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 dsifry/metaswarm --skill design-review-gategit clone --depth 1 https://github.com/dsifry/metaswarmWrote 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/dsifry/metaswarm/design-review-gate)<a href="https://agentmods.dev/skills/dsifry/metaswarm/design-review-gate"><img src="https://agentmods.dev/badge/skills/dsifry/metaswarm/design-review-gate/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/dsifry/metaswarm/design-review-gate"><img src="https://agentmods.dev/badge/skills/dsifry/metaswarm/design-review-gate.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 | $0.00035 | $0.03928 |
| Opus 5 | $0.00017 | $0.01964 |
| Sonnet 5 | $0.00007 | $0.00786 |
| Haiku 4.5 | $0.00003 | $0.00393 |
Grade A, and why
design-review-gate 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 — 606 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design Review Gate
Purpose
This skill automatically activates after a design document is created (typically via superpowers:brainstorming). It ensures complex features receive proper review before implementation begins by spawning five specialist agents:
- Product Manager Agent - Use case validation and user benefit review
- Architect Agent - Technical architecture review
- Designer Agent - UX/API design quality review
- Security Design Agent - Security threat modeling and protection review
- CTO Agent - Codebase alignment and TDD readiness review
All five must approve before proceeding to implementation.
Coordination Mode Note
This skill supports both coordination modes:
- Task Mode (default): Spawn 5 parallel
Task()subagents for each review round. Fresh instances per round. - Team Mode:
TeamCreate("review-{design-doc-name}"), spawn 5 reviewers as named teammates (pm,architect,designer,security,cto). Reviewers retain context through revision cycles — saves 5 cold starts per re-review round. After approval, sendshutdown_requestto all, thenTeamDelete.
In either mode, the review criteria, iteration protocol, and escalation rules are identical. See ./guides/agent-coordination.md for mode detection.
Activation Triggers
This skill auto-activates when:
- A design document is committed to
docs/plans/*-design.md - The
superpowers:brainstormingskill completes - User explicitly requests:
/review-design <path-to-design.md>
Workflow
Phase 1: Spawn Review Agents (Parallel)
// Spawn all five agents in parallel for efficiency
const [pmResult, architectResult, designerResult, securityResult, ctoResult] = await Promise.all([
Task({
subagent_type: "general-purpose",
description: "PM review",
prompt: pmReviewPrompt(designDocPath),
}),
Task({
subagent_type: "general-purpose",
description: "Architect review",
prompt: architectReviewPrompt(designDocPath),
}),
Task({
subagent_type: "general-purpose",
description: "Designer review",
prompt: designerReviewPrompt(designDocPath),
}),
Task({
subagent_type: "general-purpose",
description: "Security design review",
prompt: securityDesignReviewPrompt(designDocPath),
}),
Task({
subagent_type: "general-purpose",
description: "CTO review",
prompt: ctoReviewPrompt(designDocPath),
}),
]);
What ships with it
1 file 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.
- 11d ago First seen · 606 lines · 35 tokens per session scan A a58fa4462a49
design-review-gate is a skill published in the GitHub repository dsifry/metaswarm (413 stars, last pushed 2mo ago), licensed MIT. It adds 35 tokens to every session and 3,928 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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