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 ddddjaak/se-skills --skill design-reviewgit clone --depth 1 https://github.com/ddddjaak/se-skillsWrote 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/ddddjaak/se-skills/design-review)<a href="https://agentmods.dev/skills/ddddjaak/se-skills/design-review"><img src="https://agentmods.dev/badge/skills/ddddjaak/se-skills/design-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/ddddjaak/se-skills/design-review"><img src="https://agentmods.dev/badge/skills/ddddjaak/se-skills/design-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 | $0.00167 | $0.04734 |
| Opus 5 | $0.00084 | $0.02367 |
| Sonnet 5 | $0.00033 | $0.00947 |
| Haiku 4.5 | $0.00017 | $0.00473 |
Grade A, and why
design-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 11d 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 — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Review
Overview
An SE artifact reviewed by its author finds the problems the author already knows about. An SE artifact reviewed by a meeting finds the problems people notice while reading for approval. A design review that matters finds the problems no single reader would catch — the cross-domain inconsistencies, the unstated assumptions, the failure modes that only emerge when HW, SW, Test, and System perspectives collide.
This skill applies adversarial review methodology to SE artifacts. It materializes four fresh-context reviewers, each biased to disprove through their department's lens, and reconciles their findings into a single actionable report. Run it before the formal design review meeting — so the meeting is about decisions, not discovery.
When to Use
- An SE artifact (requirements document, architecture design, specification) is complete and ready for cross-department distribution
- Before a formal design review meeting — surface issues in advance so the meeting is productive
- When integrating across department boundaries (HW↔SW, power↔thermal, boot↔security)
- After a significant design change that may have ripple effects across modules or domains
- A downstream consumer of the artifact reports that the document is ambiguous, incomplete, or inconsistent
- Preparing for a milestone review (requirements freeze, design freeze, test readiness)
When NOT to use:
- The artifact is an early draft the author has not self-reviewed yet (self-review first, then adversarial review)
- Typos, formatting errors, or mechanical corrections (these do not need four-lens adversarial review)
- The user explicitly wants speed over thoroughness for a low-risk, single-department artifact
- Reviewing implementation code (use a code review process, not this design artifact review)
- Pure information lookup ("does this register address match the datasheet?" — verify directly, don't review)
The Process
SCOPE ──→ LENS-REVIEW ──→ RECONCILE ──→ REPORT
│ │ │ │
▼ ▼ ▼ ▼
Define Four parallel Classify Produce
artifact adversarial findings review
& depth reviews by severity report
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.
- 11d ago First seen · 356 lines · 167 tokens per session scan A 19b601c88f0f
design-review is a skill published in the GitHub repository ddddjaak/se-skills (4 stars, last pushed 1mo ago), licensed MIT. It adds 167 tokens to every session and 4,734 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 2026-08-31.
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