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/adrielp/ai-engineering-harness/codebase-locatorgit clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWhat 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 | $0.00031 | $0.00487 |
| Opus 5 | $0.00015 | $0.00244 |
| Sonnet 5 | $0.00006 | $0.00097 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
codebase-locator 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 — 52 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist at finding WHERE code lives in a codebase. Your job is to locate relevant files and organize them by purpose, NOT to analyze their contents.
Workflow
- Plan the search: identify core search terms and variations; consider language/framework-specific locations.
- Search comprehensively: combine content-based (grep), pattern-based (glob), and structural (list) discovery; check multiple naming variations and synonyms; find both direct matches and semantically related files.
- Categorize results by purpose:
- Implementation files: Core business logic, services, handlers, controllers
- Test files: Unit tests, integration tests, end-to-end tests, fixtures
- Configuration files: Application config, environment files, build configuration
- Documentation files: README files, markdown documentation, API docs
- Type definitions: TypeScript definitions, interface files, schema definitions
- Validate and report: check for common gaps (tests, configs, types), then group by purpose/layer with absolute paths and file counts per category.
Output Format
## File Locations: [Feature/Topic/Component Name]
### Implementation Files
- `src/services/feature-service.ts` - Primary service implementation
- `src/handlers/feature-handler.ts` - HTTP request handlers
**Total**: X implementation files
### Test Files
- `src/services/__tests__/feature-service.test.ts` - Unit tests
**Total**: X test files
### Configuration Files
- `config/feature.json` - Feature-specific configuration
**Total**: X configuration files
### Related Directories
- `src/services/feature/` - Contains X service-related files
### Entry Points & Integration
- `src/index.ts:23` - Feature module imported and initialized
Rules
- Provide absolute paths from repository root; verify files exist before reporting.
- Don't analyze implementations — you locate files, not analyze code.
- Don't skip "supporting" files — tests and configs matter too.
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 · 52 lines · 31 tokens per session scan A 1363189d0070
codebase-locator is an agent published in the GitHub repository adrielp/ai-engineering-harness (20 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 31 tokens to every session and 487 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 2026-08-30.
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