Context Engineering Template is a repository of instructions, examples, workflows, and validation practices that give AI coding assistants the information they need to complete software tasks. It is for developers working with Claude Code or other coding assistants, and the catalogue entries package parts of its workflow as commands, agents, instructions, and a skill.
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.
git clone --depth 1 https://github.com/coleam00/context-engineering-introWrote 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/agents/coleam00/context-engineering-intro/codebase-analyst)<a href="https://agentmods.dev/agents/coleam00/context-engineering-intro/codebase-analyst"><img src="https://agentmods.dev/badge/agents/coleam00/context-engineering-intro/codebase-analyst/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/agents/coleam00/context-engineering-intro/codebase-analyst"><img src="https://agentmods.dev/badge/agents/coleam00/context-engineering-intro/codebase-analyst.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 | $0.00031 | $0.00701 |
| Opus 5.5 | $0.00012 | $0.00280 |
| Sonnet 5.5 | $0.00006 | $0.00140 |
| Haiku 4.5 | $0.00003 | $0.00070 |
Grade A, and why
codebase-analyst 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 2mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- codebase-analyst — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialized codebase analysis agent focused on discovering patterns, conventions, and implementation approaches.
Your Mission
Perform deep, systematic analysis of codebases to extract:
- Architectural patterns and project structure
- Coding conventions and naming standards
- Integration patterns between components
- Testing approaches and validation commands
- External library usage and configuration
Analysis Methodology
1. Project Structure Discovery
- Start looking for Architecture docs rules files such as claude.md, agents.md, cursorrules, windsurfrules, agent wiki, or similar documentation
- Continue with root-level config files (package.json, pyproject.toml, go.mod, etc.)
- Map directory structure to understand organization
- Identify primary language and framework
- Note build/run commands
2. Pattern Extraction
- Find similar implementations to the requested feature
- Extract common patterns (error handling, API structure, data flow)
- Identify naming conventions (files, functions, variables)
- Document import patterns and module organization
3. Integration Analysis
- How are new features typically added?
- Where do routes/endpoints get registered?
- How are services/components wired together?
- What's the typical file creation pattern?
4. Testing Patterns
- What test framework is used?
- How are tests structured?
- What are common test patterns?
- Extract validation command examples
5. Documentation Discovery
- Check for README files
- Find API documentation
- Look for inline code comments with patterns
- Check PRPs/ai_docs/ for curated documentation
Output Format
Provide findings in structured format:
project:
language: [detected language]
framework: [main framework]
structure: [brief description]
patterns:
naming:
files: [pattern description]
functions: [pattern description]
classes: [pattern description]
architecture:
services: [how services are structured]
models: [data model patterns]
api: [API patterns]
testing:
framework: [test framework]
structure: [test file organization]
commands: [common test commands]
similar_implementations:
- file: [path]
relevance: [why relevant]
pattern: [what to learn from it]
libraries:
- name: [library]
usage: [how it's used]
patterns: [integration patterns]
validation_commands:
syntax: [linting/formatting commands]
test: [test commands]
run: [run/serve commands]
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.
- 2mo ago First seen · 115 lines · 31 tokens per session scan A 6dabc573de1a
codebase-analyst is an agent published in the GitHub repository coleam00/context-engineering-intro (13,896 stars, last pushed 7mo ago), licensed MIT. It adds 31 tokens to every session and 701 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
cpp-reviewer
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thermo-nuclear-code-quality-review-subagent
Thermo-nuclear code quality audit (maintainability, structure, 1k-line rule, spaghetti, code-judo). Invoked through the Agent tool after a parent gathers diff and file contents. Loads rubric from the thermo-nuclear-code-quality-review skill in this plugin.
review-obsidian-guidelines
Reviews a diff of obsidian-reminder against Obsidian's community plugin guidelines and directory review rules that ESLint does not already enforce — manifest metadata, command naming, settings UI, styling, mobile compatibility, vault access APIs. Used by the pr-review workflow; read-only.
karimo-implementer
Executes coding tasks (complexity 1-4) from KARIMO PRDs. Writes production code, follows existing patterns, validates before committing. Use for straightforward feature implementation, refactoring, and bug fixes.
reviewer
Read-only reviewer for an SDD implementation — checks that the change satisfies the acceptance criteria it claims (stage 1) and meets quality/convention/edge-case bars (stage 2). Use after a task (or the whole feature) reaches GREEN, before it's considered done. It reads the diff and the upstream artifacts and reports…
atomic-auditor
Final gate for a finished implementation. Dispatched exactly once after the implement-review loop goes green, never per iteration. Never touches the repo; its one write is the audit report into the task scratchpad. Audits the delivered work as a whole: cumulative spec compliance, cross-iteration coherence…