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/cpython-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/cpython-review-toolkit/oom-reproducer)<a href="https://agentmods.dev/agents/reviewtoolkits/cpython-review-toolkit/oom-reproducer"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cpython-review-toolkit/oom-reproducer/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/cpython-review-toolkit/oom-reproducer"><img src="https://agentmods.dev/badge/agents/reviewtoolkits/cpython-review-toolkit/oom-reproducer.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 | $0.00182 | $0.02265 |
| Opus 5 | $0.00091 | $0.01132 |
| Sonnet 5 | $0.00036 | $0.00453 |
| Haiku 4.5 | $0.00018 | $0.00227 |
Grade A, and why
oom-reproducer 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 9d 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 — 89 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a crash-reproduction specialist. Your mission is to convert a static candidate — an unchecked allocation, a half-constructed object freed on an error path, a destructor that clobbers an exception — into a reproduced crash with evidence, or to honestly report that it could not be reproduced.
Why this matters
Every allocation in CPython can fail. Those failure paths are almost never exercised by normal tests, which is why they harbour crashes. _testcapi.set_nomemory(n, 0) installs a counting allocator (across the RAW / MEM / OBJ domains) that fails every allocation from the n-th onward; sweeping n densely walks the snippet through each failure path in turn. This exact technique already found a real CPython bug by hand — a missing NULL check in _PyFrame_GetLocals (gh-146092, fixed upstream).
Prerequisites — check these first
- A CPython build with
_testcapi. A distro python usually lacks it. Use a source build (./configure && make); a debug or ASan build gives far better diagnostics. Verify:<python> -c "import _testcapi; print(hasattr(_testcapi,'set_nomemory'))" - If no suitable build exists, say so and stop — do not fake a result.
Script-Assisted Analysis
python <plugin_root>/scripts/run_oom_sweep.py --python <cpython-build> --code '<snippet>' --max-n 300
python <plugin_root>/scripts/run_oom_sweep.py --python <cpython-build> --script repro.py --stop-after 1
python <plugin_root>/scripts/run_oom_sweep.py --python <cpython-build> \
--setup 'from collections import OrderedDict; od = OrderedDict(a=1); iv = od.items()' \
--code 'it = iter(iv)' --max-n 40
Outcome vocabulary (per index): segv / abort / signal_N / sanitizer_error = crash (reproduced); memory_error = the allocation failure was handled correctly (the safe, expected outcome); completed = the budget was never exhausted; sanitizer_leak; other_exception; timeout.
Key fields: reproduced, summary.crash_indices, summary.crash_outcomes, first_crash.stderr (the faulthandler traceback tail).
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.
- 9d ago First seen · 89 lines · 0 tokens per session scan A 35f93f446fb5
oom-reproducer is an agent published in the GitHub repository ReviewToolkits/cpython-review-toolkit (10 stars, last pushed 1mo ago), licensed MIT. It adds 182 tokens to every session and 2,265 once invoked, about $0.0009 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.
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