Designs, builds, or refactors user-facing web or application interfaces with deliberate visual direction, typography, color and spacing tokens, content hierarchy, responsive behavior, accessible interaction states, and real rendered-surface verification. Use for pages, components, dashboards, landing pages, design systems, and frontend polish. Not for backend logic, API-only work, or visual claims that cannot be rendered or inspected.
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Designs and executes compatibility-preserving migrations across APIs, schemas, frameworks, dependencies, protocols, storage, and infrastructure with baselines, coexistence, staged cutover, rollback or forward-fix paths, and explicit removal criteria. Use for deprecations, upgrades, data moves, contract changes, and replacing live implementations. Not for a local refactor with no external state or compatibility boundary.
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Simplifies recently changed or explicitly scoped code while preserving observable behavior, error semantics, side effects, ordering, and public contracts. Use for readability cleanup, dead-code removal, reducing nesting, eliminating redundant wrappers, or making an implementation easier to maintain. Not for architecture redesign, new behavior, speculative cleanup, or a refactor without an adequate safety net.
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Designs or reviews relational, document, key-value, graph, or search data models with ownership, invariants, access paths, migrations, consistency, retention, privacy, and recovery behavior. Use for schema changes, new data stores, indexes, migrations, persistence boundaries, or query-driven design. Not for a query-only bug without a model change or for API contract design.
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 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.
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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。
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。
Maps an unfamiliar or large codebase before implementation by locating entry points, ownership, execution paths, conventions, tests, dependencies, change hotspots, and unresolved questions. Use when onboarding to a repository, scoping a cross-cutting change, preparing a handoff or reusable CodeTour, explaining a subsystem, or when the agent is guessing where behavior lives. Not for diagnosing one reproduced failure or designing a new architecture before the current system is understood.
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Verifies a completion, fix, passing, compatibility, release, or readiness claim with fresh task-specific evidence mapped to the actual requirements. Use before saying a change is done, before merge, after review fixes, and at release gates. Not a substitute for diagnosing the cause of a failing check.
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。
Splits a coding task into independent parallel agent workstreams with disjoint write sets, explicit inputs and outputs, dependency ordering, and a merge/review plan. Use when several subtasks can proceed without shared mutable state. Not for tightly coupled edits, one failing root cause, or parallel changes to the same files.
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Writes or updates engineering documentation and architecture decision records from repository facts, explicit assumptions, trade-offs, and verification links. Use for README changes, design docs, runbooks, ADRs, migration notes, and contributor documentation. Not for implementation planning alone or for copying external documentation without provenance.
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。
Writes a detailed, executable implementation plan from an approved design or multi-step requirement, including exact files, interfaces, tests, commands, checkpoints, and rollback considerations. Use before touching code for a substantial feature, migration, refactor, or cross-cutting change. Not for a one-file bounded fix or for executing a plan that already exists.
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Diagnoses and improves measured latency, throughput, memory, CPU, bundle, rendering, query, or resource performance by defining a target, profiling a representative workload, locating the bottleneck, making one change at a time, and comparing before/after evidence. Use for performance work or regressions. Not for guessing optimizations without a reproducible workload or for generic refactoring.
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。
Executes an existing implementation plan task by task, preserving its interfaces and constraints, running focused checks after each slice, and stopping when the repository differs from the plan. Use when a written plan or approved checklist already exists. Not for inventing the plan, debugging an unexplained failure, or broad unscoped cleanup.
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 a GitHub pull request or focused branch diff for correctness, regressions, security, compatibility, test gaps, and maintainability. Use when an implementation needs an independent source-aware review before merge. Produces prioritized findings with evidence and actionable fixes. Not for architecture-only audits, formatting preferences, or processing existing review feedback.
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Processes code review feedback by classifying each finding, reproducing or validating it against the real contract, applying the smallest in-scope fix, and re-running focused proof. Use after comments arrive on a diff, pull request, design, or implementation. Not for requesting a first review or debugging an unrelated failure.
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。
Prepares and controls software releases with risk classification, CI quality gates, artifact provenance, feature flags, staged rollout, measurable promotion and rollback thresholds, post-deploy verification, and cleanup. Use for deployment pipelines, launch readiness, canaries, production rollout, release automation, or rollback planning. Not for merely merging a completed development branch or proving one local change.
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。
Prepares a focused code review request for a branch, commit, pull request, or substantial working-tree diff by defining the review boundary, contract, risk areas, evidence, and questions for an independent reviewer. Use before merge or when another agent needs to review an implementation. Not for processing feedback already received or for claiming runtime correctness.
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。
Threat-models and hardens an application, API, data flow, dependency, or deployment against authentication and authorization flaws, injection, secrets exposure, unsafe deserialization, SSRF, abuse, privacy loss, and supply-chain risk. Use for security review, threat modeling, hardening, or sensitive changes. Not for generic code style review or an unexplained bug without a security hypothesis.
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Executes an approved implementation plan through fresh implementer and reviewer agents for each task, with explicit handoffs, focused tests, and task-by-task integration. Use for multi-task work where independent agent context improves implementation and review quality. Not for a single small edit, an unresolved design, or a failure that still needs root-cause analysis.
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。
Grounds version-sensitive engineering decisions in authoritative current sources by detecting the installed stack, retrieving official documentation or source, reconciling conflicts, and recording citations and confidence. Use for framework APIs, dependency behavior, standards, compatibility, migrations, or technical recommendations that may have changed. Not for stable project-local logic or broad product discovery.
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Implements behavior changes with a test-first red-green-refactor loop: write one meaningful failing test, watch it fail for the intended reason, make the smallest change, then refactor while green. Use for new behavior, bug fixes, refactors with preserved contracts, and regression tests. Not required for disposable prototypes, generated files, or documentation-only edits.
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。
Plans risk-based test coverage for a feature, service, release, or system by mapping user and business risk to test levels, environments, data, failure paths, automation, exploratory checks, and release gates. Use when choosing what to test or how much evidence is enough. Not for writing one test case, applying TDD to a single behavior, or debugging a failing test.
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。