Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/matteotitta/genesys-skillsnpx agentmods add skills/matteotitta/genesys-skills/product-lens-reviewerWrote 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/matteotitta/genesys-skills/product-lens-reviewer)<a href="https://agentmods.dev/skills/matteotitta/genesys-skills/product-lens-reviewer"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/product-lens-reviewer/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/matteotitta/genesys-skills/product-lens-reviewer"><img src="https://agentmods.dev/badge/skills/matteotitta/genesys-skills/product-lens-reviewer.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00155 | $0.01538 |
| Opus 5 | $0.00077 | $0.00769 |
| Sonnet 5 | $0.00031 | $0.00308 |
| Haiku 4.5 | $0.00015 | $0.00154 |
Grade A, and why
product-lens-reviewer 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 12d 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 — 141 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product-lens reviewer
Review any document through a product POV. Composes with voice-reviewer (style/voice) and design-reviewer (visual/UX). Adapted from ce-product-lens-reviewer agent in EveryInc/compound-engineering-plugin v3.5.0 (MIT).
This is the structural counterpart to voice-reviewer. Voice asks "does this sound right?"; product asks "does this think right?"
When to run
Invoke when the user says:
- "Run product review on [doc]"
- "Review this through a product lens"
- "PM review this strategy"
- "Is this strategy any good?"
- "Pre-lock review on [strategy-doc / proposal / launch plan]"
Do NOT invoke when:
- User wants voice review →
voice-reviewer - User wants visual review →
design-reviewer - User wants code review →
engineering:code-review
Composes with: voice-reviewer, design-reviewer, scope-guardian-reviewer (often run together as a review-pass family before locking strategic docs).
Inputs
Required:
- The document to review (text)
Recommended:
strategy-doc(if reviewing a strategy doc, comparing against itself; if reviewing a downstream artifact like a launch plan, comparing against the upstream strategy)positioning(cross-check differentiation defensibility)icp-research(cross-check persona focus)
The 6 dimensions
Each dimension scores PASS / WARN / FAIL with quoted evidence.
| # | Dimension | Trigger |
|---|---|---|
| 1 | Target-problem clarity | Is the problem specific, recurring, expensive? Cited evidence vs. generic? |
| 2 | Persona focus | One persona ideally; if 3+ — FAIL (audience, not persona) |
| 3 | Metric quality | SMART criteria; anti-vanity-metrics rule — page views/impressions/MAU without conversion → FAIL |
| 4 | Differentiation defensibility | Would a skeptical buyer choose this over alternatives? Cite the alternative + why this beats it |
| 5 | Scope discipline | Does the doc stay in its lane? Strategy doesn't include requirements (K6); spec doesn't include strategy; proposal doesn't blur with positioning |
| 6 | Shipping-as-experiment framing | Is the ship treated as data generation (K1)? Hypothesis stated? Falsifiable? |
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.
- 12d ago First seen · 141 lines · 155 tokens per session scan A d57b927ad5fb
product-lens-reviewer is a skill published in the GitHub repository matteotitta/genesys-skills (36 stars, last pushed 1mo ago), licensed MIT. It adds 155 tokens to every session and 1,538 once invoked, about $0.0008 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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