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 stunt-double/stuntdouble-mcp --skill design-reviewgit clone --depth 1 https://github.com/stunt-double/stuntdouble-mcpWrote 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/stunt-double/stuntdouble-mcp/design-review)<a href="https://agentmods.dev/skills/stunt-double/stuntdouble-mcp/design-review"><img src="https://agentmods.dev/badge/skills/stunt-double/stuntdouble-mcp/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/stunt-double/stuntdouble-mcp/design-review"><img src="https://agentmods.dev/badge/skills/stunt-double/stuntdouble-mcp/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 | $0.00024 | $0.00969 |
| Opus 5 | $0.00012 | $0.00485 |
| Sonnet 5 | $0.00005 | $0.00194 |
| Haiku 4.5 | $0.00002 | $0.00097 |
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 10d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Design review
When to use
- When evaluating a new design, flow, or prototype before implementation
- When comparing two or more design options
- Before engineering handoff to validate the proposed UX
- When a PM or designer wants diverse user perspectives on a concept
Instructions
-
Set up the workspace and select actors:
list_workspaces()→ find the workspacelist_actors(workspace_id)→ review available personas- Pick 3-5 actors representing different user segments (new user, power user, enterprise, accessibility, mobile, etc.)
-
Brief the actors (if needed):
add_actor_knowledge(actor_id, title, content)→ share design context, screenshots, feature descriptions, or prototype links with each actor- This ensures actors have the right context to give informed feedback
-
Run the review as an interview:
create_interview(workspace_id, project_id, name: "Design review: <feature>", target_url, research_brief)→ describe the proposed design clearly in the brief: what it does, how the user would interact with it, and what the key decision points areadd_interview_section(interview_id, title)thenadd_interview_item(section_id, type, prompt_text)→ mixtaskitems ("Find the annual price and start checkout") with specific questions ("Would you understand what this button does?", "What would you expect to happen next?", "Is anything confusing or missing?")add_interview_participant(interview_id, actor_id)→ one per selected actor, orpersona_specfor an ad-hoc personalaunch_interview(interview_id)→ async, pollget_interview(interview_id)until terminal
-
Collect and read responses:
get_interview_report(interview_id)→ summary, themes, recommendations, per-question rollupget_interview_participant(participant_id)→ verbatim transcript evidence for a finding- Conversations are read-only over MCP:
list_conversations/get_conversationread chats started in the dashboard
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.
- 10d ago First seen · 90 lines · 24 tokens per session scan A 875497fa4764
design-review is a skill published in the GitHub repository stunt-double/stuntdouble-mcp (1 stars, last pushed 26d ago), licensed MIT. It adds 24 tokens to every session and 969 once invoked, about $0.0001 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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