cook-hard

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ask user whether to skip.

Prerequisites: MUST READ .claude/skills/shared/understand-code-first-protocol.md before executing.

• docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models)
• docs/test-specs/ — Test specifications by module (read existing TCs; generate/update test specs via /tdd-spec after implementation)

Skill Variant: Variant of /cook — thorough implementation with maximum verification.

Quick Summary

Goal: Implement features with deep research, comprehensive planning, and maximum quality verification.

Workflow:

1. Research — Deep investigation with multiple researcher subagents
2. Plan — Detailed plan with /plan-hard, user approval required
3. Implement — Execute with full code review and SRE review
4. Verify — Run all tests, review changes, update docs

Key Rules:

• Maximum thoroughness: research → plan → implement → review → test → docs
• User approval required at plan stage
• Break work into todo tasks; add final self-review task

Frontend/UI Context (if applicable)

When this task involves frontend or UI changes, MUST READ .claude/skills/shared/ui-system-context.md and the following docs:

• Component patterns: docs/project-reference/frontend-patterns-reference.md
• Styling/BEM guide: docs/project-reference/scss-styling-guide.md
• Design system tokens: docs/project-reference/design-system/README.md

Ultrathink to plan and implement these tasks with maximum verification:

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

$ARGUMENTS

Mode: HARD - Extra research, detailed planning, mandatory reviews.

Workflow

1. Deep Research Phase

• Launch 2-3 researcher subagents in parallel covering:
  • Technical approach validation
  • Edge cases and failure modes
  • Security implications
  • Performance considerations
• Use /scout-ext for comprehensive codebase analysis
• Generate research reports (max 150 lines each)
• External Memory: Write all research to .ai/workspace/analysis/{task-name}.analysis.md. Re-read ENTIRE file before planning.

Graph Intelligence (MANDATORY when graph.db exists): MUST READ .claude/skills/shared/graph-assisted-investigation-protocol.md. After implementing, run python .claude/scripts/code_graph connections <file> --json on modified files to verify no related files need updates.

Graph-Trace Before Implementation

When graph DB is available, BEFORE writing code, trace to understand the blast radius:

• python .claude/scripts/code_graph trace <file-to-modify> --direction both --json — see what calls this code AND what it triggers
• python .claude/scripts/code_graph trace <file-to-modify> --direction downstream --json — see all downstream consumers
• This prevents breaking implicit dependencies (bus message consumers, event handlers)

2. Comprehensive Planning

• Use planner subagent with all research reports
• Create full plan directory with:
  • plan.md - Overview with risk assessment
  • phase-XX-*.md - Detailed phase files
  • Success criteria for each phase
  • Rollback strategy

3. Verified Implementation

• Implement one phase at a time
• After each phase:
  • Run type-check and compile
  • Run relevant tests
  • Self-review before proceeding

Batch Checkpoint (Large Plans)

For plans with 10+ tasks, execute in batches with human review:

1. Execute batch — Complete next 3 tasks (or user-specified batch size)
2. Report — Show what was implemented, verification output, any concerns
3. Wait — Say "Ready for feedback" and STOP. Do NOT continue automatically.
4. Apply feedback — Incorporate changes, then execute next batch
5. Repeat until all tasks complete

4. Mandatory Testing

• Use tester subagent for full test coverage
• Write tests for:
  • Happy path scenarios
  • Edge cases from research
  • Error handling paths
• NO mocks or fake data allowed
• Repeat until all tests pass

5. Mandatory Code Review

• Use code-reviewer subagent
• Address all critical and major findings
• Re-run tests after fixes
• Repeat until approved

6. Documentation Update

• Use docs-manager to update relevant docs
• Use project-manager to update project status
• Record any architectural decisions

7. Final Report

• Summary of all changes
• Test coverage metrics
• Security considerations addressed
• Unresolved questions (if any)
• Ask user to review and approve

When to Use

• Critical production features
• Security-sensitive changes
• Public API modifications
• Database schema changes
• Cross-service integrations

Quality Gates

Gate	Criteria
Research	2+ researcher reports
Planning	Full plan directory
Tests	All pass, no mocks
Review	0 critical/major findings
Docs	Updated if needed

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IMPORTANT Task Planning Notes (MUST FOLLOW)

• Always plan and break work into many small todo tasks
• Always add a final review todo task to verify work quality and identify fixes/enhancements