Orient
Build comprehensive understanding of a codebase. Maps tech stack, architecture, entry points, and patterns. Use when starting work on an unfamiliar codebase or onboarding to a new project.From its SKILL.md
npx -y skills add mike-diff/ai-coding-configs --skill orientAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
2.6 KB, 586 tokens by cl100k_base, as published. Nobody here has run it
/orient — Codebase Proficiency
Build comprehensive understanding of the codebase before starting work.
Workflow
<workflow> Phase 1 - Project Identity: - Read AGENTS.md and README.md for project context - Identify tech stack from manifest files (package.json, pyproject.toml, etc.) - Understand the project's purpose and architecturePhase 2 - Structure Mapping:
- Explore directory structure
- Identify key modules and their responsibilities
- Map entry points and main code paths
Phase 3 - Pattern Recognition:
- Note coding conventions and patterns used
- Identify abstractions and how they're applied
- Understand testing approach and file organisation
Phase 4 - Synthesise:
- Build mental model of how components connect
- Identify the most important files to understand
- Present orientation summary </workflow>
Process
Step 1: Read Project Documentation
cat AGENTS.md README.md 2>/dev/null
cat package.json pyproject.toml Cargo.toml go.mod 2>/dev/null | head -50
Step 2: Explore Structure
ls -la
ls -R src/ app/ lib/ 2>/dev/null | head -100
find . -maxdepth 3 -name "*.md" -o -name "main.*" -o -name "index.*" 2>/dev/null | head -20
Step 3: Understand Patterns
Read 2-3 representative files to understand code style, module structure, import patterns, and error handling.
Step 4: Deep Dive Key Areas
Use codebase search to understand the main entry point, core abstractions, and how components communicate.
Output
<output_format>
## Codebase: [project-name]
### Tech Stack
- Language: [primary language and version]
- Framework: [main framework]
- Build: [build tool and key scripts]
- Test: [test framework]
### Architecture
[2-3 sentences describing the overall architecture]
### Key Components
- `[path]` - [responsibility]
- `[path]` - [responsibility]
### Patterns & Conventions
- [Notable pattern 1]
- [Notable pattern 2]
### Entry Points
- Main: `[file]`
- Tests: `[command]`
- Dev: `[command]`
### Understanding Checklist
- [ ] Core data flow understood
- [ ] Main abstractions identified
- [ ] Test patterns recognised
- [ ] Build process clear
</output_format>
Constraints
<constraints> FOCUS: - Understanding over speed - Accuracy over completeness - Key paths over exhaustive coverageAVOID:
- Superficial scanning without comprehension
- Suggesting changes or improvements
- Making assumptions without verification </constraints>
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most architecture codebase skills give in 586 tokens
Counted across 811 of the 1,134 authors here whose files we hold, read 2026-08-07
- Ask the user which candidate to explorein 45 of 811, across 15 files
- Apply the deletion test to suspected shallow modulesin 43 of 811, across 15 files
- Read any relevant architecture decision records firstin 31 of 811, across 8 files
- Use exact glossary terms in every suggestionin 30 of 811, across 10 files
- Accept dependencies instead of creating themin 24 of 811, across 5 files
- Include before and after visualisations for each candidatein 24 of 811, across 5 files
- Read the domain glossary before exploringin 24 of 811, across 6 files
- Return results instead of producing side effectsin 23 of 811, across 4 files
- Explore the codebase for shallow modules and frictionin 23 of 811, across 3 files
- Introduce seams only where things varyin 22 of 811, across 3 files
- Reduce the number of methodsin 21 of 811, across 2 files
- Design deep modules with small interfacesin 21 of 811, across 3 files
Said here and by no other author read
- identify the tech stack from manifest files
- explore the directory structure
- map entry points and main code paths
- note coding conventions and patterns
- read representative files to understand code style
- understand the main entry point and core abstractions
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.