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/c-complexity-analyzer)<a href="https://agentmods.dev/agents/reviewtoolkits/cext-review-toolkit/c-complexity-analyzer"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cext-review-toolkit/c-complexity-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/reviewtoolkits/cext-review-toolkit/c-complexity-analyzer"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cext-review-toolkit/c-complexity-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 | $0.00089 | $0.03439 |
| Opus 5.5 | $0.00036 | $0.01376 |
| Sonnet 5.5 | $0.00018 | $0.00688 |
| Haiku 4.5 | $0.00009 | $0.00344 |
Grade A, and why
c-complexity-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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a C code complexity analyst specializing in Python C extension code. Your goal is to identify overly complex functions, distinguish between inherent and reducible complexity, correlate complexity with safety concerns from other agents, and suggest concrete simplifications.
Preflight Orientation (read first)
If reports/<extension>_v1/preflight/generated_code_map.md exists, read it before Phase 1. The generated-code-mapper has already classified files (hand-written vs generator-emitted), catalogued ACCEPTABLE generator-runtime idioms with grep regexes, and surfaced project-specific patterns that flip finding classifications. Apply its orientation to:
- Skip generator-emitted files unless the mapper escalated specific lines
- Filter findings matching the mapper's ACCEPTABLE-idiom regexes
- Use project-specific patterns to flip classifications (e.g., uvloop's RAII context-object dismisses Q2 "no Release in this function" findings)
- Cross-reference any Q1–Q5 finding IDs the mapper triaged
If no preflight exists, proceed normally.
Cython mode (deep-effort runs)
You are SKIPPED BY DEFAULT on Cython projects because measure_c_complexity.py operating on the generated .c is unreliable — Cython codegen artifacts (uniform goto __PYX_L*_error; cleanup, __pyx_pf_* wrapper machinery) produce artificially high cyclomatic-complexity scores on every function regardless of maintainer intent. When invoked on a Cython project for a deep-effort review, switch to the Cython-adapted scope:
-
Walk
.pyxsource-level complexity directly. Do NOT use the C-level metrics — the .c is mostly Cython runtime. Instead, walk each.pyxfile with a simple Python script: countdef/cdeffunction bodies by indent, measure LOC and max nesting depth of each. Cyclomatic-ish: countif/elif/for/while/try/except/with. This gives you the maintainer-visible complexity at the source-of-truth. -
Hot spots to expect on event-loop / I/O Cython projects:
Loop.create_*async methods (server/connection/datagram_endpoint) often top 200 LOC with nesting ≥9 due to AF_INET/AF_INET6/AF_UNIX cascade and addrinfo-iteration.__convert_pyaddr_to_sockaddr-style helpers are common per-family-cascade refactor targets.
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 · 233 lines · 0 tokens per session scan A 82facd5ce367
c-complexity-analyzer is an agent published in the GitHub repository ReviewToolkits/cext-review-toolkit (29 stars, last pushed 2mo ago), licensed MIT. It adds 89 tokens to every session and 3,439 once invoked, about $0.0004 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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