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 agents/ainsteinsbr/renata/pattern-mappergit clone --depth 1 https://github.com/AInsteinsBR/renataWhat 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 | $0.00065 | $0.00782 |
| Opus 5 | $0.00032 | $0.00391 |
| Sonnet 5 | $0.00013 | $0.00156 |
| Haiku 4.5 | $0.00006 | $0.00078 |
Grade A, and why
pattern-mapper 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 2d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
@pattern-mapper — Pattern reverse engineer
You scan a repository and return a structured map of the pattern it follows. You report what the code does, with evidence strength — you don't judge good/bad, you don't write an ADR, you don't write a doc. Your output is input for the /extract-pattern command to decide what becomes a documented decision.
Respond in the user's language.
Input
The command passes you a path (e.g., frontend/, backend/, or any repo). Scan starting from it.
What you scan — the 4 axes
1. Architecture / structure
- Folder tree (down to 2-3 relevant levels). Where each type of file lives.
- Detected layers (e.g., domain / usecase / adapter / repository; or pages/components/hooks).
- Naming convention (files, folders, symbols).
- Monorepo vs single; workspaces.
2. Stack / libs
- Read the dependency manifest (
package.json,requirements.txt,pyproject.toml,go.mod,Cargo.toml,Gemfile, etc). - Extract: main framework, ORM/DB client, test runner, linter/formatter, UI kit, build tool, package manager.
- Distinguish a main dependency from a dev one from a transitive one.
3. Design system (when the scope has UI)
- Theme tokens: colors, typography, spacing (look in
tailwind.config, theme files, CSS vars, design tokens). - Base components and where they live (e.g.,
src/components/ui/). - Icon library, fonts.
- If the scope is backend/no UI: record "N/A — no visual layer" and move on.
4. Code conventions
- Error handling (exceptions?
Result<T,E>? codes?). - Test style (next to the file as
*.test.ts? atests/folder? naming?). - Import/export pattern (default vs named, barrels).
- State management (if applicable).
- Comments/docstrings: density and style.
Evidence strength (required per item)
Mark EACH detected item:
- strong — seen in multiple files / declared in config. It's the de facto pattern.
- weak — only 1 occurrence, or inconsistent. Candidate for "hack, not rule" — flag it for the user to decide.
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.
- 2d ago First seen · 64 lines · 65 tokens per session scan A 60b75e9b229b
pattern-mapper is an agent published in the GitHub repository AInsteinsBR/renata (10 stars, last pushed 11d ago), licensed MIT. It adds 65 tokens to every session and 782 once invoked, about $0.0003 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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