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Codebase Orientation

Community
adamentwistle
codebase-orientation

Fast recon before changing unfamiliar code — instructions, manifest, tree, one flow traced end-to-end, git history, newest precedent. Use when starting in a repo or module you haven't touched this session, when asked "where does X live" or "how is Y wired", or before designing against an existing architecture. Not for a one-line edit to a file already open in the conversation.

Overview

Publisheradamentwistle
Repositoryfable-skills
Skill namecodebase-orientation
Stars
98
Forks
11
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by adamentwistle on GitHub. Read the source before you install it.

Installation

Install the Codebase Orientation AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/adamentwistle/fable-skills/tree/main/codebase-orientation
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/adamentwistle/fable-skills.git /tmp/fable-skills
mkdir -p .claude/skills
cp -r /tmp/fable-skills/codebase-orientation .claude/skills/codebase-orientation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codebase Orientation in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Codebase Orientation on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Codebase Orientation is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Codebase Orientation

Weak orientation reads the one file named in the request and starts editing; the result fights the repo's architecture and gets rewritten in review. Strong orientation spends 5–10 minutes on breadth-first reads, then edits where the existing analog lives, in the repo's idiom.

The recon sequence

  1. Instructions first. CLAUDE.md / AGENTS.md / CONTRIBUTING / README, in that order. They override your defaults and usually name the gotchas you would otherwise rediscover.

  2. The manifest. package.json scripts, Makefile, justfile, pyproject, Cargo.toml: how to build, test, lint, run, and what the intended stack is. Use the project's declared commands, never your generic equivalents. Run the declared test (or build) command once now, before any edit: a red baseline is a finding to report, not a bug you introduced.

  3. Shape of the tree. One ls-depth pass over the source root. Learn the layering (types, business logic, UI, IO) and spot generated or vendored directories you must not hand-edit. New code goes where the existing analog lives.

  4. The relevant flow, end to end. Trace one representative request or action from entry point to effect (route → handler → service → store; CLI arg → command → output). Read the actual files on that path: this is the single highest-value read. Note error-handling style, naming, import conventions, and where the nearest test for that path lives.

  5. Recent history. git log --oneline -20, plus git log --oneline -5 -- <file> for each file you will edit. Look for in-flight migrations: a commit titled "migrate X to Y" means new code uses Y, even if most of the repo still uses X.

  6. Find the precedent. For "add a Z" tasks, find the most recently added Z and read all of its wiring (git log --diff-filter=A --oneline -- <dir> finds it). Imitate it exactly; deviate only deliberately and say why.

Write the map before the first edit

Before editing, put 3–6 lines in your notes or first status message: test/build command; the files on the traced path; the precedent you are imitating; any in-flight migration or instruction that constrains the change; the baseline test result. If you cannot fill a line, you have not oriented on it yet.

Judging which pattern to copy

When two patterns compete for the same job, prefer: (1) the one in newer code, (2) the one the instructions endorse, (3) the one nearest your change. If it is genuinely ambiguous and load-bearing, ask one question citing both patterns.

Cheap map, not deep study

Breadth-first and time-boxed. Read signatures and shapes, not every body; depth comes later on the specific path you change. If the repo is huge, delegate the sweep to search subagents and keep only the conclusions.

Signs you skipped this step (go back)

  • You are about to add a dependency the repo already has an equivalent for.
  • Your new file's imports look different from every neighbor's.
  • You invented a directory.
  • You wrote a helper that grep would have found already exists.
  • You edited a file that a build step regenerates.

Frequently asked questions

What does the Codebase Orientation AI skill do?

Fast recon before changing unfamiliar code — instructions, manifest, tree, one flow traced end-to-end, git history, newest precedent. Use when starting in a repo or module you haven't touched this session, when asked "where does X live" or "how is Y wired", or before designing against an existing architecture. Not for a one-line edit to a file already open in the conversation.

Why use Codebase Orientation on TypingMind?

Because you install it once and use it with any model. Codebase Orientation is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Codebase Orientation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/adamentwistle/fable-skills/tree/main/codebase-orientation. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Codebase Orientation?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Codebase Orientation?

As many as you like. As long as a model supports skills, you can use Codebase Orientation with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Codebase Orientation AI skill free?

Yes. It is published on GitHub by adamentwistle under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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