Search through previous sessions to find relevant decisions, approaches that worked, and approaches that failed. Queries two sources:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionrecall-reasoningExecute the skills CLI command in your project's root directory to begin installation:
Fetches recall-reasoning from parcadei/continuous-claude-v3 and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate recall-reasoning. Access via /recall-reasoning in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Search through previous sessions to find relevant decisions, approaches that worked, and approaches that failed. Queries two sources:
uv run python scripts/core/artifact_query.py "<query>" [--outcome SUCCEEDED|FAILED] [--limit N]
This searches handoffs with post-mortems (what worked, what failed, key decisions).
bash "$CLAUDE_PROJECT_DIR/.claude/scripts/search-reasoning.sh" "<query>"
This searches .git/claude/commits/*/reasoning.md for build failures and fixes.
# Search for authentication-related work
uv run python scripts/core/artifact_query.py "authentication OAuth JWT"
# Find only successful approaches
uv run python scripts/core/artifact_query.py "implement agent" --outcome SUCCEEDED
# Find what failed (to avoid repeating mistakes)
uv run python scripts/core/artifact_query.py "hook implementation" --outcome FAILED
# Search build/test reasoning
bash "$CLAUDE_PROJECT_DIR/.claude/scripts/search-reasoning.sh" "TypeError"
Artifact Index (handoffs, plans, ledgers):
Reasoning Files (.git/claude/):
From Artifact Index:
✓ = SUCCEEDED outcome (pattern to follow)✗ = FAILED outcome (pattern to avoid)? = UNKNOWN outcome (not yet marked)From Reasoning:
build_fail = approach that didn't workbuild_pass = what finally succeededArtifact Index empty:
uv run python scripts/core/artifact_index.py --all to index existing handoffsReasoning files empty:
/commit after builds to capture reasoning.git/claude/ directory existsMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
parcadei/continuous-claude-v3
mattpocock/skills
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
Registry listing for recall-reasoning matched our evaluation — installs cleanly and behaves as described in the markdown.
recall-reasoning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
recall-reasoning reduced setup friction for our internal harness; good balance of opinion and flexibility.
Useful defaults in recall-reasoning — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for recall-reasoning matched our evaluation — installs cleanly and behaves as described in the markdown.
recall-reasoning is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Keeps context tight: recall-reasoning is the kind of skill you can hand to a new teammate without a long onboarding doc.
recall-reasoning fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Registry listing for recall-reasoning matched our evaluation — installs cleanly and behaves as described in the markdown.
recall-reasoning has been reliable in day-to-day use. Documentation quality is above average for community skills.
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