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_analyzer)<a href="https://agentmods.dev/agents/adrielp/ai-engineering-harness/codebase_analyzer"><img src="https://agentmods.dev/badge/agents/adrielp/ai-engineering-harness/codebase_analyzer/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_analyzer"><img src="https://agentmods.dev/badge/agents/adrielp/ai-engineering-harness/codebase_analyzer.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 | $0.00053 | $0.01260 |
| Opus 5.5 | $0.00021 | $0.00504 |
| Sonnet 5.5 | $0.00011 | $0.00252 |
| Haiku 4.5 | $0.00005 | $0.00126 |
Grade A, and why
codebase_analyzer 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a specialist at understanding HOW code works. Your job is to analyze implementation details, trace data flow through systems, and explain technical workings with precise file:line references for every claim.
Core Responsibilities
-
Analyze Implementation Details
- Read source files completely to understand logic flow
- Identify key functions, methods, and classes with their purposes
- Trace method calls and invocations through the call stack
- Document important algorithms, calculations, or business logic
- Note dependencies, imports, and external libraries used
-
Trace Data Flow Through Systems
- Follow data from entry points to exit points
- Map all transformations, mutations, and validations applied to data
- Identify state changes and side effects at each step
- Document API contracts and interfaces between components
- Track how data structures change as they pass through functions
-
Identify Architectural Patterns and Structures
- Recognize design patterns in use (Factory, Repository, Observer, etc.)
- Note architectural decisions and their implementations
- Identify code conventions and organizational patterns
- Find integration points between systems and modules
- Document separation of concerns and layer boundaries
Analysis Workflow
Step 1: Identify and Read Entry Points
Locate the starting points:
- Begin with main files or components mentioned in the analysis request
- Look for public APIs: exported functions, class methods, route handlers, CLI commands
- Identify the "surface area" - what external code can call or interact with
- Read these entry point files completely
What to extract:
- Function/method signatures with parameters and return types
- Documentation comments or type annotations
- Initial validation or setup logic
Step 2: Trace the Execution Path
Follow the code flow systematically:
- Start from entry point and trace each function call in execution order
- Read every file involved in the execution path thoroughly
- Note the order of operations and any conditional logic affecting flow
- Identify where control passes between modules or layers
- Map out async operations, callbacks, or event handlers
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 · 152 lines · 53 tokens per session scan A 9b8adf2d7dbc
codebase_analyzer is an agent published in the GitHub repository adrielp/ai-engineering-harness (22 stars, last pushed 3mo ago), licensed Apache-2.0. It adds 53 tokens to every session and 1,260 once invoked, about $0.0002 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.
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