Ouroboros test plan author
Skill secondorderai/ouroboros/.agents/skills/ouroboros-test-plan-author
Create intent-based Ouroboros desktop E2E Markdown test plans from a high-level goal, feature, module, bug, PRD, ticket, or UI area. Use when asked to generate, draft, author, improve, or expand files under test-plan/ for Agent Browser desktop testing.From its SKILL.md
npx -y skills add secondorderai/ouroboros --skill ouroboros-test-plan-authorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
2 things to look at
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
- runs commandsInstructs the agent to run 2 commands, including `bun run test:intent:e2e -- test-plan/<name>.md --dry-run` and 1 more.
SKILL.md
3.1 KB, 638 tokens by cl100k_base, as published. Nobody here has run it
Ouroboros Test Plan Author
Use this skill to turn a high-level feature, module, bug, or goal into one or
more executable Markdown charters under test-plan/.
Workflow
- Ground the plan in the repo before writing:
- Search relevant renderer components, stores, protocol types, existing E2E specs, and existing
test-plan/*.md. - Prefer current labels, UI names, domain language, and mock data patterns from the codebase.
- Search relevant renderer components, stores, protocol types, existing E2E specs, and existing
- Decide plan granularity:
- One plan for one user-centered workflow.
- Split broad modules into multiple charters only when the workflows have different setup, risks, or pass/fail oracles.
- Write the Markdown plan in
test-plan/<kebab-case-name>.md. - Keep the plan intent-based:
- Describe what the user is trying to accomplish.
- Avoid brittle CSS selectors, implementation details, or Playwright-style commands.
- Include enough observable outcomes for an Agent Browser runner to judge pass/fail.
- If the plan needs mock data, name the required scenario shape in plain language.
- Do not invent large fixture JSON unless the user explicitly asks for it.
- State when missing mock data should produce
INCONCLUSIVE.
Required Plan Shape
# Title Case Plan Name
## Mission
One or two sentences describing the user workflow and why it matters.
## Priority / Tags
p0, smoke, desktop, feature-name
## Initial State
- Fresh Electron user data directory, unless persistence is the subject.
- Mock CLI scenario requirements.
- Any required workspace, dialog response, policy response, or seeded data.
## Intent Steps
1. User-centered action.
2. Observable action or navigation.
3. Verification step.
## Expected Outcomes
- Concrete visible UI state.
- Relevant persisted/logged behavior when observable through test logs.
- Recovery or closing behavior where appropriate.
- No uncaught renderer error.
## Evidence Required
- Screenshot names or moments worth capturing.
- Console and page error output.
- Any mock CLI log evidence worth checking.
Quality Bar
- Use
p0for release-blocking smoke flows; usep1for important surfaces; usep2for edge cases and exploratory coverage. - Make each expected outcome externally observable from the running app, screenshots, logs, or console output.
- Prefer stable human-facing terms: accessible labels, menu names, panel titles, visible messages.
- Include negative or recovery checks for risky flows: cancellation, empty states, disabled actions, denied approvals, failed config, or restart.
- Keep each plan short enough for an agent to execute in one focused run.
Output
After writing or updating a plan, report:
- The file path.
- The workflow covered.
- Any mock scenario assumptions.
- The exact command to dry-run and execute it:
bun run test:intent:e2e -- test-plan/<name>.md --dry-runbun run test:intent:e2e -- test-plan/<name>.md
What ships with it: 1 file
264 B alongside SKILL.md
agents/
- openai.yaml264 B