Review whether game design requirements are covered by documented architecture decisions. Identify missing coverage, conflicting decisions, and engine compatibility concerns, with an optional matrix linking requirements to development stories and tests.
Traceability matrix mapping GDD requirements to ADRs. Finds gaps, cross-ADR conflicts, engine compatibility. PASS/CONCERNS/NOT ASSESSED/FAIL.
Review the instructions the agent will receive before you install.
!bash "${CLAUDE_SKILL_DIR}/../../hooks/yaml-helper.sh" resolve_config --keys automation,workflow
The architecture review validates that the complete body of architectural decisions covers all game design requirements, is internally consistent, and correctly targets the project's pinned engine version. It is the quality gate between Technical Setup and Pre-Production.
Argument modes:
full: Full review — all phasescoverage: Traceability only — which GDD requirements have no ADRconsistency: Cross-ADR conflict detection onlyengine: Engine compatibility audit onlysingle-gdd [path]: Review architecture coverage for one specific GDDrtm: Requirements Traceability Matrix — extends the standard matrix
to include story file paths and test file paths; outputs
docs/architecture/requirements-traceability.md with the full
GDD requirement → ADR → Story → Test chain. Use in Production phase when
stories and tests exist.Every AskUserQuestion call follows .claude/docs/automation-modes.md
(collaborative asks always · guided major-only · autonomous logs and proceeds;
automation_always_ask categories always prompt).
workflow (see .claude/docs/workflow-modes.md):
full — full traceability matrix across all GDDs and all ADRs.standard — reduced scope: architecture doc + critical ADRs only.minimal — not applicable (no architecture doc required).Read references/1-load.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/2-extract-requirements.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/3-traceability.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/4-conflicts.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/5-engine.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/6-document-coverage.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/7-report.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/8-write.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
Read references/9-handoff.md now and follow it — this phase's steps are in that file, not here. Read it again if the conversation was compacted or resumed during this phase.
First, verify the artifact. If the return contract named a path, check the path exists before treating the phase as done — a named artifact that is not on disk is a failed phase, however fluent the response reads. An agent can burn a full phase and return a plausible preamble having written nothing, which is neither BLOCKED nor an error nor "fails to complete", so the trigger below never fires. Resume it naming the unmet contract; the context is usually still there.
If any spawned agent returns BLOCKED, errors, or fails to complete: surface it
immediately, don't proceed past a dependency it blocks, and always produce a
partial report (retry scope here = fewer GDDs / single-system). Full procedure:
.claude/docs/error-recovery-protocol.md.
Applies in collaborative mode (the default). For guided and
autonomous modes, see .claude/docs/automation-modes.md — the rules below
describe what collaborative mode requires, not universal behavior.
AskUserQuestion for write approvals — plain text "May I?" is not
sufficient. Use the structured tool with labeled options [A]/[B]/[C] so the
user can choose between "write now", "show full draft first", and "not yet".
Multi-file changesets must list every file and what changes, then ask once
with grouped options — not a separate plain-text question per file.No reviews yet. Tell others what you thought.
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Audit an existing project's design documents and supporting files to check whether their formats work with the template's skills. Get a numbered migration plan that prioritizes gaps and required changes, rather than simply listing what exists.
Document a technical decision in an architecture decision record, or ADR. Capture its context, alternatives, and consequences, assign a record number, and distinguish a proposed decision from an accepted one so dependent work reflects its actual status.
Create a game's art direction document, defining its visual rules, mood, shapes, colors, and production standards. Review and approve sections individually, with guidance that connects character, environment, and interface design to the game's concept and technical constraints.
Audit game asset files for naming rules, size limits, formats, and broken references. Receive a report of measured violations and suggested fixes, with clear explanations of checks that lack data or cannot be assessed for the engine.
Turn game design documents and character profiles into asset specifications and image generation prompts. Define appearance, dimensions, file formats, and naming rules, then maintain an asset list that tracks progress and identifies shared assets.
Review game data and formulas for combat, economy, progression, or loot. Compare values with documented targets, identify dominant strategies and broken resource loops, and produce prioritized adjustment recommendations while clearly marking areas that lack enough data.