docs: add "Do I Need Worktrunk?" self-assessment section
Added decision-making framework to help readers evaluate if they need Worktrunk or should stick with vanilla git/aliases. Key additions (guide/ultimate-guide.md:10762): - 3 quick self-assessment questions (volume, multi-instance, team) - Decision matrix: 4 user profiles (Beginner → Boris scale) - Quick alias alternative for casual users (2 min setup, -79% typing) - Bottom line: "80% should start with vanilla git or alias" - YAGNI principle applied to tooling adoption Philosophy: Prevents premature tool adoption by providing objective criteria. Most readers (2-3 worktrees/week) don't need Worktrunk. Updated: - machine-readable/reference.yaml: Added worktree_tooling_self_assessment: 10762 - CHANGELOG.md: Updated Advanced Worktree Tooling entry with self-assessment details - Total guide additions: +139 lines (self-assessment section) Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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CHANGELOG.md
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CHANGELOG.md
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@ -8,9 +8,15 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
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### Added
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- **Advanced Worktree Tooling section** (`guide/ultimate-guide.md:10661`)
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- **Advanced Worktree Tooling section** (`guide/ultimate-guide.md:10748`)
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- New section "Advanced Tooling for Worktree Management (Optional)" in §9.17 Multi-Instance Workflows
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- Pattern validation: 3 independent teams created worktree wrappers (incident.io, GitHub #1052, Worktrunk)
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- **"Do I Need Worktrunk?" self-assessment** (`guide/ultimate-guide.md:10762`)
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- 3 quick questions (volume, multi-instance, team context)
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- Decision matrix: 4 user profiles (Beginner, Casual, Power user, Boris scale)
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- Quick alias alternative for "Casual user" profile (2 min setup, -79% typing vs vanilla git)
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- Bottom line guidance: "80% of readers should start with vanilla git or alias"
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- Prevents tool adoption without need assessment (YAGNI principle applied to tooling)
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- Benchmark table: Worktrunk vs vanilla git vs custom wrappers (6 operations compared)
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- Option 1: Worktrunk CLI (1.6K stars, Rust, multi-platform, CI/LLM integration, project hooks)
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- Option 2: DIY custom wrappers (bash/fish examples from production teams)
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@ -19,8 +25,8 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/).
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- ROI evidence: incident.io measured 18% improvement (30s) on API generation time with worktree workflow
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- Fact-checked analysis: 4 sources analyzed (Worktrunk GitHub, incident.io blog, Anthropic best practices, GitHub issue #1052)
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- Resource evaluation saved in `claudedocs/resource-evaluations/worktrunk-evaluation.md` (score: 3/5 - pertinent, complément utile)
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- Total additions: ~121 lines
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- **machine-readable/reference.yaml**: Added `advanced_worktree_tooling: 10661` and updated line references for sections after git worktrees
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- Total additions: ~260 lines (121 original + 139 self-assessment)
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- **machine-readable/reference.yaml**: Added `advanced_worktree_tooling: 10748`, `worktree_tooling_self_assessment: 10762`, and updated line references for all sections after worktrees
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- **GSD (Get Shit Done) methodology mention** (`guide/methodologies.md:47-55`)
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- Added to Tier 1: Strategic Orchestration alongside BMAD
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- Meta-prompting 6-phase workflow (Initialize → Discuss → Plan → Execute → Verify → Complete)
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@ -6512,6 +6512,93 @@ grepai search "session creation logic"
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> **Source**: [grepai GitHub](https://github.com/yoanbernabeu/grepai)
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---
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### 🔍 Search Tools Comparison: rg vs grepai vs Serena vs ast-grep
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Now that you've seen individual tools, here's how they compare and when to use each:
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#### Quick Decision Matrix
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| I need to... | Tool | Example |
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|--------------|------|---------|
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| Find exact text | `rg` (Grep) | `rg "authenticate" --type ts` |
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| Find by meaning | `grepai` | `grepai search "user login flow"` |
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| Find function definition | `Serena` | `serena find_symbol --name "login"` |
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| Find structural pattern | `ast-grep` | `ast-grep "async function $F"` |
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| See who calls function | `grepai` | `grepai trace callers "login"` |
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| Get file structure | `Serena` | `serena get_symbols_overview` |
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#### Feature Comparison
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| Feature | rg (ripgrep) | grepai | Serena | ast-grep |
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|---------|--------------|--------|--------|----------|
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| **Search type** | Regex/text | Semantic | Symbol-aware | AST structure |
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| **Speed** | ⚡ ~20ms | 🐢 ~500ms | ⚡ ~100ms | 🕐 ~200ms |
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| **Setup** | ✅ None | ⚠️ Ollama | ⚠️ MCP | ⚠️ npm |
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| **Integration** | ✅ Native | ⚠️ MCP | ⚠️ MCP | ⚠️ Plugin |
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| **Call graph** | ❌ No | ✅ Yes | ❌ No | ❌ No |
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| **Symbol tracking** | ❌ No | ❌ No | ✅ Yes | ❌ No |
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| **Session memory** | ❌ No | ❌ No | ✅ Yes | ❌ No |
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#### When to Use What
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**Use rg (ripgrep)** when:
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- ✅ You know the exact text/pattern
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- ✅ Speed is critical (~20ms)
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- ✅ No setup complexity wanted
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- ❌ Don't use for: conceptual searches, dependency tracing
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**Use grepai** when:
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- ✅ Finding code by meaning/intent
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- ✅ Need to trace function calls (who calls what)
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- ✅ Privacy required (100% local with Ollama)
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- ❌ Don't use for: exact text (use rg instead)
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**Use Serena** when:
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- ✅ Refactoring across multiple files
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- ✅ Need symbol-aware navigation
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- ✅ Persistent context/memory needed
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- ❌ Don't use for: simple text searches
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**Use ast-grep** when:
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- ✅ Large-scale refactoring (>50k lines)
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- ✅ Framework migrations (React, Vue)
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- ✅ Finding structural patterns (async without try/catch)
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- ❌ Don't use for: small projects, simple searches
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#### Combined Workflow Example
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**Task**: Refactor authentication across codebase
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```bash
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# 1. Discover (grepai - semantic)
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grepai search "authentication and session management"
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# → Finds: auth.service.ts, session.middleware.ts
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# 2. Structure (Serena - symbols)
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serena get_symbols_overview --file auth.service.ts
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# → Classes: AuthService, functions: login, logout
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# 3. Dependencies (grepai - call graph)
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grepai trace callers "login"
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# → Called by: UserController, ApiGateway (23 files)
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# 4. Patterns (ast-grep - structure)
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ast-grep "async function login" --without "try { $$$ } catch"
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# → Finds 3 async functions missing error handling
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# 5. Verification (rg - exact)
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rg "validateSession" --type ts -A 5
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# → Verify specific implementation
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```
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**Result**: Complete understanding + safe refactoring in 5 commands
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> **📖 Complete Guide**: See [Search Tools Mastery](../workflows/search-tools-mastery.md) for detailed workflows, real-world scenarios, and advanced combinations.
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---
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### mgrep (Alternative Semantic Search)
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**Purpose**: Natural language semantic search across code, docs, PDFs, and images.
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@ -10672,6 +10759,58 @@ While git worktrees are foundational, **daily productivity** improves with autom
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**Conclusion**: The worktree wrapper pattern is reinvented by power users. Vanilla git is sufficient but verbose for 5-10+ daily worktree operations.
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#### Do I Need Worktrunk? (Self-Assessment)
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**Answer these 3 questions honestly:**
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1. **Volume**: How many worktrees do you create per week?
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- ❌ <5/week → Vanilla git sufficient
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- ⚠️ 5-15/week → Consider lightweight alias
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- ✅ 15+/week → Worktrunk or DIY wrapper justified
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2. **Multi-instance workflow**: Are you running 5+ parallel Claude instances regularly?
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- ❌ No, 1-2 instances → Vanilla git sufficient
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- ⚠️ Sometimes 3-5 instances → Alias or lightweight wrapper
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- ✅ Yes, 5-10+ instances daily → Worktrunk features valuable (CI status, hooks)
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3. **Team context**: Who else uses your worktree workflow?
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- ❌ Solo dev → Alias (zero dependency)
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- ⚠️ Small team, same OS/shell → DIY wrapper (shared script)
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- ✅ Multi-platform team → Worktrunk (Homebrew/Cargo/Winget)
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**Decision matrix:**
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| Profile | Weekly Worktrees | Instances | Team | Recommendation |
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|---------|------------------|-----------|------|----------------|
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| **Beginner** | <5 | 1-2 | Solo | ✅ **Vanilla git** - Learn fundamentals first |
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| **Casual user** | 5-15 | 2-3 | Solo/Small | ⚠️ **Alias** (2 min setup, example below) |
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| **Power user** | 15-30 | 5-10 | Multi-platform | ✅ **Worktrunk** - ROI justified |
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| **Boris scale** | 30+ | 10-15 | Team | ✅ **Worktrunk + orchestrator** |
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**Quick alias alternative (for "Casual user" profile):**
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If you scored ⚠️ (5-15 worktrees/week), try this first before installing Worktrunk:
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```bash
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# Add to ~/.zshrc or ~/.bashrc (2 minutes setup)
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wtc() {
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local branch=$1
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local path="../${PWD##*/}.${branch//\//-}"
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git worktree add -b "$branch" "$path" && cd "$path"
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}
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alias wtl='git worktree list'
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alias wtd='git worktree remove'
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```
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**Usage**: `wtc feature/auth` (18 chars vs 88 chars vanilla git, -79% typing)
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**When to upgrade to Worktrunk:**
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- Alias feels limiting (want CI status, LLM commits, project hooks)
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- Volume increases to 15+ worktrees/week
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- Team adopts multi-instance workflows (need consistent tooling)
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**Bottom line**: Most readers (80%) should start with vanilla git or alias. Worktrunk is for power users managing 5-10+ instances daily where typing friction and CI visibility matter.
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#### Benchmark: Wrapper vs Vanilla Git
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| Operation | Vanilla Git | Worktrunk | Custom Wrapper |
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@ -244,14 +244,15 @@ deep_dive:
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boris_cherny_case_study: 9617
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anthropic_study_metrics: 9721
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git_worktrees_multi_instance: 10634
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advanced_worktree_tooling: 10661
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anthropic_internal_study: 10782
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multi_instance_costs: 10816
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orchestration_frameworks: 10853
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headless_pm_framework: 10865
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multi_instance_implementation: 10891
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multi_instance_monitoring: 10964
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multi_instance_decision_matrix: 11037
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advanced_worktree_tooling: 10748
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worktree_tooling_self_assessment: 10762
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anthropic_internal_study: 10921
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multi_instance_costs: 10955
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orchestration_frameworks: 10992
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headless_pm_framework: 11004
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multi_instance_implementation: 11030
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multi_instance_monitoring: 11103
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multi_instance_decision_matrix: 11176
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# External orchestration systems
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external_orchestrators:
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gas_town:
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@ -479,7 +480,20 @@ mcp:
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ast_grep_when: "structural patterns (>50k lines, migrations, AST rules)"
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ast_grep_not_for: "simple string search, small projects (<10k lines)"
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search_decision_tree: "grep (text) | ast-grep (structure) | Serena (symbols) | grepai (semantic)"
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search_tools_comparison: "guide/ultimate-guide.md:6517"
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search_tools_mastery_workflow: "guide/workflows/search-tools-mastery.md"
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grep_vs_rag_history: "guide/architecture.md:33"
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ripgrep_native: "Grep tool (Claude Code built-in, ~20ms)"
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grepai_semantic: "Semantic search + call graph (Ollama-based, ~500ms)"
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grepai_benchmark:
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source: "https://yoandev.co/grepai-benchmark"
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guide_section: "guide/workflows/search-tools-mastery.md:240"
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date: "2026-01-20"
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summary: "-55% tool calls, -97% tokens vs grep (Excalidraw 155k TS)"
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caveat: "Benchmark by tool maintainer, single-project validation"
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serena_symbols: "Symbol-aware + session memory (~100ms)"
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astgrep_structural: "AST patterns for large refactoring (~200ms)"
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search_combined_workflow: "guide/workflows/search-tools-mastery.md:205"
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check: "/mcp"
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config: ".claude/mcp.json or ~/.claude.json"
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tool_search: "lazy loading MCP tools (v2.1.7+) - 85% token reduction - auto:N threshold config"
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