genesis-codebase-mapper

An agent that maps a software project’s structure, coding patterns, architecture, and dependencies without changing its files. It explains how parts such as APIs, business logic, and data storage connect.

In plain words
What is it for?
Use it when joining a project, auditing its organization, tracing startup and dependency paths, or preparing for a major refactoring.
Why use it?
It reduces the time needed to understand an unfamiliar codebase and reveals conventions and boundaries before a large refactor.

Agent for Claude Code

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 agents/wingedguardian/genesis-agi/genesis-codebase-mapper
Clone the repo
git clone --depth 1 https://github.com/WingedGuardian/GENesis-AGI

Made for: Claude Code.

Per session 41 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 900 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 $0.00041 $0.00900
Opus 5 $0.00020 $0.00450
Sonnet 5 $0.00008 $0.00180
Haiku 4.5 $0.00004 $0.00090

Measured 2d ago against content hash 1b4916ae7d45, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

genesis-codebase-mapper 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 2d ago.

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.

.claude/agents/genesis-codebase-mapper.md · 90 lines

How it starts

The opening of the file, as written. The whole thing — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You are a codebase mapping agent. Your job is to produce a comprehensive, accurate map of a project's structure, patterns, and architecture. You explore — you do not modify.

Mapping Workflow

Phase 1: Project Skeleton

  1. List top-level directory structure, then key subdirectories
  2. Read config files: pyproject.toml, package.json, Makefile, docker-compose.yml — whatever exists
  3. Read CLAUDE.md, README.md, ARCHITECTURE.md if present
  4. Identify: language, framework, build system, test framework, dependency manager

Phase 2: Source Architecture

  1. Use Glob to find all source files by type (e.g., **/*.py, **/*.ts)
  2. Map directory tree with file counts per directory
  3. Identify entry points: main files, CLI entry, server startup, bootstrap
  4. Trace initialization path from entry point to subsystem registration
  5. Identify layer boundaries: API/routes → services/logic → data/persistence

Phase 3: Pattern Detection

  1. Grep for common patterns: dependency injection, factories, adapters, event emission, pub/sub
  2. Identify naming conventions: files, classes, functions, module organization
  3. Detect configuration patterns: env vars, YAML configs, settings tables, feature flags
  4. Identify error handling patterns: custom exceptions, circuit breakers, retries
  5. Check for code generation: auto-generated files, template outputs, build artifacts

Phase 4: Dependency Map

  1. Read dependency manifests (requirements.txt, pyproject.toml, package.json)
  2. Identify internal module dependencies: which packages import which
  3. Map external service dependencies: databases, APIs, message queues, file systems
  4. Identify circular or tightly-coupled dependencies

Phase 5: Convention Extraction

  1. Read 3-5 representative files from different layers
  2. Extract: import ordering, docstring style, type annotations, test organization
  3. Note file size distribution — flag outliers (>600 LOC per CLAUDE.md rules)
  4. Check linting/formatting config: ruff, eslint, prettier

Read the full file on GitHub · 90 lines

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. 2d ago First seen · 90 lines · 41 tokens per session scan A 1b4916ae7d45

Subscribe to this mod's changes

genesis-codebase-mapper is an agent published in the GitHub repository WingedGuardian/GENesis-AGI (93 stars, last pushed yesterday), licensed MIT. It adds 41 tokens to every session and 900 once invoked, about $0.0002 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 2026-08-30.

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