Search past reasoning for relevant decisions and approaches
npx skills add https://github.com/parcadei/Continuous-Claude-v3 --skill recall-reasoning
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 existsGuide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.
Intelligently organizes your files and folders across your computer by understanding context, finding duplicates, suggesting better structures, and automating cleanup tasks. Reduces cognitive load and keeps your digital workspace tidy without manual effort.
Generates 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.
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Creative research ideation and exploration. Use for open-ended brainstorming sessions, exploring interdisciplinary connections, challenging assumptions, or identifying research gaps. Best for early-stage research planning when you do not have specific observations yet. For formulating testable hypotheses from data use hypothesis-generation.
Comprehensive GitHub project management with swarm-coordinated issue tracking, project board automation, and sprint planning
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
Take parcadei/recall-reasoning from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.