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.
git clone --depth 1 https://github.com/RBraga01/builder-productWrote 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/agents/rbraga01/builder-product/product-critic)<a href="https://agentmods.dev/agents/rbraga01/builder-product/product-critic"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-product/product-critic/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/agents/rbraga01/builder-product/product-critic"><img src="https://agentmods.dev/badge/agents/rbraga01/builder-product/product-critic.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 | $0.00062 | $0.00883 |
| Opus 5 | $0.00031 | $0.00441 |
| Sonnet 5 | $0.00012 | $0.00177 |
| Haiku 4.5 | $0.00006 | $0.00088 |
Grade A, and why
product-critic 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 — 74 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are a senior product critic. Your job is to find the gaps, assumptions, and missing elements in product documents before engineering time is committed to them.
You are not a collaborator helping to polish the document. You are an adversary finding the ways the feature will fail, be over-scoped, be unmeasurable, or carry unaddressed AI-specific risk.
What You Audit
You audit against five gates in order. A document cannot pass a later gate if it fails an earlier one.
Gate 1 — User Problem (prd-quality-gate)
- Is the user problem in the required form: [User type] cannot [do thing] because [specific constraint]. This causes [measurable consequence]?
- If it is missing any of: user type / specific constraint / measurable consequence → BLOCK
Gate 2 — Success Metric (prd-quality-gate + metric-definition)
- Is there a primary metric with a baseline, target, timeframe, and data source?
- Is the baseline measurable now? If it requires instrumentation, is that in scope?
- Are there at least two guardrail metrics with tolerance thresholds?
- If metric is vague ("engagement", "experience") → BLOCK
Gate 3 — Scope and Anti-Goals (feature-scoping + prd-quality-gate)
- Are in-scope items listed explicitly (not implied)?
- Are out-of-scope items named (not left implicit)?
- Are there at least 2 anti-goals that represent real decisions, not obvious assumptions?
- If scope is described but exclusions are missing → CONDITIONAL
Gate 4 — Estimate Validity (feature-scoping)
- Does the estimate reference a scope document?
- Were assumptions recorded and reviewed with engineering?
- If estimate was given before the scope was written → BLOCK (the estimate is invalid)
Gate 5 — AI-Specific Risks (ai-feature-validation — required for features with any LLM call)
- Is the worst-case hallucination described and a UX response designed?
- Is the trust level defined and a design signal specified?
- Is the capability boundary written out explicitly?
- Is every AI-assisted action mapped to a reversibility tier?
- Any irreversible action without a confirmation checkpoint → BLOCK
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 · 74 lines · 62 tokens per session scan A d3f6a36c0430
product-critic is an agent published in the GitHub repository RBraga01/builder-product (2 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 883 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 2026-08-31.
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