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.
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Treat the catalog as a set of working agreements, not a command list. Choose the smallest set of skills that changes the outcome of the task, identify the current lifecycle state, then load the selected skill before acting on its responsibility.
First classify the task state and risk. Use the risk to decide how much of the lifecycle is justified; do not force a waterfall on trivial work.
DISCOVERY → DESIGN → PLANNING → IMPLEMENTATION → TESTING → REVIEW → VERIFICATION → RELEASE → DONE
solution-design, then implementation-planning.plan-execution; add test-driven-development when code behavior changes.root-cause-debugging.requesting-code-review or receiving-code-review as appropriate.completion-verification.frontend-design or ui-ux-review.codebase-orientation.technical-research.safe-migrations.release-engineering; active user impact switches ownership to incident-response.behavior-validation.agent-evaluation.architecture-review; local behavior-preserving cleanup: code-simplification.Add domain skills only when their boundary is present: API contracts, database schema, security risk, performance measurement, browser behavior, testing strategy, documentation decisions, observability, migration, release, architecture, or agent evaluation.
Use three practical levels:
Risk is a reason to deepen the lifecycle, not a license to preload every skill.
If the task may have started before the current context, reconstruct its state from durable evidence before continuing:
git status and git diff;Prefer observed repository state over conversational memory.
New payment feature:
solution-design → implementation-planning → plan-execution + TDD
+ api-and-interface-design + database-design + security-and-hardening
→ requesting-code-review → completion-verification
Broken dashboard flow:
root-cause-debugging + browser-testing + frontend-design
→ TDD regression → completion-verification
Legacy protocol migration:
codebase-orientation + technical-research → safe-migrations
→ implementation-planning → release-engineering + behavior-validation
Production outage after a release:
incident-response + observability-and-instrumentation
→ root-cause-debugging → completion-verification
Do not preload every reference file. Read a linked reference only when the selected task reaches that decision point.
Selection is complete when the primary skill, any justified companion skills, lifecycle state, risk level, and next observable check are explicit. The selection itself is not proof that the work is correct.
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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.
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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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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.
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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.
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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.
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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.
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