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 skills add Undertone0809/rudder --skill codex-session-product-reviewer-maintainergit clone --depth 1 https://github.com/Undertone0809/rudderWrote 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/undertone0809/rudder/codex-session-product-reviewer-maintainer)<a href="https://agentmods.dev/skills/undertone0809/rudder/codex-session-product-reviewer-maintainer"><img src="https://agentmods.dev/badge/skills/undertone0809/rudder/codex-session-product-reviewer-maintainer/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/undertone0809/rudder/codex-session-product-reviewer-maintainer"><img src="https://agentmods.dev/badge/skills/undertone0809/rudder/codex-session-product-reviewer-maintainer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 50 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
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 | $0.00054 | $0.02072 |
| Opus 5 | $0.00027 | $0.01036 |
| Sonnet 5 | $0.00011 | $0.00414 |
| Haiku 4.5 | $0.00005 | $0.00207 |
Grade A, and why
codex-session-product-reviewer-maintainer 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 11d 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 — 253 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codex Session Product Reviewer Maintainer
This skill reviews a completed or in-progress Codex task from a product manager's point of view. It is a reviewer workflow, not an implementation workflow.
The core question is:
Did this session solve the right product problem, with the right scope, behavior, and validation?
Use it to turn a vague request like "review this Codex session as a PM" into a grounded product review based on the session transcript, actual code changes, tests, plan docs, and repository product standards.
Use When
Use this skill when the user asks to:
- review a Codex session id, task, thread, or run as a product manager
- evaluate whether another agent's implementation was product-correct
- apply first-principles thinking to a shipped task
- judge whether a proposal or implementation solved the right user problem
- produce a reviewer-style accept / conditional accept / reject
- translate fuzzy dissatisfaction into explicit product critique
Common trigger phrases:
- "review 一下 codex session id ..."
- "as a 专业的产品经理 review"
- "第一性原理思考一下"
- "作为 reviewer"
- "PM review this task"
- "这个 session 做得怎么样"
- "这个实现是不是产品上对"
Do Not Use When
Do not use this skill for:
- generic code review where the user mainly wants bugs and line comments
- debugging a failed Rudder agent run transcript
- creating a new product idea or brainstorming from scratch
- implementing the fixes found during review, unless the user explicitly asks
- summarizing a session without judgment
- judging only from the final assistant message when local evidence is available
If the user asks for code correctness review, use a code-review workflow. If the user asks why a Rudder agent run failed, use the run transcript debugging workflow first.
Inputs
Required:
- A Codex session id, commit hash, PR, branch, or clearly identified task to review.
Optional:
- The review lens, such as PM, first principles, design, workflow, release, or founder mode.
- A desired output style, such as short verdict, detailed memo, or findings only.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 253 lines · 54 tokens per session scan A c2b661525b9d
codex-session-product-reviewer-maintainer is a skill published in the GitHub repository Undertone0809/rudder (288 stars, last pushed today), licensed Apache-2.0. It adds 54 tokens to every session and 2,072 once invoked, about $0.0003 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 2026-08-30.
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