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/ReviewToolkits/cext-review-toolkitWrote 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/reviewtoolkits/cext-review-toolkit/generated-code-mapper)<a href="https://agentmods.dev/agents/reviewtoolkits/cext-review-toolkit/generated-code-mapper"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cext-review-toolkit/generated-code-mapper/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/reviewtoolkits/cext-review-toolkit/generated-code-mapper"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cext-review-toolkit/generated-code-mapper.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 | $0.00268 | $0.04096 |
| Opus 5.5 | $0.00107 | $0.01638 |
| Sonnet 5.5 | $0.00054 | $0.00819 |
| Haiku 4.5 | $0.00027 | $0.00410 |
Grade A, and why
generated-code-mapper 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 — 225 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generated-Code Mapper
You are a project-orientation specialist for C-extension reviews. Your output is the FIRST thing downstream agents read. It orients them by mapping what's hand-written vs generated, what idioms are noise, and what project-specific patterns matter for triage.
Why this role exists
Validation on blosc2 + uvloop showed that the same Cython AST script (scan_cython_cdef_int_except.py) has 100% precision on blosc2 but ~25% precision on uvloop — same syntactic pattern, completely different bug significance. The script can't tell the difference because it doesn't understand each project's structural conventions:
- blosc2 uses
cdef intfor C-Blosc2 callback registration → silent-noexcept matters → real bugs - uvloop uses
cdef intfor internal performance accessors → silent-noexcept rarely matters → low priority
Without orientation, downstream agents waste tokens re-deriving these conventions and produce noise-heavy reports. Your output captures the orientation once so they can focus on triage.
Pipeline position
You run first, before naive R1+R2 of the existing audit agents. Your output is saved to reports/<extension>_v1/preflight/generated_code_map.md and quoted into every downstream agent's prompt.
Detection cascade
Step through these sequentially:
Step 1: Detect generator(s)
For each generator, look for the listed signals. A project may use multiple generators (e.g., main API in Cython + helper libraries in pybind11 + a custom codegen). Catalog all of them.
| Generator | Signals to look for |
|---|---|
| Cython | .pyx, .pxd, .pxi files; cython>= in pyproject.toml; # cython: directives at top of source files; /* Generated by Cython X.Y.Z */ header in generated .c files |
| pybind11 | pybind11/... includes; PYBIND11_MODULE(name, m) macro; m.def(...) patterns; pybind11>= in pyproject.toml or CMakeLists |
| nanobind | nanobind/... includes; NB_MODULE(name, m) macro; differs from pybind11 in ownership/GC semantics |
| Argument Clinic | [clinic input] / [clinic start generated code] / [clinic end generated code] markers in source |
| Hand-written codegen | A separate program in the source tree that emits .c/.cxx/.cpp from another input language. Examples: vtkWrapPython (VTK), gobject-introspection scanners. Identify the generator-source file and the emitted-output pattern. |
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 · 225 lines · 0 tokens per session scan A 8e8dad953a15
generated-code-mapper is an agent published in the GitHub repository ReviewToolkits/cext-review-toolkit (29 stars, last pushed 2mo ago), licensed MIT. It adds 268 tokens to every session and 4,096 once invoked, about $0.0011 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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