Explores ambiguous product or engineering intent before implementation, clarifies users, constraints, alternatives, risks, and acceptance criteria, and turns the result into an approved design direction. Use for a new feature, subsystem, creative UI, architecture change, or unclear request. Not for an already-scoped bug fix, an existing implementation plan, or a narrow code review.
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。
Make the problem concrete before choosing the solution. The goal is shared understanding, not a long ceremony.
When uncertain, choose the heavier path until discovery proves otherwise.
Use discovery-questions.md when the brief has unclear goals or competing stakeholders.
For architectural work, save a concise design under the repository's normal docs location. Include:
Problem and users
Outcome and non-goals
Constraints and assumptions
Options considered and recommendation
Interfaces and data affected
Failure modes and rollback
Acceptance evidence
Open decisions
Do not start implementation while a decision that materially changes the public behavior, data model, or safety boundary is unresolved.
implementation-planning.root-cause-debugging.Solution design is complete when the outcome, scope, constraints, acceptance evidence, risks, and next decision are explicit. A polished idea without a testable outcome is not a completed design.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Designs and runs reproducible evaluations for AI agents, prompts, tools, skills, and model-backed workflows using realistic datasets, isolated baselines, objective assertions, rubric grading, trajectory analysis, cost/latency tracking, and regression comparison. Use when measuring agent quality, optimizing skill triggering, comparing prompts or models, or gating an AI feature release. Not for ordinary deterministic unit tests.
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。
Designs or reviews HTTP, REST, GraphQL, RPC, CLI, webhook, event, and service interfaces with explicit inputs, outputs, errors, compatibility, idempotency, pagination, authentication, versioning, and observability. Use when introducing or changing an API or cross-component contract. Not for internal implementation details with no boundary or for debugging one API failure; use root-cause-debugging there.
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。
Reviews an existing codebase for structural friction, unclear ownership, leaky or shallow interfaces, excessive coupling, misplaced state, poor testability, and risky dependency direction, then prioritizes evidence-backed improvement candidates. Use for architecture audits, modularization, modernization, or recurring cross-cutting change pain. Not for designing one new interface, simplifying a local function, or fixing a reproduced bug.
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。
Validates a running application, CLI, API, service, or generated artifact as a user or operator against a prewritten observable behavior contract while remaining source-blind. Use for acceptance checks, runtime proof, anti-fake probes, release smoke tests, or an independent companion to code review. Not for source-quality findings, root-cause diagnosis, or visual design judgment outside the contract.
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。
Closes a completed development branch by checking the final diff and proof, presenting merge, pull-request, keep, or discard options, and cleaning up only after the user or repository workflow chooses a path. Use when feature work is complete and the branch must be integrated or retired. Not for claiming a feature is complete before verification.
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。
Tests a real web user flow with a browser by asserting semantic behavior, network and loading states, keyboard access, responsive layouts, and stable visual evidence. Use for browser bugs, end-to-end UI behavior, responsive or accessibility checks, and screenshot baselines. Not for static source review without a browser or for backend-only tests.
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。