agentmods.dev

gsd:map-codebase

A codebase analysis that uses several mapper agents to document an existing project’s technologies, structure, architecture, conventions, tests, integrations, and concerns.

In plain words
What is it for?
Use it to create seven planning documents describing the stack, architecture, folder structure, coding practices, testing, integrations, and known risks.
Why use it?
It helps developers understand an unfamiliar or older project before making changes.

Skill for Claude CodeCodex

492 20d ago A scan 14 tokens original MIT
View the source file allgpt-co/QuickVoice
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/allgpt-co/quickvoice/map-codebase
Any agent
npx skills add allgpt-co/QuickVoice --skill map-codebase
Clone the repo
git clone --depth 1 https://github.com/allgpt-co/QuickVoice

Made for: Claude Code, Codex.

Per session 14 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 238 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 $0.00014 $0.00238
Opus 5 $0.00007 $0.00119
Sonnet 5 $0.00003 $0.00048
Haiku 4.5 $0.00001 $0.00024

Measured 2d ago against content hash 24b1d5261db9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

gsd:map-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 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/skills/gsd/commands/map-codebase/SKILL.md · 38 lines

What it actually says

GSD Map Codebase

Analyzes existing codebase using parallel mapper agents.

When to Use

  • Understanding an existing codebase structure
  • Starting work on a brownfield project
  • Documenting technology stack and architecture

Process

  1. Check for existing .planning/codebase/ directory
  2. Create directory structure if needed
  3. Spawn 4 parallel mapper agents (tech, arch, quality, concerns)
  4. Wait for all agents to complete
  5. Verify all 7 documents exist
  6. Commit codebase map to git

Output Documents

  • STACK.md, INTEGRATIONS.md (tech focus)
  • ARCHITECTURE.md, STRUCTURE.md (arch focus)
  • CONVENTIONS.md, TESTING.md (quality focus)
  • CONCERNS.md (concerns focus)

Success Criteria

All 7 documents written with content and committed to git.

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 · 38 lines · 14 tokens per session scan A 24b1d5261db9

Subscribe to this mod's changes

gsd:map-codebase is a skill published in the GitHub repository allgpt-co/QuickVoice (492 stars, last pushed 20d ago), licensed MIT. It adds 14 tokens to every session and 238 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 2026-08-30.

Backend and APIsFrontendTestingai-voice-agentscall-automationexpresslivekitnextjsvoice ai
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