Borrowing it
Nothing to install: this file belongs to deonmenezes/mantishack. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/deonmenezes/mantishack/main/.codex/skills/code-review-context/SKILL.mdgit clone --depth 1 https://github.com/deonmenezes/mantishackWrote 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/skills/deonmenezes/mantishack/code-review-context)<a href="https://agentmods.dev/skills/deonmenezes/mantishack/code-review-context"><img src="https://agentmods.dev/badge/skills/deonmenezes/mantishack/code-review-context/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/skills/deonmenezes/mantishack/code-review-context"><img src="https://agentmods.dev/badge/skills/deonmenezes/mantishack/code-review-context.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 | $0.00007 | $0.00142 |
| Opus 5.5 | $0.00003 | $0.00057 |
| Sonnet 5.5 | $0.00001 | $0.00028 |
| Haiku 4.5 | $0.00001 | $0.00014 |
Grade A, and why
code-review-context 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.
This is a copy
100% identical to code-review-context — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Codex maintains a context (history of messages) that is sent to the model in inference requests.
- No history rewrite - the context must be built up incrementally.
- Avoid frequent changes to context that cause cache misses.
- No unbounded items - everything injected in the model context must have a bounded size and a hard cap.
- No items larger than 10K tokens.
- Highlight new individual items that can cross >1k tokens as P0. These need an additional manual review.
- All injected fragments must be defined as structs in
core/contextand implement ContextualUserFragment trait
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 · 13 lines · 7 tokens per session scan A 0af80b6388cc
code-review-context is a skill published in the GitHub repository deonmenezes/mantishack (504 stars, last pushed 18d ago), licensed Apache-2.0. It adds 7 tokens to every session and 142 once invoked, about $0.0000 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to code-review-context, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
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wiki-ingest
Use when an operation issue asks to ingest a captured raw/ source into the LLM Wiki, or the user says "ingest ". Create durable source, entity, concept, synthesis, index, and log pages; use paperclip-distill for Paperclip bundles.
wiki-lint
Use when an LLM Wiki operation issue is a lint or health check. Audit for contradictions, orphans, weak provenance, broken links, missing concept pages, and index/log drift; return triage findings without auto-fixing.
agent-v3-memory-specialist
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agent-memory-coordinator
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