Agent skills you can check before you install
Public SKILL.md skills from GitHub repositories with 50+ stars and from the vendors themselves, scanned and scored. Install any of them with one command in Claude Code, Cursor, Codex, GitHub Copilot or Gemini CLI.
9,277 skills from 267 repositories · updated 16 minutes ago
618 skills
- quality-checklista5c-ai/babysitterValidate implementation quality through custom checklists, scoring against constitution standards, specification coverage, and producing remediation recommendations.PlanningNo warnings★ 1.9K↓ —
- sprint-planninga5c-ai/babysitterBabysitter enforces obedience on agentic workforces and enables them to manage extremely complex tasks and workflows through deterministic, hallucination-free self-orchestrationPlanningNo warnings★ 1.9K↓ —
- architecture-patternsa5c-ai/babysitterSystem and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.PlanningNo warnings★ 1.9K↓ —
- story-decompositiona5c-ai/babysitterBreak technical specifications into small, implementable stories with dependency orderingPlanningNo warnings★ 1.9K↓ —
- executing-plansa5c-ai/babysitterUse when you have a written implementation plan to execute in a separate session with review checkpoints between batches.PlanningNo warnings★ 1.9K↓ —
- model-profile-resolutiona5c-ai/babysitterResolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.PlanningNo warnings★ 1.9K↓ —
- decision-documentationa5c-ai/babysitterCreate Architecture Decision Records (ADRs) documenting significant technical choices with context, options, consequences, and sequential numbering.PlanningNo warnings★ 1.9K↓ —
- requirements-interviewa5c-ai/babysitterInteractive PM interview with expertise-adaptive questioning for requirements elicitationPlanningNo warnings★ 1.9K↓ —
- zephyr-rtosa5c-ai/babysitterSpecialized skill for Zephyr RTOS development and configurationPlanningNo warnings★ 1.9K↓ —
- arm-cortex-ma5c-ai/babysitterDeep expertise in ARM Cortex-M architecture and peripheralsPlanningNo warnings★ 1.9K↓ —
- specialization-validatora5c-ai/babysitterValidate specialization completeness across all 7 phases, score each phase, identify gaps, and generate validation reports.PlanningNo warnings★ 1.9K↓ —
- specification-generationa5c-ai/babysitterConvert requirements into structured technical specifications with architecture decisionsPlanningNo warnings★ 1.9K↓ —
- cross-artifact-analysisa5c-ai/babysitterPerform cross-artifact consistency and coverage analysis across constitution, specification, plan, and task artifacts to detect gaps, conflicts, and misalignments before implementation.PlanningNo warnings★ 1.9K↓ —
- domain-name-brainstormerComposioHQ/awesome-claude-skillsGenerates creative domain name ideas for your project and checks availability across multiple TLDs (.com, .io, .dev, .ai, etc.). Saves hours of brainstorming and manual checking.PlanningNo warnings★ 77.6K↓ —Also in 3 other repos
- Hunter AutomationComposioHQ/awesome-claude-skillsAutomate Hunter.io email intelligence -- search domains for email addresses, find specific contacts, verify email deliverability, manage leads, and monitor account usage -- using natural language through the Composio MCP integration.PlanningNo warnings★ 77.6K↓ —Also in 1 other repo
- route-to-openapizebbern/claude-code-guideGenerates RESTful API documentation (OpenAPI 3.0 / Swagger spec) by scanning route definitions in code for Flask, FastAPI, Express, Gin, and other frameworks. Trigger when users ask about API documentation, OpenAPI, Swagger, endpoint docs, generating docs from code, or extracting endpoints.PlanningNo warnings★ 4.7K↓ —
- ablation-plannerbrycewang-stanford/Auto-Empirical-Research-SkillsUse when main results pass result-to-claim (claim_supported=yes or partial) and ablation studies are needed for paper submission. Codex designs ablations from a reviewer's perspective, CC reviews feasibility and implements.PlanningNo warnings★ 4.7K↓ —
- brainstormbrycewang-stanford/Auto-Empirical-Research-SkillsUse when starting a new research project, exploring a research idea, deciding whether a question is viable, or before touching code or data for a new paper. Runs a research-focused brainstorm that clarifies research question, identification strategy, data feasibility, and contribution before any implementation.PlanningNo warnings★ 4.7K↓ —
- project-sizing-guidezebbern/claude-code-guideSoftware project effort estimation assistant. Outputs three-point estimates (optimistic/most-likely/pessimistic values with confidence intervals), T-shirt sizes, or Function Point Analysis (FPA) counts. Triggered when users ask 'how long will this feature take,' need to assess project workload, perform PERT estimation, T-shirt sizing, FPA, sprint planning, or quote-based effort breakdowns.PlanningNo warnings★ 4.7K↓ —
- jira-driven-planningbreaking-brake/cc-wf-studioJiraチケットの要件とConfluenceの関連ドキュメントを基に、Frontend/Backend/Infrastructureに分割した実装計画を策定するプランニングスキル。Jiraチケット情報とConfluence検索結果が前段で取得済みであることを前提とし、構造化された実装計画を出力する。「プランニング」「実装計画策定」「タスク分割」などの文脈で使用。PlanningNo warnings★ 5.4K↓ —
- aer-introductionbrycewang-stanford/Auto-Empirical-Research-SkillsUse when drafting or rewriting the introduction of an economics manuscript targeted at AER, AER:Insights, or an AEJ, or when compressing an abstract to the mandatory 100-word limit. Implements the Keith Head / Bellemare five-paragraph formula and AER-specific formatting conventions. Apply after the body sections exist.PlanningNo warnings★ 4.7K↓ —
- matchmsforyourhealth111-pixel/Vibe-SkillsSpectral similarity and compound identification for metabolomics. Use for comparing mass spectra, computing similarity scores (cosine, modified cosine), and identifying unknown compounds from spectral libraries. Best for metabolite identification, spectral matching, library searching. For full LC-MS/MS proteomics pipelines use pyopenms.PlanningNo warnings★ 3.7K↓ —
- execute-planbrycewang-stanford/Auto-Empirical-Research-SkillsUse when a research implementation plan exists in docs/superpapers/plans/ and the user is ready to execute it — collecting data, running analysis, producing outputs, writing the paper. Orchestrates task execution with replication-driven verification and two-stage review at phase boundaries.PlanningNo warnings★ 4.7K↓ —
- experiment-planbrycewang-stanford/Auto-Empirical-Research-SkillsTurn a refined research proposal or method idea into a detailed, claim-driven experiment roadmap. Use after `research-refine`, or when the user asks for a detailed experiment plan, ablation matrix, evaluation protocol, run order, compute budget, or paper-ready validation that supports the core problem, novelty, simplicity, and any LLM / VLM / Diffusion / RL-based contribution.PlanningNo warnings★ 4.7K↓ —
arm-cortex-m
a5c-ai/babysitter
PlanningUpdated Sep 16, 2026
From the author
Deep expertise in ARM Cortex-M architecture and peripherals
Install
npx skills add a5c-ai/babysitter --skill arm-cortex-m -a claude-code
Installs to .claude/skills/arm-cortex-m/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Download .zip
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
What it can touch
Instructions onlyNo network use seenLicence: MIT
Safety checks on SKILL.md
No warnings.
Why 86
Security100
Provenance79
Maintenance85
Licence100
Adoption52
Files (2)
- README.md
- SKILL.md