Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Gate for HIGH/EPIC tasks that validates plan completeness and architecture compliance before implementation begins
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Validates that a plan is ready for implementation before agents are spawned. Prevents wasted compute from incomplete plans, missing acceptance criteria, or architectural misalignment.
Skill({ skill: 'implementation-readiness' });
Invoke when:
Skip when:
READINESS_GATE=offEvery task in the plan must have:
Pass: All tasks have all required fields. Fail: Tasks missing acceptance criteria or file paths.
Verify that planned changes align with framework conventions:
.claude/skills/<name>/SKILL.md path pattern.claude/agents/<category>/<name>.md path pattern.claude/hooks/<category>/<name>.cjs path patternPass: All planned paths follow conventions. Fail: Non-standard paths or direct writes to creator-managed paths.
Pass: DAG is valid with no cycles. Fail: Circular dependencies or dangling references.
For HIGH/EPIC tasks:
Pass: Risk section present in plan. Fail: Missing risk assessment for HIGH/EPIC task.
Pass: Test strategy present. Fail: No test strategy for implementation tasks.
{
"verdict": "PASS",
"complexity": "HIGH",
"checks": [
{ "name": "plan-completeness", "passed": true, "details": "8/8 tasks complete" },
{
"name": "architecture-compliance",
"passed": true,
"details": "All paths follow conventions"
},
{ "name": "dependency-graph", "passed": true, "details": "DAG valid, critical path: 4 tasks" },
{ "name": "risk-assessment", "passed": true, "details": "Rollback strategy documented" },
{ "name": "test-strategy", "passed": false, "details": "Task 3 missing test file path" }
],
"blockers": ["Task 3 missing test file path"],
"warnings": []
}
This gate integrates into router-decision.md Step 7 as a pre-implementation check:
Skill({ skill: 'implementation-readiness' })Environment variable override: READINESS_GATE=off disables the gate.
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Ensure accessibility in UI components including semantic HTML, ARIA attributes, keyboard navigation, and WCAG 2.2 AA compliance.
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Use when you want to improve response quality through meta-cognitive reasoning. Applies 15+ reasoning methods to reconsider and refine initial outputs.
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N-round opposing-stance debates for trade-off analysis. Assigns pro/con roles to agents, runs structured debate rounds with quality scoring, and produces a moderator synthesis with confidence-rated recommendation. Generalizable to architecture, technology, security, and design decisions.
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Force adversarial code review stance that eliminates confirmation bias — reviewer must find issues or re-analyze
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Creates specialized AI agents on-demand when no existing agent matches a request. Use when the Router cannot find a suitable agent for a task. Enables self-evolution by generating persistent agents.
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LLM-as-judge evaluation framework with 5-dimension rubric (accuracy, groundedness, coherence, completeness, helpfulness) for scoring AI-generated content quality with weighted composite scores and evidence citations
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