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.
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。
thiientv/godmode☆ 972026年8月26日 更新
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.
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。
thiientv/godmode☆ 972026年8月26日 更新
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。
thiientv/godmode☆ 972026年8月26日 更新
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。
thiientv/godmode☆ 972026年8月26日 更新
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。
thiientv/godmode☆ 972026年8月26日 更新
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.
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。
thiientv/godmode☆ 972026年8月26日 更新
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。
thiientv/godmode☆ 972026年8月26日 更新
Creates and manages isolated Git worktrees for parallel agents, risky experiments, or long-running feature work while preserving the user's current checkout. Use before concurrent branch edits or when isolation makes rollback safer. Not for a trivial one-file change that is already isolated.
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。
thiientv/godmode☆ 972026年8月26日 更新
Selects and composes the Godmode skills for a coding task, explains the activation boundary, keeps workflow skills from being skipped when they materially reduce risk, and identifies the task's current engineering lifecycle state. Use when starting a task with Godmode installed, deciding which skill to invoke, recovering a task after context loss, or checking whether a workflow applies. Not a replacement for the selected skill's instructions or for repository-local rules.
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。
thiientv/godmode☆ 972026年8月26日 更新
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。
thiientv/godmode☆ 972026年8月26日 更新