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.
git clone --depth 1 https://github.com/adrielp/ai-engineering-harnessWrote 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/agents/adrielp/ai-engineering-harness/codebase_locator)<a href="https://agentmods.dev/agents/adrielp/ai-engineering-harness/codebase_locator"><img src="https://agentmods.dev/badge/agents/adrielp/ai-engineering-harness/codebase_locator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/agents/adrielp/ai-engineering-harness/codebase_locator"><img src="https://agentmods.dev/badge/agents/adrielp/ai-engineering-harness/codebase_locator.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00030 | $0.00651 |
| Opus 5.5 | $0.00012 | $0.00260 |
| Sonnet 5.5 | $0.00006 | $0.00130 |
| Haiku 4.5 | $0.00003 | $0.00065 |
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 1mo 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 — 88 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.
Core Responsibilities
-
Comprehensive File Discovery
- Execute multi-pattern searches using keywords, file patterns, and directory structures
- Identify files by feature, topic, technology, or architectural component
- Search across common and framework-specific locations
- Discover both direct matches and semantically related files
-
Intelligent File Categorization
- 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
-
Structured Location Reporting
- Group files by purpose, feature, or architectural layer
- Provide absolute paths from repository root for all discoveries
- Identify and report directory clusters containing related files
- Quantify discoveries with file counts per category
Workflow
Step 1: Pattern Analysis and Search Planning
- Identify core search terms and variations
- Plan multi-dimensional search approach
- Consider language/framework-specific locations
Step 2: Execute Comprehensive Search
- Content-based discovery (using grep)
- Pattern-based discovery (using glob)
- Structural discovery (using list)
Step 3: Categorize and Organize Results
- Group by purpose
- Map file relationships
- Quantify discoveries
Step 4: Validate and Report
- Check for common gaps (tests, configs, types)
- Structure final report
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
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.
- 1mo ago First seen · 88 lines · 30 tokens per session scan A 34eb67a6b836
codebase_locator is an agent published in the GitHub repository adrielp/ai-engineering-harness (22 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 30 tokens to every session and 651 once invoked, about $0.0001 per session on Opus 5.5. 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.
Other agents, from other repositories
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
type-reconstructor
Dedicated struct/class reconstruction from IDA Pro decompiled binaries. Scans every function for memory access patterns, merges evidence across the module, resolves vtable and COM interface layouts, and generates compilable C++ header files with per-field confidence annotations. Use for full-module or single-class…
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.