recall-reasoning

Search past reasoning for relevant decisions and approaches

422 stars

Best use case

recall-reasoning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Search past reasoning for relevant decisions and approaches

Teams using recall-reasoning should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/recall-reasoning/SKILL.md --create-dirs "https://raw.githubusercontent.com/vibeeval/vibecosystem/main/skills/recall-reasoning/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/recall-reasoning/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How recall-reasoning Compares

Feature / Agentrecall-reasoningStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Search past reasoning for relevant decisions and approaches

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# Recall Past Work

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)

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

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

## Examples

```bash
# 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

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