Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Use when completing implementation, fixing bugs, refactoring code, or any time you need to verify the test suite passes. Also use when tests fail and you hear "pre-existing" or "not my changes" — enforces strict code ownership. Ensures MECE coverage (no overlap, no gaps) and that ALL test categories including E2E are executed.
日本語の概要は準備中です。原文の説明を表示しています。
実行スコア 未検証
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
Act as a test execution and code ownership enforcer. Discover tests, run them, and ensure the codebase is left in a passing state — no exceptions, no excuses.
Test Target: $ARGUMENTS
The standard: all tests pass, every test produces signal, every behavior with a real failure mode has coverage. A green suite full of noise tests (tautology, framework re-verification, identity-mapped mocks, call-sequence-only assertions) is a regression, not a deliverable.
If a test fails, there are three acceptable responses:
Tests must be Mutually Exclusive, Collectively Exhaustive, Signal-bearing (MECES):
When evaluating or writing tests, flag violations:
user.test.ts and user.integration.test.ts — consolidate to unit test."service.ts:42 has no test coverage — add a test."test_keys.py asserts format_key(x) == f'prefix:{x}' against an implementation returning f'prefix:{x}' — delete; the caller's test covers any breakage." See reference/test-design-rules.md.Failure { status: FAIL category: YOUR_CHANGE | OUTDATED_TEST | TEST_BUG | NOISE_TEST | MISSING_DEP | ENVIRONMENT | CODE_BUG test: string // test name location: string // file:line error: string // one-line error message action: string // what you will do to fix it (fix / delete / escalate) }
State { target = $ARGUMENTS runner: string // discovered test runner command: string // exact test command mode: Standard | Agent Team | Dynamic Workflow baseline?: string failures: Failure[] costSignals?: { // populated during discovery when available runtimePerCategory: map<string, duration> mockDensity: map<file, count> // matches of mock/Mock/stub/spy per test file testToSourceRatio: map<dir, float> // test_LOC / source_LOC per directory } }
Always:
Never:
scenarios/ directories — those are holdout evaluation sets managed by the implement skill's factory loop, not part of the test suite.Read reference/discovery-protocol.md.
match (target) { "all" | empty => full suite discovery file path => targeted discovery (still identify runner first) "baseline" => discovery + capture baseline only, no fixes "audit" => discovery + cost signals + design audit only, do not run tests }
Read reference/output-format.md and present discovery results accordingly.
If target == "audit": skip mode selection and proceed to step 7 (Audit).
Ask the user to choose: Standard (default) — sequential test execution, discover-run-fix-verify Agent Team — parallel runners per test category (unit, integration, E2E, quality) Dynamic Workflow — one inline workflow script runs every category in parallel and categorizes the failures; fixes stay in this session
Recommend Agent Team when: 3+ test categories | full suite > 2 min | failures span multiple modules | both lint/typecheck AND test failures to fix Recommend Dynamic Workflow instead when 3+ test categories or the full suite > 2 min, but the failures can be fixed one at a time in this session.
Run ALL test commands discovered in step 1 — not just the primary suite. If unit tests use vitest and E2E tests use playwright, both commands must run. Record passing, failing, skipped counts per category.
Read reference/output-format.md and present baseline accordingly.
match (baseline) { all passing => continue failures => flag per Ownership Mandate — you still own these E2E skipped => escalate why — never silently omit }
match (mode) { Standard => run each discovered test command sequentially (unit → integration → E2E), capture verbose output, parse results Agent Team => create team, spawn one runner per test category, assign tasks — E2E gets its own dedicated runner Dynamic Workflow => run one dynamic workflow: one runner agent per test category in parallel (E2E gets its own), each returning verbatim output and its failures categorized per reference/failure-investigation.md; no agent in it edits code — fix the returned failures below }
For Dynamic Workflow, these instructions are the opt-in: call the Workflow tool directly with an inline script. Do not load the workflow-authoring reference or assemble the script through shell commands first — runs that detour through either stall before launching. Choose model and effort per stage from what the stage does. Mechanical stages — running a command, gathering or quoting sources, mapping text into a fixed schema — can run on a smaller, faster model at lower effort. Analysis, writing, and judging another agent's work need the strongest model. A judging stage never runs on a weaker model than the stage it judges. When unsure, omit model so the stage inherits the session model.
E2E Execution Checklist:
npx playwright install if needed)Read reference/output-format.md and present execution results accordingly.
match (results) { all passing => skip to step 5 failures => proceed to fix failures E2E not run => THIS IS A FAILURE — go back and run them or escalate }
For each failure:
For each quality command discovered in step 1:
Read reference/output-format.md and present final report accordingly.
Include in the final report:
Apply reference/test-design-rules.md and reference/discovery-protocol.md cost-signal capture. Do NOT run tests. Produce an Audit Report (see reference/output-format.md) listing:
mock.assert_called_with(...) with no outcome checkAudit mode never modifies code. It produces a report the user can act on with /start:test all (after deletions) or with a separate refactor session.
Called by other workflow skills:
/start:implement — verify implementation didn't break tests/start:refactor — verify refactoring preserved behavior/start:debug — verify fix resolved the issue without regressions/start:review — ensure clean test suite before reviewWhen called by another skill, skip step 1 if test infrastructure was already identified.
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Context enrichment for agentic AI application development using LangChain, Vercel AI SDK, and assistant-ui. Use when building AI agents, chat interfaces, tool-calling pipelines, RAG systems, or multi-step AI workflows.
日本語の概要は準備中です。原文の説明を表示しています。
Deep-research analysis of a codebase, a topic, or both. Clarifies the question, agrees the research angles with you, then runs a dynamic workflow that gathers cited claims per angle, merges duplicates, has independent skeptics try to refute every claim, and writes one cited report from the claims that survived. Use for "how does X work", "map the Y flow", "research Z", or any mechanism-level question that must be evidence-backed.
日本語の概要は準備中です。原文の説明を表示しています。
REST and GraphQL API design patterns, OpenAPI/Swagger specifications, versioning strategies, and authentication patterns. Use when designing APIs, reviewing API contracts, evaluating API technologies, or implementing API endpoints.
日本語の概要は準備中です。原文の説明を表示しています。
System architecture patterns including monolith, microservices, event-driven, and serverless, with C4 modeling, scalability strategies, and technology selection criteria. Use when designing system architectures, evaluating patterns, or planning scalability.
日本語の概要は準備中です。原文の説明を表示しています。
Consolidate a completed specification into a single archived record and remove its working directory. Use as the final stage after implementation — distills requirements + solution into .start/archive/[NNN]-[name].md and deletes the .start/specs/[NNN]-[name]/ directory.
日本語の概要は準備中です。原文の説明を表示しています。
Required first step before any creative work — creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements, and design before implementation.
日本語の概要は準備中です。原文の説明を表示しています。