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 caiaffa/claude-code-ultimate-engineering-system --skill prd-reviewgit clone --depth 1 https://github.com/caiaffa/claude-code-ultimate-engineering-systemWrote 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/caiaffa/claude-code-ultimate-engineering-system/prd-review)<a href="https://agentmods.dev/skills/caiaffa/claude-code-ultimate-engineering-system/prd-review"><img src="https://agentmods.dev/badge/skills/caiaffa/claude-code-ultimate-engineering-system/prd-review/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/caiaffa/claude-code-ultimate-engineering-system/prd-review"><img src="https://agentmods.dev/badge/skills/caiaffa/claude-code-ultimate-engineering-system/prd-review.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 | $0.01197 |
| Opus 5.5 | $0.00025 | $0.00479 |
| Sonnet 5.5 | $0.00012 | $0.00239 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
prd-review 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 2mo 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mission
Ensure the team builds the right thing AND can build it well. Review the PRD the way a staff engineer and a senior PM would in a peer review — critique and ask, never rewrite. The PRD belongs to the PM; this skill produces feedback.
When to use
- Reviewing a PRD before engineering commitment.
- The daily routine review of PRDs synced from Drive.
Handoff
- Receives from: principal-engineer (initial review).
- Hands off to: architecture-decisions (if approved) or back to the PM (if not).
Engineering lens
Front 1 - Problem, value & audience
- What metric proves this problem exists today? How big is it?
- Root cause or symptom?
- "Show me the number": baseline, expected gain, mechanism linking solution to gain.
- Cost-to-value ratio acceptable for the time horizon?
- Which users/personas are affected - and what happens to those who are NOT the target audience? What is the blast radius if it goes wrong?
Front 2 - Metrics & measurement
- Is the baseline credible and measured today?
- Are success criteria specific and measurable?
- Guardrail metrics - what must NOT regress?
- How and when is impact observed?
Front 3 - Gaps & hidden engineering work
- Sections missing or vague?
- Engineering work implied but unstated: migrations, backfill, infra, auth.
- Ambiguities that will block implementation.
- Quick feasibility check: does this conflict with ~/.claude/engineering/SYSTEM_INVARIANTS.md, or depend on a service/data that does not exist? (Deep design goes to /adr.)
Front 4 - Dependencies & sequencing
- Which other teams, systems, or PRDs does this depend on?
- What must exist before this can start?
- Coupling with work already in flight?
- Sequencing or ownership risk ("we found mid-build we needed team X")?
Front 5 - Decision quality & risk
- Is the scope disciplined, or a wishlist? Are cuts identified?
- Is the decision reversible if the bet is wrong?
- Operational cost (run + maintain) considered?
- Non-technical risk: legal/compliance, data privacy (LGPD), product-level security (does this expose sensitive data?), reputation. Cross-check ~/.claude/engineering/ENGINEERING_RISKS_FROM_PRD.md.
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.
- 2mo ago First seen · 119 lines · 62 tokens per session scan A 2bf60589baef
prd-review is a skill published in the GitHub repository caiaffa/claude-code-ultimate-engineering-system (17 stars, last pushed 2mo ago), licensed MIT. It adds 62 tokens to every session and 1,197 once invoked, about $0.0002 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 2026-09-15.
prd-review compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| prd-reviewcaiaffa/claude-code-ultimate-engineering-system | Skill | 17 | 2mo ago | MIT | A | 62 | Claude Code |
| imagegenopenai/codex | Skill | 135k | today | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 100k | today | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 80k | 7d ago | MIT | A | 200 | Claude Code, Codex |
| next-cache-components-adoptionvercel/next.js | Skill | 144k | today | MIT | A | 95 | Claude Code |
| chat-pet-sprite-creationmicrosoft/vscode | Skill | 195k | today | MIT | A | 53 | Claude Code, Codex |