researching-codebase

A codebase research step that maps how an unfamiliar project is organised and how its parts work before implementation planning.

In plain words
What is it for?
Use it before a substantial coding task, when exploring unfamiliar areas, or before making architecture decisions. It records examined files, paths, line numbers, and code references.
Why use it?
It prevents planning based on incomplete searches or guesses. The findings stay separate from the main conversation and return only a concise, evidence-based summary.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/qte77/claude-code-plugins/researching-codebase
Any agent
npx skills add qte77/claude-code-plugins --skill researching-codebase
Clone the repo
git clone --depth 1 https://github.com/qte77/claude-code-plugins

Made for: Claude Code, Codex.

Per session 26 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 584 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00026 $0.00584
Opus 5 $0.00013 $0.00292
Sonnet 5 $0.00005 $0.00117
Haiku 4.5 $0.00003 $0.00058

Measured yesterday against content hash f56f168ecd1c, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

researching-codebase scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/codebase-tools/skills/researching-codebase/SKILL.md · 84 lines

What it actually says

Codebase Research (ACE-FCA)

Query: $ARGUMENTS

Gathers codebase context in isolation before planning. Prevents search artifacts from polluting main context.

Core Principles

  1. Documentation-only - Describe what exists, where, and how it works
  2. No evaluations - Never suggest improvements or critique implementation
  3. Evidence-based - Provide file paths, line numbers, and code references
  4. Isolation - Research runs in fork context; return only distilled findings

When to Use

  • Before planning non-trivial implementations
  • When unfamiliar with relevant codebase areas
  • Before architectural decisions

Workflow

  1. Read mentioned files first - If specific files mentioned, read completely before exploring
  2. Decompose the question - Break query into researchable components
  3. Explore codebase - Investigate architecture, patterns, constraints
  4. Identify scope - Determine relevant areas based on findings
  5. Distill - Return structured summary using output format below

Output Format

Follow ACE-FCA quality equation: Correct + Complete + Minimal noise

---
research_query: "<original question>"
timestamp: "<ISO 8601>"
files_examined: <count>
---

## Key Files

| File | Purpose | Key Lines |
|------|---------|-----------|
| `path/to/file.ext` | Brief purpose | L42-58 |

## Patterns

- **Pattern name**: Description with file reference (`path:line`)

## Constraints

- Constraint with evidence (`path:line`)

Evidence Requirements

Every claim must include:

  • File path: Exact location (src/auth/login.ts)
  • Line numbers: Specific lines (L42-58 or L127)
  • Code reference: Function/class name when relevant

Bad: "Authentication uses JWT tokens" Good: "Authentication uses JWT tokens (src/auth/jwt.ts:L23-45, verifyToken function)"

References

See references/context-management.md and references/core-principles.md.

Files

What ships with it

2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 84 lines · 26 tokens per session scan A f56f168ecd1c

Subscribe to this mod's changes

researching-codebase is a skill published in the GitHub repository qte77/claude-code-plugins (2 stars, last pushed 2d ago), licensed Apache-2.0. It adds 26 tokens to every session and 584 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

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