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/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/rules/stunt-double/stuntdouble-mcp/stuntdouble-basics)<a href="https://agentmods.dev/rules/stunt-double/stuntdouble-mcp/stuntdouble-basics"><img src="https://agentmods.dev/badge/rules/stunt-double/stuntdouble-mcp/stuntdouble-basics.svg" alt="Measured on agentmods" 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 | $0.01445 | $0.01445 |
| Opus 5 | $0.00723 | $0.00723 |
| Sonnet 5 | $0.00289 | $0.00289 |
| Haiku 4.5 | $0.00145 | $0.00145 |
Grade A, and why
stuntdouble-basics 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 6d 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 — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
stuntdouble-basics:
- Stunt Double deploys AI agents with realistic user personas to validate user journeys at scale.
- Authentication is handled automatically via OAuth 2.1 with PKCE. No API keys or tokens are needed.
- Always specify a workspace when creating or listing resources. Use
list_workspacesto find available workspaces.
Finding things:
searchis the fastest way to locate anything in a workspace: projects, actors, checklists, interviews, automations, issues, goals, feedback, actor knowledge, insights, design reviews, project resources and conversations, all in one ranked call.- Prefer it over listing an entity type and filtering the list yourself. Narrow with
typesandproject_idwhen you already know the shape of what you want. - Search before you create. It is how you find the actor, checklist, or workflow that already covers the job instead of adding a near-duplicate.
- Search only ever returns entities from workspaces you are a member of; the boundary is enforced server-side, not by the filters you pass.
Actors:
- Actors represent AI user personas. Create actors with clear names (format: "FirstName - Role"), descriptions, and system prompts.
- Give actors knowledge via
add_actor_knowledgeso they understand your product context. - Conversations are read-only over MCP (
list_conversations,get_conversation); an actor chat is started from the dashboard. To probe actors for research, design reviews or concept testing, run an interview: it puts every persona through the same guide and synthesises the answers, which one-off chats cannot do. - Create diverse actors covering different segments: new users, power users, enterprise, accessibility, mobile.
Workflows and checklists:
- Use workflows for multi-step user journey validation (signup, checkout, onboarding flows).
- Use checklists for point-in-time quality checks (accessibility, performance, content).
- Workflow and checklist runs are asynchronous. After triggering a run, poll
get_workflow_runorget_checklist_runfor results. - Use
create_workflowwith trigger_type "schedule" or "webhook" for automated continuous validation.
Feedback:
- Review feedback items surfaced by Stunt Double and update their status as issues are triaged or resolved.
- Status lifecycle: new → reviewed → resolved (or dismissed for false positives).
- Cross-reference feedback with actors and workflows to identify patterns and coverage gaps.
Interviews:
- Interviews are structured user research rounds: a discussion guide (sections of questions and tasks) is run against a target URL by AI participants (existing actors or ad-hoc personas).
- Build the guide with
add_interview_sectionandadd_interview_itembefore launching. Each section should focus on one topic and contain orderedquestionortaskitems. - Add participants with
add_interview_participant— passactor_idto reuse an existing actor, orpersona_spec(name,bio,traits) for an ad-hoc persona. launch_interviewis async — it returns a trigger run ID and flips the interview torunning. Participants update independently; useget_interviewandget_interview_participantto follow progress.- Once participants complete, the synthesis task produces a report (summary, themes, recommendations, per-question rollup). Fetch it with
get_interview_report, or callregenerate_interview_reportafter editing transcripts or re-running participants.
Guidelines (the standards a workspace holds itself to):
- A guideline is a standing rule (design system, tone of voice, brand, content, accessibility, compliance, security, performance, shared knowledge). It is owned by the workspace and attached to the projects it applies to, so one rule holds for several projects without being retyped or edited in several places.
- Whatever is in force for a project is rendered into every checklist run, design review, interview and triage for it. Read
list_project_guidelinesbefore writing checks, interview questions or design feedback, and assert the rules rather than restating or contradicting them. - Two switches decide whether a rule is in force: the library's and the project attachment's.
list_project_guidelinesfolds them into oneenabled. - Write a rule once with
add_project_guideline(library plus this project) oradd_workspace_guideline(library only), then hold other projects to the same rule withset_project_guidelinerather than adding a near-duplicate. Checklist_workspace_guidelinesfirst. update_workspace_guidelinewithapply_to_design_reviewscarries a rule to every design review in the workspace, including the Slack and Linear reviews that have no project to attach it through.- Guidelines are project-wide standards;
add_actor_knowledgeis for what one actor needs to remember.
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.
- 6d ago First seen · 64 lines · 1,445 tokens per session scan A 8762a1404d84
stuntdouble-basics is a cursor rule published in the GitHub repository stunt-double/stuntdouble-mcp (1 stars, last pushed 21d ago), licensed MIT. It adds 1,445 tokens to every session, about $0.0072 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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