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 aaronartistzhang-afk/DailyWork --skill group-discussion-reviewer-methodologygit clone --depth 1 https://github.com/aaronartistzhang-afk/DailyWorkWrote 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/aaronartistzhang-afk/dailywork/group-discussion-reviewer-methodology)<a href="https://agentmods.dev/skills/aaronartistzhang-afk/dailywork/group-discussion-reviewer-methodology"><img src="https://agentmods.dev/badge/skills/aaronartistzhang-afk/dailywork/group-discussion-reviewer-methodology/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/aaronartistzhang-afk/dailywork/group-discussion-reviewer-methodology"><img src="https://agentmods.dev/badge/skills/aaronartistzhang-afk/dailywork/group-discussion-reviewer-methodology.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 | $0.00203 | $0.00753 |
| Opus 5.5 | $0.00081 | $0.00301 |
| Sonnet 5.5 | $0.00041 | $0.00151 |
| Haiku 4.5 | $0.00020 | $0.00075 |
Grade A, and why
group-discussion-reviewer-methodology 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 — 43 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Group Discussion Reviewer — methodology (no key, inline)
Apply a disciplined product group-discussion review to a PRD directly in the conversation. No API key, no Node, no code execution — you (the agent) perform the review by following the written methodology.
This is the lightweight sibling of the
group-discussion-reviewerengine skill. The engine runs the same pipeline deterministically (and gates P0s with code) but needs an OpenAI-compatible key. Prefer the engine when a key is available and fidelity matters; use this methodology skill when there's no key, or for a quick framework-driven review.Honest limitation: without the engine's deterministic P0 gatekeeper, the strictness of P0 downgrading depends on your judgment. Hold the P0 bar hard.
How to use
- Get the PRD body as text/markdown (this skill does not fetch URLs or expand sheets).
- Read
methodology.mdin this folder and execute its 8 phases in order. - Produce exactly the output contract:
## 组内准入,## 模拟评审结果,## P0 Blockers,## P1 Questions,## P2 Questions,## P1/P2 Improvement Suggestions. - Respect the mode the user asks for (standard / deep / challenge; default challenge) and the language (default Chinese).
The core discipline (summary — full detail in methodology.md)
- Two independent axes: 组内准入 (is it concrete enough to discuss?) vs 模拟评审结果 (would it pass?). A PRD can be admitted and still 不通过.
- P0 only for four failures: wrong direction/population, unmeasurable success (for a formal decision), unsafe launch, or non-viable delivery — each with a concrete product bridge. Everything else (stats audit, SLA/QPS/monitoring, tracking schema, release checklist, compliance checklist, naming/icons, missing sections) defaults to P1/P2.
- A clean PRD has 0 P0. Don't inflate P0 to fill a quota.
- Blind review: PRD body only; ignore comments/annotations/post-meeting context. Ask questions, don't answer them — except every P0 must include a concrete revision.
What ships with it
2 files 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.
- 1mo ago First seen · 43 lines · 0 tokens per session scan A 575e25bd009c
group-discussion-reviewer-methodology is a skill published in the GitHub repository aaronartistzhang-afk/DailyWork (1 stars, last pushed 1mo ago), licensed MIT. It adds 203 tokens to every session and 753 once invoked, about $0.0008 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 2026-08-31.
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