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Claude Skills

The open format is called Agent Skills and works in Claude Code, Codex, Cursor and other agents — most people know it as Claude Skills.

Every Agent Skill we could find on GitHub, deduplicated by content. 79 566 files from 1 758 authors, of which 61 913 are unique — the rest is the same skill repackaged into someone else's repository. For each one: what it weighs in tokens, whether it ships runnable scripts, and which MCP servers it needs.

61 913
unique skills
out of 79 566 files found on GitHub
17 653
are copies
same content, someone else's repository
1 739
tokens, median
what a typical skill costs you in context
7 886
name collisions
two skills with one name cannot sit side by side

15 541–15 600 of 61 913

page 260 of 1 032
Nw Jtbd Opportunity Scoring
by nWave-ai

JTBD opportunity scoring and prioritization - outcome statement format, opportunity algorithm, scoring interpretation, feature prioritization, and opportunity matrix template

2k tokens
Nw Jtbd Interviews
by nWave-ai

JTBD discovery techniques adapted for AI product owner context. Four Forces extraction, job dimension probing, question banks, and anti-patterns for interactive feature discovery conversations.

2k tokens
Nw Jtbd Workflow Selection
by nWave-ai

JTBD workflow classification and routing - ODI two-phase framework, five job types with workflow sequences, baseline type selection, workflow anti-patterns, and common recipes

2k tokens
Nw Leanux Methodology
by nWave-ai

LeanUX backlog management methodology - user story template, story sizing, story states, task types, Definition of Ready/Done, anti-pattern detection and remediation

2k tokens
Nw Legacy Refactoring Ddd
by nWave-ai

DDD-guided legacy refactoring patterns -- strangler fig, bubble context, ACL migration, 14 tactical/strategic/infrastructure patterns, and incremental monolith-to-microservices methodology

2k tokens
Nw Mutation Test
by nWave-ai

Runs feature-scoped mutation testing to validate test suite quality. Use after implementation to verify tests catch real bugs (kill rate >= 80%).

1k tokens
Nw Mikado
by nWave-ai

[EXPERIMENTAL] Complex refactoring roadmaps with visual tracking

609 tokens
Nw Mikado Method
by nWave-ai

Enhanced Mikado Method for complex architectural refactoring - systematic dependency discovery, tree-based planning, and bottom-up execution

1k tokens
Nw Operational Safety
by nWave-ai

Tool safety protocols, adversarial output validation, error recovery patterns, and I/O contracts for research operations

1k tokens
Nw Opportunity Mapping
by nWave-ai

Opportunity Solution Trees, opportunity scoring, Lean Canvas, JTBD job mapping, and technique selection guide

915 tokens
Nw New
by nWave-ai

Guided wizard to start a new feature. Asks what you want to build, recommends the right starting wave, and launches it.

1k tokens
Nw Optimize Tests
by nWave-ai

Minimizes test count while preserving coverage. Detects byte-identical pairs, parametrize-inflation, language-guarantee tests, AST-shape tests, stale migration nets. Approval gate before any change.

1k tokens
Nw Par Critique Dimensions
by nWave-ai

Platform design review critique dimensions and severity levels. Load when reviewing CI/CD pipelines, infrastructure, deployment strategies, observability, or security designs.

1k tokens
Nw Par Review Criteria
by nWave-ai

Quality dimensions and review checklist for devop reviews

1k tokens
Nw Pdr Review Criteria
by nWave-ai

Evidence quality validation and decision gate criteria for product discovery reviews

1k tokens
Nw Outcome Kpi Framework
by nWave-ai

Outcome KPI definition methodology - synthesizes Who Does What By How Much (Gothelf/Seiden), Running Lean (Maurya), and Measure What Matters (Doerr) into a practical framework for measurable outcome KPIs

3k tokens
Nw Po Review Dimensions
by nWave-ai

Requirements quality critique dimensions for peer review - confirmation bias detection, completeness validation, clarity checks, testability assessment, and priority validation

2k tokens
Nw Persona Jtbd Analysis
by nWave-ai

Structured persona creation and JTBD analysis methodology - persona templates, ODI job step tables, pain point mapping, success metric quantification, and multi-persona segmentation

1k tokens
Nw Platform Engineering Foundations
by nWave-ai

Foundational platform engineering knowledge from key references -- Continuous Delivery, SRE, Accelerate, Team Topologies, Chaos Engineering, and Secure Delivery. Load when contextual grounding in platform engineering theory is needed.

1k tokens
Nw Production Readiness
by nWave-ai

Monitoring, observability, operational procedures, CI/CD lessons learned, and quality gate definitions. Load when assessing production readiness or validating operational excellence.

679 tokens
Nw Por Review Criteria
by nWave-ai

Review dimensions and bug patterns for journey artifact reviews

1k tokens
Nw Post Mortem Framework
by nWave-ai

Blameless post-mortem structure, incident timeline reconstruction, response evaluation, and organizational learning

758 tokens
Nw Production Safety
by nWave-ai

Agent safety boundaries - input validation, output filtering, scope constraints, and document creation policy

471 tokens
Nw Progressive Refactoring
by nWave-ai

Progressive L1-L6 refactoring hierarchy, 22 code smell taxonomy, atomic transformations, test code smells, and Fowler refactoring catalog

2k tokens
Nw Property Based Testing
by nWave-ai

Property-based testing strategies, mutation testing, shrinking, and combined PBT+mutation workflow for test quality validation

2k tokens
Nw Quality Validation
by nWave-ai

Type-specific validation checklists, six quality characteristics, and quality gate thresholds for documentation assessment

538 tokens
Nw Quality Framework
by nWave-ai

Quality gates - 11 commit readiness gates, build/test protocol, validation checkpoints, and quality metrics

3k tokens
Nw Research
by nWave-ai

Gathers knowledge from web and files, cross-references across multiple sources, and produces cited research documents. Use when investigating technologies, patterns, or decisions that need evidence backing.

2k tokens
Nw Refactor
by nWave-ai

Applies the Refactoring Priority Premise (RPP) levels L1-L6 for systematic code refactoring. Use when improving code quality through structured refactoring passes.

1k tokens
Nw Review Output Format
by nWave-ai

YAML output format and approval criteria for platform design reviews. Load when generating review feedback.

615 tokens
Nw Query Optimization
by nWave-ai

SQL and NoSQL query optimization techniques, indexing strategies, execution plan analysis, JOIN algorithms, cardinality estimation, and database-specific query patterns

1k tokens
Nw Review Workflow
by nWave-ai

Detailed review process, v2 validation checklist, and scoring methodology for agent definition reviews

758 tokens
Nw Research Methodology
by nWave-ai

Research output templates, distillation workflow, and quality standards for evidence-driven research

1k tokens
Nw Rigor
by nWave-ai

Selects a quality-vs-token-consumption profile (lean, standard, thorough, exhaustive, custom, inherit) and persists it globally (~/.nwave/global-config.json) or per-project (.nwave/des-config.json). Use when tuning how much rigor wave commands apply.

5k tokens
Nw Review
by nWave-ai

Dispatches an expert reviewer agent to critique workflow artifacts. Use when a roadmap, implementation, or step needs quality review before proceeding.

2k tokens
Nw Roadmap
by nWave-ai

Creates a phased roadmap.json for a feature goal with acceptance criteria and TDD steps. Use when planning implementation steps before execution.

2k tokens
Nw Root Why
by nWave-ai

Root cause analysis and debugging

693 tokens
Nw Roadmap Review Checks
by nWave-ai

Roadmap-specific validation checks for architecture reviews. Load when reviewing roadmaps for implementation readiness.

747 tokens
Nw Sar Critique Dimensions
by nWave-ai

Architecture quality critique dimensions for peer review. Load when performing architecture document reviews.

1k tokens
Nw Roadmap Design
by nWave-ai

Roadmap concision rules, step decomposition efficiency, AC abstraction guidelines, and step-to-scenario mapping. Load when creating implementation roadmaps.

2k tokens
Nw Rr Critique Dimensions
by nWave-ai

Critique dimensions and scoring for research document reviews

968 tokens
Nw Sa Critique Dimensions
by nWave-ai

Architecture quality critique dimensions for peer review. Load when invoking solution-architect-reviewer or performing self-review of architecture documents.

1k tokens
Nw Sc Review Dimensions
by nWave-ai

Reviewer critique dimensions for peer review - implementation bias detection, test quality validation, completeness checks, and priority validation

3k tokens
Nw Sd Framework
by nWave-ai

4-step system design framework with back-of-envelope estimation, scaling ladder, and common pitfalls

1k tokens
Nw Sd Case Studies
by nWave-ai

25 real-world system design case studies condensed from Alex Xu's System Design Interview Vol 1 and 2 - requirements, architecture, deep dive insights, key takeaways

3k tokens
Nw Sd Patterns Advanced
by nWave-ai

Advanced distributed patterns - event sourcing, CQRS, saga, stream processing, append-only log, exactly-once delivery, sequencer, double-entry ledger, erasure coding, order book, watermarks

2k tokens
Nw Shared Artifact Tracking
by nWave-ai

Shared artifact registry, common artifact patterns, and integration validation. Load when tracking data that flows across journey steps or validating horizontal coherence.

978 tokens
Nw Security And Governance
by nWave-ai

Database security (encryption, access control, injection prevention), data governance (lineage, quality, MDM), and compliance frameworks (GDPR, CCPA, HIPAA)

2k tokens
Nw Sd Patterns
by nWave-ai

Core distributed systems patterns - load balancing, caching, sharding, consistent hashing, message queues, rate limiting, CDN, Bloom filters, ID generation, replication, conflict resolution, CAP theorem

2k tokens
Nw Security By Design
by nWave-ai

Security design principles, STRIDE threat modeling, OWASP Top 10 architectural mitigations, and secure patterns. Load when designing systems or reviewing architecture for security.

2k tokens
Nw Source Verification
by nWave-ai

Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements

627 tokens
Nw Speculative Dispatch
by nWave-ai

Speculative parallel implementation methodology — dispatch N candidate implementations, audit all, score, pick best. Auditability mandate: ALL candidates logged (not just winner).

2k tokens
Nw Spike Methodology
by nWave-ai

Teaches agents how to run a timeboxed spike - throwaway code that validates one assumption before DESIGN

936 tokens
Nw Spike
by nWave-ai

Runs a timeboxed PROBE to validate one core assumption, then optionally PROMOTES the probe into a walking skeleton — the first e2e thin slice of the feature, committed and demo-able. Use after DISCUSS when the feature involves a new mechanism, performance requirement, or external integration.

3k tokens
Nw Stakeholder Engagement
by nWave-ai

Demonstration preparation, audience-tailored presentations, feedback collection, and business outcome measurement. Load when preparing demos or measuring business value delivery.

980 tokens
Nw Stress Analysis
by nWave-ai

Advanced architecture stress analysis methodology for designing systems that survive unknown stresses. Load when --residuality flag is used or when designing high-uncertainty, mission-critical systems.

1k tokens
Nw Taste Evaluation
by nWave-ai

Design taste evaluation framework — DVF primary filter, Apple/Google/Jobs design principles as explicit scoring criteria, weighted decision matrix, and option ranking for the DIVERGE wave

2k tokens
Nw Tdd Methodology
by nWave-ai

Deep knowledge for Outside-In TDD - double-loop architecture, ATDD integration, port-to-port testing, walking skeletons, and test doubles policy

9k tokens
Nw Tdd Cross Language
by nWave-ai

Port the state-delta + property-based testing paradigm to languages other than Python. DIY recipes per language; canonical Python ref shipped in nwave_ai.state_delta.

3k tokens
Nw Tdd Review Enforcement
by nWave-ai

Test design mandate enforcement, test budget validation, TDD phase validation (3-phase canon per ADR-025), and external validity checks for the software crafter reviewer

3k tokens

Claude Skills — questions

Answers built from the skills we actually parsed.

What is a Claude Skill?
A folder with a SKILL.md file: instructions that teach an agent to do one thing well, optionally with scripts and reference files alongside. The format is open and called Agent Skills — Claude Code, Codex and other agents read the same files. It is not a program you run; it is knowledge the agent loads when the task calls for it.
How is a skill different from an MCP server?
A server gives the agent new abilities — it connects to something and exposes tools. A skill gives the agent knowledge: how to use what it already has. They combine, and often literally: 11 350 of the skills here declare which MCP servers they need to work.
Why are there fewer skills here than in other catalogues?
Because we deduplicate by content. Of 79 566 files found on GitHub, 61 913 are unique — the rest is the same skill copied into someone else's repository, word for word. Catalogues that count files rather than skills show every copy as a separate entry.
What does the token count mean?
A skill is loaded into the model's context when it is used, so its size is a running cost on every request that touches it. We measure the whole folder, not just SKILL.md: one official skill is 377 tokens, another drags 83 files of fonts behind it.
How do I install a skill?
Copy the skill folder into ~/.claude/skills for personal use, or into .claude/skills inside a project. The agent picks it up by the name in the SKILL.md header — which is worth checking: 7 886 skills here share a name with another skill, and two of them cannot sit side by side.