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feat(workflow): add project-level state management with intelligent initialization
Implement comprehensive project.json system for tracking project state, completed features, and architecture overview. ## New Features ### 1. /workflow:init Command (NEW) - Independent project initialization command using cli-explore-agent - Deep Scan mode analyzes: technology stack, architecture, key components, metrics - Generates project.json with comprehensive overview field - Supports --regenerate flag to update analysis while preserving features - One-time initialization with intelligent project cognition ### 2. Enhanced session:start - Added Step 0: Check project.json existence before session creation - Auto-calls /workflow:init if project.json missing - Separated project-level vs session-level initialization responsibilities ### 3. Enhanced session:complete - Added Phase 3: Update Project Feature Registry - Extracts feature metadata from IMPL_PLAN.md - Records completed sessions as features in project.json - Includes: title, description, tags, timeline, traceability (archive_path, commit_hash) - Auto-generates feature IDs and tags from implementation plans ### 4. Enhanced status Command - Added --project flag for project overview mode - Displays: technology stack, architecture patterns, key components, metrics - Shows completed features with full traceability - Provides query commands for feature exploration ### 5. Enhanced context-gather - Integrated project.json reading in context-search-agent workflow - Phase 1: Load project.json overview as foundational context - Phase 3: Populate context-package.json from project.json - Prioritizes project.json context for architecture and tech stack - Avoids redundant project analysis on every planning session ## Data Flow project.json (init) → context-gather → context-package.json → task-generation session-complete → project.json (features registry) ## Benefits - Single source of truth for project state - Efficient context reuse across sessions - Complete feature traceability and history - Consistent architectural baseline for all workflows 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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@@ -71,9 +71,10 @@ You are executing as context-search-agent (.claude/agents/context-search-agent.m
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Execute complete context-search-agent workflow for implementation planning:
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### Phase 1: Initialization & Pre-Analysis
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1. **Detection**: Check for existing context-package (early exit if valid)
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2. **Foundation**: Initialize code-index, get project structure, load docs
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3. **Analysis**: Extract keywords, determine scope, classify complexity
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1. **Project State Loading**: Read and parse `.workflow/project.json`. Use its `overview` section as the foundational `project_context`. This is your primary source for architecture, tech stack, and key components. If file doesn't exist, proceed with fresh analysis.
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2. **Detection**: Check for existing context-package (early exit if valid)
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3. **Foundation**: Initialize code-index, get project structure, load docs
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4. **Analysis**: Extract keywords, determine scope, classify complexity based on task description and project state
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### Phase 2: Multi-Source Context Discovery
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Execute all 4 discovery tracks:
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@@ -84,16 +85,17 @@ Execute all 4 discovery tracks:
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### Phase 3: Synthesis, Assessment & Packaging
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1. Apply relevance scoring and build dependency graph
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2. Synthesize 4-source data (archive > docs > code > web)
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3. Integrate brainstorm artifacts (if .brainstorming/ exists, read content)
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4. Perform conflict detection with risk assessment
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5. **Inject historical conflicts** from archive analysis into conflict_detection
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6. Generate and validate context-package.json
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2. **Synthesize 4-source data**: Merge findings from all sources (archive > docs > code > web). **Prioritize the context from `project.json`** for architecture and tech stack unless code analysis reveals it's outdated.
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3. **Populate `project_context`**: Directly use the `overview` from `project.json` to fill the `project_context` section of the output `context-package.json`. Include technology_stack, architecture, key_components, and entry_points.
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4. Integrate brainstorm artifacts (if .brainstorming/ exists, read content)
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5. Perform conflict detection with risk assessment
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6. **Inject historical conflicts** from archive analysis into conflict_detection
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7. Generate and validate context-package.json
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## Output Requirements
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Complete context-package.json with:
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- **metadata**: task_description, keywords, complexity, tech_stack, session_id
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- **project_context**: architecture_patterns, coding_conventions, tech_stack
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- **project_context**: architecture_patterns, coding_conventions, tech_stack (sourced from `project.json` overview)
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- **assets**: {documentation[], source_code[], config[], tests[]} with relevance scores
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- **dependencies**: {internal[], external[]} with dependency graph
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- **brainstorm_artifacts**: {guidance_specification, role_analyses[], synthesis_output} with content
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@@ -139,7 +141,7 @@ Refer to `context-search-agent.md` Phase 3.7 for complete `context-package.json`
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**Key Sections**:
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- **metadata**: Session info, keywords, complexity, tech stack
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- **project_context**: Architecture patterns, conventions, tech stack
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- **project_context**: Architecture patterns, conventions, tech stack (populated from `project.json` overview)
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- **assets**: Categorized files with relevance scores (documentation, source_code, config, tests)
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- **dependencies**: Internal and external dependency graphs
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- **brainstorm_artifacts**: Brainstorm documents with full content (if exists)
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@@ -277,6 +279,7 @@ if (historicalConflicts.length > 0 && currentRisk === "low") {
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## Notes
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- **Detection-first**: Always check for existing package before invoking agent
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- **Project.json integration**: Agent reads `.workflow/project.json` as primary source for project context, avoiding redundant analysis
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- **Agent autonomy**: Agent handles all discovery logic per `.claude/agents/context-search-agent.md`
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- **No redundancy**: This command is a thin orchestrator, all logic in agent
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- **Plan-specific**: Use this for implementation planning; brainstorm mode uses direct agent call
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