Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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strategy-advisor
High-level strategic thinking and business decision guidance for planning and direction-setting.
Use when: making strategic decisions, evaluating business options, setting direction, analyzing
trade-offs, or when user mentions strategy, business planning, competitive analysis, or long-term planning.
Shubhamsaboo/awesome-llm-apps 105,157
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fullstack-developer
Modern web development expertise covering React, Node.js, databases, and full-stack architecture.
Use when: building web applications, developing APIs, creating frontends, setting up databases,
deploying web apps, or when user mentions React, Next.js, Express, REST API, GraphQL, MongoDB,
PostgreSQL, or full-stack development.
Shubhamsaboo/awesome-llm-apps 105,157
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email-drafter
Professional email composition for business communication across various contexts.
Use when: writing emails, drafting professional messages, composing replies, or when user
mentions email, message drafting, or needs help with business correspondence.
Shubhamsaboo/awesome-llm-apps 105,157
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project-planner
Breaks down complex projects into actionable tasks with timelines, dependencies, and milestones.
Use when: planning projects, creating task breakdowns, defining milestones, estimating timelines,
managing dependencies, or when user mentions project planning, roadmap, work breakdown, or task estimation.
Shubhamsaboo/awesome-llm-apps 105,157
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ux-designer
Expert UX design assistance for user research, wireframing, prototyping, and design strategy.
Use when: creating wireframes, conducting user research, building prototypes, designing user flows,
writing UX copy, reviewing designs for usability, creating personas, planning usability tests,
or when user mentions UX design, user experience, wireframes, prototypes, user research,
information architecture, or design systems.
Shubhamsaboo/awesome-llm-apps 105,157
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academic-researcher
Academic research assistant for literature reviews, paper analysis, and scholarly writing.
Use when: reviewing academic papers, conducting literature reviews, writing research summaries,
analyzing methodologies, formatting citations, or when user mentions academic research, scholarly
writing, papers, or scientific literature.
Shubhamsaboo/awesome-llm-apps 105,157
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debugger
Systematic debugging and root cause analysis for identifying and fixing software issues.
Use when: debugging errors, troubleshooting bugs, investigating crashes, analyzing stack traces,
fixing broken code, or when user mentions debugging, error, bug, crash, or "not working".
Shubhamsaboo/awesome-llm-apps 105,157
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python-expert
Senior Python developer expertise for writing clean, efficient, and well-documented code.
Use when: writing Python code, optimizing Python scripts, reviewing Python code for best practices,
debugging Python issues, implementing type hints, or when user mentions Python, PEP 8, or needs help
with Python data structures and algorithms.
Shubhamsaboo/awesome-llm-apps 105,157
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data-analyst
SQL, pandas, and statistical analysis expertise for data exploration and insights.
Use when: analyzing data, writing SQL queries, using pandas, performing statistical analysis,
or when user mentions data analysis, SQL, pandas, statistics, or needs help exploring datasets.
Shubhamsaboo/awesome-llm-apps 105,157
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editor
Professional editing and proofreading for clarity, grammar, style, and readability improvements.
Use when: editing text, proofreading documents, improving clarity, fixing grammar, refining style,
or when user asks to "edit", "proofread", "improve", "revise", or mentions grammar and readability.
Shubhamsaboo/awesome-llm-apps 105,157
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fact-checker
Systematic fact verification and misinformation identification using evidence-based analysis.
Use when: verifying claims, checking facts, identifying misinformation, evaluating source credibility,
or when user asks to "fact check", "verify", "is this true", or mentions claims that need validation.
Shubhamsaboo/awesome-llm-apps 105,157
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code-reviewer
Thorough code review with focus on security, performance, and best practices.
Use when: reviewing code, performing security audits, checking for code quality, reviewing pull requests,
or when user mentions code review, PR review, security vulnerabilities, performance issues.
Shubhamsaboo/awesome-llm-apps 105,157
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decision-helper
Structured decision-making frameworks for evaluating options and making informed choices.
Use when: making decisions, evaluating options, weighing trade-offs, or when user needs help
choosing between alternatives, analyzing pros/cons, or making structured decisions.
Shubhamsaboo/awesome-llm-apps 105,157
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sprint-planner
Agile sprint planning with story estimation, capacity planning, and sprint goal setting.
Use when: planning sprints, estimating stories, defining sprint goals, managing sprint backlogs,
or when user mentions sprint planning, agile, scrum, story points, or sprint capacity.
Shubhamsaboo/awesome-llm-apps 105,157
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refine-plan
Iteratively refine development plans using TDD methodology. Ensures plans are clear, actionable, and include red-green-refactor cycles with proper test coverage.
coder/coder 12,860
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pull-requests
Guide for creating, updating, and following up on pull requests in the Coder repository. Use when asked to open a PR, update a PR, rewrite a PR description, or follow up on CI/check failures.
coder/coder 12,860
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deep-review
Multi-reviewer code review. Spawns domain-specific reviewers in parallel, cross-checks findings, posts a single structured GitHub review.
coder/coder 12,860
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doc-check
Checks if code changes require documentation updates
coder/coder 12,860
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code-review
Reviews code changes for bugs, security issues, and quality problems
coder/coder 12,860
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skill-creator
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
EvoScientist/EvoScientist 2,732
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find-skills
Helps users discover agent skills from the open ecosystem. Searches skills.sh and presents options for installation via the built-in skill_manager tool.
EvoScientist/EvoScientist 2,732
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research-ideation
Guides research ideation through a 5-step goal-driven workflow: define long-term goal, build literature tree (novelty + challenge-insight), select a problem (well-established solution check), design a solution (cross-domain transfer + decomposition), validate and iterate. Also covers structured paper reading (3 depth levels). Use when: user wants to find a research direction, brainstorm ideas, build field vision, do a literature review, evaluate idea novelty, or read papers systematically. Do NOT use for comparing/ranking existing ideas (use idea-tournament) or planning a paper (use paper-planning).
EvoScientist/EvoSkills 141
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paper-writing
Guides writing academic papers section by section using an 11-step workflow with LaTeX templates and counterintuitive writing tactics. Covers Abstract, Introduction, Method, Experiments, Related Work, Conclusion, and Supplementary. Use when: user asks to write or draft a paper section, needs LaTeX templates, wants to improve academic writing quality, optimize novelty framing, or mentions 'write introduction', 'draft method', 'paper writing'. Do NOT use for pre-submission review (use paper-review), experiment execution (use experiment-pipeline), or paper planning/story design (use paper-planning).
EvoScientist/EvoSkills 141
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evo-memory
Manages persistent research memory across ideation and experimentation cycles. Maintains two stores: Ideation Memory M_I (feasible/unsuccessful directions) and Experimentation Memory M_E (reusable strategies for data processing, model training, architecture, debugging). Three evolution mechanisms: IDE (after idea-tournament), IVE (after experiment failure — classifies failures as implementation vs fundamental), ESE (after experiment success — extracts reusable strategies). Use when: updating memory after completing idea tournaments or experiment pipelines, classifying why a method failed (implementation vs fundamental failure), starting a new research cycle needing prior knowledge, user mentions 'update memory', 'classify failure', 'what worked before', 'research history', 'evolution'. Do NOT use for running experiments (use experiment-pipeline), debugging experiment code (use experiment-craft), or generating ideas (use idea-tournament).
EvoScientist/EvoSkills 141