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dtbuchholz
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recall-commit

Enforce conventional commit formats and capture insights into AGENT-LEARNINGS.md.

Updated Jan 22, 2026
Search Tags:#git#knowledge management#commit#conventional commits#learning capture#recall labs
One-click install
npx skills add https://github.com/dtbuchholz/claude-config --skill recall-commit
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: recall-commit
Source: https://github.com/dtbuchholz/claude-config/tree/main/skills/recall-commit
Command: npx skills add https://github.com/dtbuchholz/claude-config --skill recall-commit

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill streamlines the commit process by enforcing conventional commit standards and integrating a crucial learning capture mechanism for Recall Labs projects.

Core Features & Use Cases

  • Conventional Commits: Enforces a structured commit message format (type(scope): subject, body with summary, changes, why, and testing).
  • Learning Capture: Prompts for and captures high-leverage insights from the development session into AGENT-LEARNINGS.md.
  • Guardrails: Verifies project context (Recall Labs) before proceeding and prevents committing secrets.
  • Use Case: After completing a feature, use this skill to create a well-documented commit that not only records the code changes but also captures any non-obvious constraints or design rationales that would benefit future AI agent sessions.

Quick Start

Use the recall-commit skill to commit your staged changes with integrated learning capture.

Frequently Asked Questions about recall-commit

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I enforce conventional commit standards when using git?▼

To enforce conventional commit standards with git, you apply a structured commit message format using `type(scope): subject` alongside a body containing summary, changes, why, and testing details.

What is conventional commit format and how does it capture development learnings?▼

Conventional commit format structures git history using `type(scope): subject` while capturing non-obvious design rationales into `AGENT-LEARNINGS.md`, ensuring consistent code history and knowledge sharing for future AI agent sessions.

Do I need git CLI to commit staged changes and capture high-leverage insights?▼

Yes, you need the git CLI to commit staged changes and capture high-leverage insights, as version control operations rely entirely on the git command line interface to execute the commit actions.

Does this commit workflow prevent committing secrets and verify project context?▼

Yes, this commit workflow includes guardrails that verify designated Recall Labs project context before proceeding and actively prevents committing secrets to ensure secure repository history.

What's the best way to document code changes and design rationale for future AI agent sessions?▼

The best way to document code changes for future AI agent sessions is committing with inline learning capture, which records design rationale and non-obvious constraints into `AGENT-LEARNINGS.md` files.

Can I use this conventional commit mechanism outside of designated repositories?▼

No, the conventional commit mechanism verifies designated Recall Labs project context before proceeding, meaning it only applies to commit actions within specifically designated repositories.

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