Borrowing it
Nothing to install: this file belongs to kensaurus/mushi-mushi. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/kensaurus/mushi-mushi/master/.cursor/skills/mushi-test/SKILL.mdgit clone --depth 1 https://github.com/kensaurus/mushi-mushiWrote 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/kensaurus/mushi-mushi/mushi-test)<a href="https://agentmods.dev/skills/kensaurus/mushi-mushi/mushi-test"><img src="https://agentmods.dev/badge/skills/kensaurus/mushi-mushi/mushi-test/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/kensaurus/mushi-mushi/mushi-test"><img src="https://agentmods.dev/badge/skills/kensaurus/mushi-mushi/mushi-test.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 | $0.00088 | $0.00882 |
| Opus 5 | $0.00044 | $0.00441 |
| Sonnet 5 | $0.00018 | $0.00176 |
| Haiku 4.5 | $0.00009 | $0.00088 |
Grade A, and why
mushi-test 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 9d 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 — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Mushi TDD Testing Guide
The TDD Loop
Live App → map stories → generate tests → approve → run → analyze failures → improve → repeat
Step 1: Map User Stories
# Automatic discovery from live app (recommended)
mushi stories map --url https://your-app.com --wait
# Or use the console: Inventory → Discovery → "Map from live app"
Review the draft in Inventory → Discovery → Past proposals and click Accept.
Step 2: Generate Playwright Tests
# From CLI (after accepting a proposal)
mushi tdd gen <story-id> --mode review
# Options:
# --mode auto → enabled immediately, no approval needed
# --mode review → lands in pending queue (default)
# --no-pr → skip GitHub PR
# Or via MCP in Cursor:
# generate_tdd_from_story(projectId, storyNodeId, automationMode: 'review')
Each generated test includes:
- Full TypeScript Playwright spec (
@playwright/test) - Firecrawl Actions YAML equivalent (for cloud-only execution)
- Draft GitHub PR (if configured)
Step 3: Review and Approve
# See what needs review
mushi tdd pending
# Approve a test (enables it in QA schedule)
mushi tdd approve <qa-story-id>
# Reject a test
mushi tdd approve <qa-story-id> --reject
In the console: QA Coverage → "TDD Tests Pending Review" banner shows the queue.
Step 4: Run Tests
Tests run automatically on cron (default: hourly).
# Trigger manually
mushi tdd run <qa-story-id>
# Or via MCP: run_qa_story(projectId, qaStoryId)
Monitor results in QA Coverage — each card shows pass rate, last run status, and Browserbase replay link.
Step 5: PDCA Auto-Improve
When tests fail repeatedly, the PDCA improver proposes fixes:
# Run immediately
mushi tdd improve
# Runs automatically every 6 hours via pg_cron
Improved tests appear in the pending review queue with source=pdca and a (PDCA v2) suffix.
Automation Modes
| Mode | What happens | Use when |
|---|---|---|
auto |
Tests run immediately after generation | You trust the LLM output, CI-only projects |
review |
Tests queued for human approval | Default — verify before running in schedule |
approve |
Same as review | Explicit approval-first workflow |
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.
- 9d ago First seen · 125 lines · 88 tokens per session scan A e9ad2d8d683a
mushi-test is a skill published in the GitHub repository kensaurus/mushi-mushi (3 stars, last pushed today), licensed MIT. It adds 88 tokens to every session and 882 once invoked, about $0.0004 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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A standard workflow for taking screenshots to check a user interface, using a dedicated review process for different verification modes.
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QA workflow that validates a running application against Gherkin user stories. Use when running /qa or /qa:new-story, writing user stories under docs/user-stories/, decomposing Gherkin scenarios into Playwright and Tidewave validation work, mapping Given/When/Then to a RED/GREEN TDD loop, or filing observed behavior…