the skill folder\n2. Copy the prompt into your LLM conversation\n3. Follow the structured workflow\n\n---\n\n## License\n\nMIT\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbob798%2Fai-skill-kit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbob798%2Fai-skill-kit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbob798%2Fai-skill-kit/lists"}