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.
npx skills add boparaiamrit/skills-by-amrit --skill codebase-mappinggit clone --depth 1 https://github.com/boparaiamrit/skills-by-amritWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/boparaiamrit/skills-by-amrit/codebase-mapping)<a href="https://agentmods.dev/skills/boparaiamrit/skills-by-amrit/codebase-mapping"><img src="https://agentmods.dev/badge/skills/boparaiamrit/skills-by-amrit/codebase-mapping/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/boparaiamrit/skills-by-amrit/codebase-mapping"><img src="https://agentmods.dev/badge/skills/boparaiamrit/skills-by-amrit/codebase-mapping.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00040 | $0.01920 |
| Opus 5 | $0.00020 | $0.00960 |
| Sonnet 5 | $0.00008 | $0.00384 |
| Haiku 4.5 | $0.00004 | $0.00192 |
Grade A, and why
codebase-mapping 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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 254 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Mapping
Overview
Before you can improve a system, you must understand it. Codebase mapping creates a comprehensive mental model.
Core principle: Observation before action. Understanding before modification.
The Iron Law
NO CHANGES TO A CODEBASE YOU HAVEN'T MAPPED. NO ASSUMPTIONS ABOUT STRUCTURE.
When to Use
- First time encountering a project
- Before any audit skill
- Before major refactoring
- When onboarding to a team
- When the codebase feels "confusing"
When NOT to Use
- You've already mapped this codebase and it hasn't changed significantly
- Simple bug fix in a file you already understand (use
systematic-debugging) - Adding to an area you've recently worked in (context is fresh)
Anti-Shortcut Rules
YOU CANNOT:
- Start modifying code before completing the mapping — understand first, change second
- Assume structure from directory names — read the actual files
- Skip the dependency analysis — hidden dependencies create hidden bugs
- Map only the parts you think are relevant — map the whole system, surprises hide in corners
- Trust the README as ground truth — READMEs age, code doesn't lie
- Skip the data model phase — the data model IS the architecture for most systems
- Stop at the directory tree — trace actual data flows through the code
- Declare mapping complete without tracing at least 2 critical flows end-to-end
Common Rationalizations (Don't Accept These)
| Rationalization | Reality |
|---|---|
| "I just need to fix this one file" | One file connects to other files. Map first. |
| "The README explains everything" | READMEs explain intent. Code reveals reality. |
| "It's a small project, I can figure it out" | Small projects still have hidden complexity. |
| "I've worked with this framework before" | Framework knowledge ≠ project knowledge. |
| "I'll learn as I go" | Learning by breaking things is not mapping. |
| "The tests explain the behavior" | Tests explain expected behavior. Code reveals actual behavior. |
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.
- 8d ago First seen · 254 lines · 40 tokens per session scan A 4b4e50920f74
codebase-mapping is a skill published in the GitHub repository boparaiamrit/skills-by-amrit (5 stars, last pushed 5mo ago), licensed MIT. It adds 40 tokens to every session and 1,920 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 2026-09-03.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…