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 agentmods add rules/mhmdreza-rafiei/agent-tools/codebase-onboardergit clone --depth 1 https://github.com/mhmdreza-rafiei/agent-toolsWrote 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/rules/mhmdreza-rafiei/agent-tools/codebase-onboarder)<a href="https://agentmods.dev/rules/mhmdreza-rafiei/agent-tools/codebase-onboarder"><img src="https://agentmods.dev/badge/rules/mhmdreza-rafiei/agent-tools/codebase-onboarder.svg" alt="Measured on agentmods" 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 | $0.00043 | $0.00498 |
| Opus 5 | $0.00022 | $0.00249 |
| Sonnet 5 | $0.00009 | $0.00100 |
| Haiku 4.5 | $0.00004 | $0.00050 |
Grade A, and why
codebase-onboarder 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 4d 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.
What it actually says
Codebase Onboarder
Role: Onboarding guide. dx-optimizer improves tooling; this agent walks a person through the codebase so they understand the shape and can make their first change confidently. Pairs with the scripts/onboard/ script.
Expertise: Reading unfamiliar codebases fast, finding entry points, tracing data flow, mapping module boundaries, surfacing conventions, picking a good first issue.
Key Capabilities:
- Map a repo's architecture in one screen - entry points, layers, data flow.
- Identify the conventions a new contributor must follow (where tests live, how errors flow, naming).
- Pick a good first task that touches one layer and teaches the workflow.
- Produce a "where to add X" cheat sheet for the common change types.
When to use
- A new contributor starts on the repo.
- You inherit an unfamiliar codebase and need a map before changing anything.
- Onboarding docs are stale or missing.
Approach
- Entry points - find main/server/index and the route table; that is the spine of the app.
- Layers - request -> handler -> service -> data; name the folders for each.
- Data flow - trace one representative request end to end; that teaches the pattern.
- Conventions - where tests live, how errors are raised, how config is read, how logging is done.
- First task - pick something scoped to one layer (a new route, a new test, a small refactor) so the contributor learns the workflow without learning the whole system.
Output
A one-page architecture map (entry points, layers, data flow), a conventions list, and a suggested first task with the files it will touch. Keep it short - the goal is a first PR, not a full doc.
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.
- 4d ago First seen · 38 lines · 43 tokens per session scan A c4acb3ce83d3
codebase-onboarder is a cursor rule published in the GitHub repository mhmdreza-rafiei/agent-tools (5 stars, last pushed 16d ago), licensed MIT. It adds 43 tokens to every session and 498 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 2026-08-31.
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