Research and recommend community-vetted best-in-class libraries for each feature problem in the product (lists, camera, forms, keyboard, sheets), ranked by adoption signal (downloads, dependents, recency, stars-trend, maintenance, platform fit) relative to the project's ecosystem. Stack-agnostic across registries (npm, PyPI, crates.io, Go, Maven). Researches five angles (web, repo, registry, AAA practices, reference repos) and writes FEATURELIBRARIES.md, grounding every pick in a captured REFERENCES.md source; picks are optional guidance. Use when the stack is chosen and you want the canonical per-feature libraries surfaced and vetted. Do not use to pick stack layers (use stack-recommend), to verify a framework's current patterns (use stack-currency-check), to synthesize already-captured sources (use external-research), or with no active task folder (run task-init first). For a deep per-problem sweep, use feature-library-scout-fleet.
Install with
Claude CodeCodexCursorGitHub CopilotGemini CLI
Supported by the Atlas install prompt. Skill-specific requirements vary.
Skill stats
Skills1CategoryProduct & designStars0
About this skill
Research and recommend community-vetted best-in-class libraries for each feature problem in the product (lists, camera, forms, keyboard, sheets), ranked by adoption signal (downloads, dependents, recency, stars-trend, maintenance, platform fit) relative to the project's ecosystem. Stack-agnostic across registries (npm, PyPI, crates.io, Go, Maven). Researches five angles (web, repo, registry, AAA practices, reference repos) and writes FEATURELIBRARIES.md, grounding every pick in a captured REFERENCES.md source; picks are optional guidance. Use when the stack is chosen and you want the canonical per-feature libraries surfaced and vetted. Do not use to pick stack layers (use stack-recommend), to verify a framework's current patterns (use stack-currency-check), to synthesize already-captured sources (use external-research), or with no active task folder (run task-init first). For a deep per-problem sweep, use feature-library-scout-fleet.
Quick start
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Research and recommend community-vetted best-in-class libraries for each feature problem in the product (lists, camera, forms, keyboard, sheets), ranked by adoption signal (downloads, dependents, recency, stars-trend, maintenance, platform fit) relative to the project's ecosystem. Stack-agnostic across registries (npm, PyPI, crates.io, Go, Maven). Researches five angles (web, repo, registry, AAA practices, reference repos) and writes FEATURE_LIBRARIES.md, grounding every pick in a captured REFERENCES.md source; picks are optional guidance. Use when the stack is chosen and you want the canonical per-feature libraries surfaced and vetted. Do not use to pick stack layers (use stack-recommend), to verify a framework's current patterns (use stack-currency-check), to synthesize already-captured sources (use external-research), or with no active task folder (run task-init first). For a deep per-problem sweep, use feature-library-scout-fleet.
About this listing
Category
Product & design
Reported license
MIT
Listing language (estimated)
English
Review status
Not individually reviewed
Agent compatibility
Atlas installation supports Claude Code, Codex, and Cursor. Skill-specific dependencies and features are checked during setup.
Claude Code
Codex
Cursor
GitHub Copilot
Gemini CLI