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 commands/reviewtoolkits/cpython-review-toolkit/informed-exploregit clone --depth 1 https://github.com/ReviewToolkits/cpython-review-toolkitWhat 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 | $0.00106 | $0.01817 |
| Opus 5 | $0.00053 | $0.00908 |
| Sonnet 5 | $0.00021 | $0.00363 |
| Haiku 4.5 | $0.00011 | $0.00182 |
Grade A, and why
informed-explore scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Informed CPython C Code Exploration
Same coverage as explore, but informed: every agent is seeded with the toolkit's
accumulated knowledge before it triages. That is what turns a cold, re-discovering pass into a
fix-propagation sweep — finding every instance of a known bug shape and naming the guarded twin that
fixes it. Validated pattern, ported from the sibling toolkits' informed runs.
Arguments: "$ARGUMENTS"
Plugin root: <plugin_root> is the plugins/cpython-review-toolkit/ directory — this command
file's grandparent. Resolve it relative to this file.
Argument Parsing
Identical to explore: scope (path or glob, default the whole checkout), aspects (the same
aspect→agent table as explore.md, default all), and options (deep, summary, parallel,
--max-parallel N).
Execution Workflow
Phase 0 — Project Discovery
Exactly as explore Phase 0: identify the CPython root (Include/Python.h + Objects/object.c),
count .c/.h files in scope, read the version from Include/patchlevel.h, print a brief scope
summary.
Phase 0.5 — Build the informed briefing ← the new step
python <plugin_root>/scripts/build_informed_briefing.py > reports/preflight/informed_briefing.md
If you keep the durable findings repo
(cpython-review-findings) checked out — the
static analog of the cpython-oom-findings / cpython-tsan-findings repos — add
--catalog-dir <path-to-cpython-review-findings> to fold its reports/*/meta.json entries into the
briefing as "confirm, don't re-litigate" leads, so a re-review is cumulative.
This assembles a Markdown briefing from three catalogs:
data/cpython_bug_shapes.json— recurring CPython C bug SHAPES, each with its guarded twin (the correctly-handled sibling = the fix), a sibling-hunt directive, a confirming differential, and which scanner surfaces it.- The cross-cutting triage rules (guarded-twin-is-the-signal, both-crash ≠ acceptable, reachability-first, confirm-don't-relitigate, Class-J out of scope).
data/cpython_non_bugs.md— the false-positive taxonomy, reproduced inline.
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 · 125 lines · 106 tokens per session scan A 78121d6450e2
informed-explore is a command published in the GitHub repository ReviewToolkits/cpython-review-toolkit (10 stars, last pushed 1mo ago), licensed MIT. It adds 106 tokens to every session and 1,817 once invoked, about $0.0005 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 2026-08-31.
Other commands, from other repositories
git
Git operations with intelligent commit messages and workflow optimization.
checklist
Generate a custom checklist for the current feature based on user requirements.
clarify
Identify underspecified areas in the current feature spec by asking up to 5 highly targeted clarification questions and encoding answers back into the spec.
specify
Create or update the feature specification from a natural language feature description.
analyze
Perform a non-destructive cross-artifact consistency and quality analysis across spec.md, plan.md, and tasks.md after task generation.
converge
Assess the current codebase against the feature's spec, plan, and tasks, then append any remaining unbuilt work as new tasks to tasks.md so implement can complete it.