Recall Past Work

SkillSearch

Lets your agent search its past reasoning to find earlier decisions and approaches.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the Recall Past Work skill

About this capability

Search past reasoning for relevant decisions and approaches

What this skill tells your AI

The instructions your AI receives, as published by parcadei/continuous-claude-v3 in .claude/skills/recall-reasoning/SKILL.md and read by ahel’s review.

Search through previous sessions to find relevant decisions, approaches that worked, and approaches that failed. Queries two sources:

  1. Artifact Index - Handoffs, plans, ledgers with post-mortems (what worked/failed)
  2. Reasoning Files - Build attempts, test failures, commit context

When to Use

  • Starting work similar to past sessions
  • "What did we do last time with X?"
  • Looking for patterns that worked before
  • Investigating why something was done a certain way
  • Debugging an issue encountered previously

Usage

Primary: Artifact Index (rich context)

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).

Secondary: Reasoning Files (build attempts)

bash "$CLAUDE_PROJECT_DIR/.claude/scripts/search-reasoning.sh" "<query>"

This searches .git/claude/commits/*/reasoning.md for build failures and fixes.

Examples

# 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"

What Gets Searched

Artifact Index (handoffs, plans, ledgers):

  • Task summaries and status
  • What worked - Successful approaches
  • What failed - Dead ends and why
  • Key decisions - Choices with rationale
  • Goal and constraints from ledgers

Reasoning Files (.git/claude/):

  • Failed build attempts and error output
  • Successful builds after failures
  • Commit context and branch info

Interpreting Results

From Artifact Index:

  • = SUCCEEDED outcome (pattern to follow)
  • = FAILED outcome (pattern to avoid)
  • ? = UNKNOWN outcome (not yet marked)
  • Post-mortem sections show distilled learnings

From Reasoning:

  • build_fail = approach that didn't work
  • build_pass = what finally succeeded
  • Multiple failures before success = non-trivial problem

Process

  1. Run Artifact Index query first - richer context, post-mortems
  2. Review relevant handoffs - check what worked/failed sections
  3. If needed, search reasoning - for specific build errors
  4. Apply learnings - follow successful patterns, avoid failed ones

No Results?

Artifact Index empty:

  • Run uv run python scripts/core/artifact_index.py --all to index existing handoffs
  • Create handoffs with post-mortem sections for future recall

Reasoning files empty:

  • Use /commit after builds to capture reasoning
  • Check if .git/claude/ directory exists

Signals

GitHub stars
4k
Forks
300
Last commit
Jan 2026
Advanced
Catalog kind
skill
Gateway key
recall-reasoning
Source
github.com/parcadei/continuous-claude-v3