codebase-pattern-finder

A codebase research assistant that finds similar implementations, examples, and tests in an existing project, then explains the patterns and conventions they use.

In plain words
What is it for?
Use it to locate comparable features, component or class structures, integrations, test examples, preferred approaches, and file-and-line references.
Why use it?
It reduces the time spent searching through unfamiliar code and helps new work match approaches already used in the project.

Agent

Install

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.

agentmods
npx agentmods add agents/iamironz/ai-config-bundle/codebase-pattern-finder
Clone the repo
git clone --depth 1 https://github.com/iamironz/ai-config-bundle
Per session 70 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,520 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 81% copy Near-identical to another mod in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured yesterday against content hash a90ef5532a44, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

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.

Origin

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.

.opencode/agents/codebase-pattern-finder.md · 223 lines

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

  1. Find Similar Implementations

    • Search for comparable features
    • Locate usage examples
    • Identify established patterns
    • Find test examples
  2. Extract Reusable Patterns

    • Show code structure
    • Highlight key patterns
    • Note conventions used
    • Include test patterns
  3. 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, and LS tools 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' }
  });

Read the full file on GitHub · 223 lines

Changes

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.

  1. yesterday First seen · 223 lines · 70 tokens per session scan A a90ef5532a44

Subscribe to this mod's changes

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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