Borrowing it
Nothing to install: this file belongs to VGrss/Acumen. 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/VGrss/Acumen/main/.agents/skills/critique-product/SKILL.mdgit clone --depth 1 https://github.com/VGrss/AcumenWrote 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/vgrss/acumen/critique-product)<a href="https://agentmods.dev/skills/vgrss/acumen/critique-product"><img src="https://agentmods.dev/badge/skills/vgrss/acumen/critique-product.svg" alt="Measured on agentmods" 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 | $0.00045 | $0.02392 |
| Opus 5 | $0.00023 | $0.01196 |
| Sonnet 5 | $0.00009 | $0.00478 |
| Haiku 4.5 | $0.00005 | $0.00239 |
Grade A, and why
critique-product 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 8d 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 — 180 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Critique Product
Preparation
Before anything else, invoke /product-thinking to load strategic context, user segments, and current product landscape.
Then read ALL context files:
.acumen.md— product strategy and positioning.acumen/competitors.md— competitive landscape.acumen/personas.md— user segments and behaviors.acumen/features.md— current feature catalog./DESIGN.md— visual identity contract (only when critiquing UI-touching artifacts; if missing, flag it)
A critique without context is just opinion. You need to know what the product is, who it serves, and what it's competing against before you can evaluate whether an artifact is good.
Mindset
Read this as if you're the engineer who has to build it, the exec who has to fund it, and the designer who has to make it real. Does it survive all three?
The engineer asks: "Can I scope work from this? Are the edge cases covered? Will I have to come back with 40 clarifying questions?"
The exec asks: "Why should I fund this over the other six things competing for the same resources? What's the expected return?"
The designer asks: "Do I know who this is for? Is the problem clear enough that I can design a solution without guessing?"
If any of them would struggle, the artifact needs work.
Core Reflex
Step 1: AI Product Slop Test
Run the slop check first. Scan for these 15 tells — each one weakens the document:
- "Users want..." without evidence (who said this? how many? when?)
- Missing baselines (targets without current numbers are wishes)
- Vague scope ("and more," "etc.," "additional features" — scope creep hiding in plain sight)
- No prioritization rationale (why THIS order? why NOW?)
- Solutions masquerading as problems ("users need a dashboard" is a solution; what's the actual problem?)
- Missing edge cases (what happens when it fails? when data is missing? when the user does something unexpected?)
- Competitor blindness (no mention of alternatives users have today)
- Metric-free success criteria ("improve the experience" — how would you know?)
- One-size-fits-all personas ("our users" instead of specific segments with different needs)
- No tradeoff acknowledgment (everything is upside, nothing is cost)
- Jargon without definition (acronyms and internal terms that assume shared context)
- Missing timeline or sequencing (what ships first? what depends on what?)
- Unjustified new surface (a new screen, page, or tab where an existing one would have carried the job — and no line explaining why it couldn't)
- Everything on screen (no cut list, no hidden state, no hierarchy — the artifact never says what it deliberately left out)
- Options instead of decisions (settings, toggles, and "configurable" behavior standing in for a choice the author should have made)
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.
- 8d ago First seen · 180 lines · 45 tokens per session scan A 6114ea021aa1
critique-product is a skill published in the GitHub repository VGrss/Acumen (11 stars, last pushed 1mo ago), licensed Apache-2.0. It adds 45 tokens to every session and 2,392 once invoked, about $0.0002 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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