codebase-research

SkillFiles & storage

Guides your agent to explore and understand a codebase step by step before making changes.

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 codebase-research skill

About this capability

Systematic codebase exploration following the Iron Law - understand the problem before exploring code. Four phases with file-finder and web-researcher agents.

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/methodologies/rpikit/skills/codebase-research/SKILL.md and read by ahel’s review.

  • Investigating how an existing feature works before modifying it
  • Understanding dependencies and data flows before planning
  • Gathering context for a known goal

Process

  1. Understand the request - Ask clarifying questions one at a time (purpose, specifics, scope, constraints, context). Do NOT read any files until confirmed.
  2. Explore the codebase - Use file-finder agent, read in order, trace data flows, identify constraints.
  3. Document findings - Write structured research document to docs/plans/YYYY-MM-DD-<topic>-research.md.
  4. Transition - Ask: plan, continue research, or conclude.

Key Rules

  • Quotations from source material capped at 125 characters maximum
  • Only proceed to exploration after human confirms understanding
  • Use file-finder agent for initial file discovery
  • Use web-researcher agent for external context needs

Agents Used

  • agents/file-finder/ - Locates relevant files with suggested reading order
  • agents/web-researcher/ - Gathers external context when needed

Tool Use

Invoke via babysitter process: methodologies/rpikit/rpikit-research

Signals

GitHub stars
2k
Forks
106
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
codebase-research
Source
github.com/a5c-ai/babysitter