Agent skills
Skills you can use with AI coding agents, indexed from public GitHub repositories.
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review-pr
Review a pull request (GitHub) or merge request (GitLab) and provide detailed feedback
desplega-ai/agent-swarm 335
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respond-github
Respond to a GitHub issue/PR or GitLab issue/MR
desplega-ai/agent-swarm 335
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start-worker
Start an Agent Swarm Worker
desplega-ai/agent-swarm 335
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todos
Handle the agent personal todos.md file
desplega-ai/agent-swarm 335
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create-pr
Create a pull request (GitHub) or merge request (GitLab) from the current branch
desplega-ai/agent-swarm 335
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review-offered-task
Review a task that has been offered to you and decide whether to accept or reject it
desplega-ai/agent-swarm 335
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swarm-local-e2e
Guide for running local E2E tests with API server, Docker lead/worker containers, task creation, log verification, UI dashboard, and cleanup
desplega-ai/agent-swarm 335
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nw-jtbd-analysis
JTBD methodology for extracting real jobs behind feature requests — job statements, abstraction layers, first-principles extraction, ODI outcome statements, and opportunity scoring
nWave-ai/nWave 341
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nw-stress-analysis
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.
nWave-ai/nWave 341
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nw-bdd-requirements
BDD requirements discovery methodology - Example Mapping, Three Amigos, conversational patterns, Given-When-Then translation, and collaborative specification
nWave-ai/nWave 341
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nw-ux-desktop-patterns
Desktop application UI patterns for product owners. Load when designing native or cross-platform desktop applications, writing desktop-specific acceptance criteria, or evaluating panel layouts and keyboard workflows.
nWave-ai/nWave 341
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nw-abr-critique-dimensions
Review dimensions for validating agent quality - template compliance, safety, testing, and priority validation
nWave-ai/nWave 341
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nw-command-design-patterns
Best practices for command definition files - size targets, declarative template, anti-patterns, and canonical examples based on research evidence
nWave-ai/nWave 341
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nw-discovery-methodology
Question-first approach to understanding user journeys. Load when starting a new journey design or when the discovery phase needs deepening.
nWave-ai/nWave 341
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nw-par-review-criteria
Quality dimensions and review checklist for devop reviews
nWave-ai/nWave 341
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nw-fp-scala
Scala 3 language-specific patterns with ZIO, Cats Effect, and opaque types
nWave-ai/nWave 341
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nw-pbt-go
Go property-based testing with rapid and gopter frameworks
nWave-ai/nWave 341
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nw-source-verification
Source reputation tiers, cross-referencing methodology, bias detection, and citation format requirements
nWave-ai/nWave 341
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nw-fp-domain-modeling
Domain modeling with algebraic data types, smart constructors, and type-level error handling
nWave-ai/nWave 341
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nw-diverger-review-criteria
Review criteria for the nw-diverger-reviewer — validates JTBD rigor, research quality, option diversity, taste application correctness, and recommendation coherence in DIVERGE wave artifacts
nWave-ai/nWave 341
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nw-sar-critique-dimensions
Architecture quality critique dimensions for peer review. Load when performing architecture document reviews.
nWave-ai/nWave 341
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nw-pbt-erlang-elixir
Erlang/Elixir property-based testing with PropEr, PropCheck, and StreamData frameworks
nWave-ai/nWave 341
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nw-po-review-dimensions
Requirements quality critique dimensions for peer review - confirmation bias detection, completeness validation, clarity checks, testability assessment, and priority validation
nWave-ai/nWave 341
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nw-taste-evaluation
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
nWave-ai/nWave 341