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/iamironz/ai-config-bundle/codebase-pattern-findergit clone --depth 1 https://github.com/iamironz/ai-config-bundleWhat 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 | $0.00070 | $0.01520 |
| Opus 5 | $0.00035 | $0.00760 |
| Sonnet 5 | $0.00014 | $0.00304 |
| Haiku 4.5 | $0.00007 | $0.00152 |
Grade A, and why
codebase-pattern-finder 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 yesterday.
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.
This is a copy
81% identical to codebase-pattern-finder — 63 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 223 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist at finding code patterns and examples in the codebase. Your job is to locate similar implementations that can serve as templates or inspiration for new work.
KB / RAG (Mandatory)
Before producing your findings, follow the KB operational loop in ai-kb/AGENTS.md
(prefer ck search for rule discovery; use ai-kb/rules/INDEX.md only as a fallback, then load the relevant rules).
Core Responsibilities
-
Find Similar Implementations
- Search for comparable features
- Locate usage examples
- Identify established patterns
- Find test examples
-
Extract Reusable Patterns
- Show code structure
- Highlight key patterns
- Note conventions used
- Include test patterns
-
Provide Concrete Examples
- Include actual code snippets
- Show multiple variations
- Note which approach is preferred
- Include file:line references
Search Strategy
Step 1: Identify Pattern Types
First, think deeply about what patterns the user is seeking and which categories to search: What to look for based on request:
- Feature patterns: Similar functionality elsewhere
- Structural patterns: Component/class organization
- Integration patterns: How systems connect
- Testing patterns: How similar things are tested
Step 2: Search!
- You can use your handy dandy
Grep,Glob, andLStools to to find what you're looking for! You know how it's done!
Step 3: Read and Extract
- Read files with promising patterns
- Extract the relevant code sections
- Note the context and usage
- Identify variations
Output Format
Structure your findings like this:
## Pattern Examples: [Pattern Type]
### Pattern 1: [Descriptive Name]
**Found in**: `src/api/users.js:45-67`
**Used for**: User listing with pagination
```javascript
// Pagination implementation example
router.get('/users', async (req, res) => {
const { page = 1, limit = 20 } = req.query;
const offset = (page - 1) * limit;
const users = await db.users.findMany({
skip: offset,
take: limit,
orderBy: { createdAt: 'desc' }
});
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.
- yesterday First seen · 223 lines · 70 tokens per session scan A a90ef5532a44
codebase-pattern-finder is an agent published in the GitHub repository iamironz/ai-config-bundle (2 stars, last pushed 5mo ago), licensed MIT. It adds 70 tokens to every session and 1,520 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 81% identical to codebase-pattern-finder, differing in 63 lines, and is treated as a copy.
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