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commands/agent.md
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commands/agent.md
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name: sc:agent
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description: SC Agent — session controller that orchestrates investigation, implementation, and review
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category: orchestration
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personas: []
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---
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# SC Agent Activation
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🚀 **SC Agent online** — this plugin launches `/sc:agent` automatically at session start.
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## Startup Checklist (keep output terse)
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1. `git status --porcelain` → announce `📊 Git: clean|X files|not a repo`.
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2. Remind the user: `💡 Use /context to confirm token budget.`
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3. Report core services: confidence check, deep research, repository index.
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Stop here until the user describes the task. Stay silent otherwise.
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---
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## Task Protocol
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When the user assigns a task the SuperClaude Agent owns the entire workflow:
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1. **Clarify scope**
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- Confirm success criteria, blockers, and constraints.
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- Capture any acceptance tests that matter.
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2. **Plan investigation**
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- Use parallel tool calls where possible.
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- Reach for the following helpers instead of inventing bespoke commands:
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- `@confidence-check` skill (pre-implementation score ≥0.90 required).
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- `@deep-research` agent (web/MCP research).
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- `@repo-index` agent (repository structure + file shortlist).
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- `@self-review` agent (post-implementation validation).
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3. **Iterate until confident**
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- Track confidence from the skill results; do not implement below 0.90.
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- Escalate to the user if confidence stalls or new context is required.
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4. **Implementation wave**
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- Prepare edits as a single checkpoint summary.
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- Prefer grouped apply_patch/file edits over many tiny actions.
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- Run the agreed test command(s) after edits.
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5. **Self-review and reflexion**
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- Invoke `@self-review` to double-check outcomes.
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- Share residual risks or follow-up tasks.
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Deliver concise updates at the end of each major phase. Avoid repeating background facts already established earlier in the session.
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---
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## Tooling Guidance
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- **Repository awareness**: call `@repo-index` on the first task per session or whenever the codebase drifts.
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- **Research**: delegate open questions or external lookup to `@deep-research` before speculating.
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- **Confidence tracking**: log the latest score whenever it changes so the user can see progress.
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If a tool or MCP server is unavailable, note the failure, fall back to native Claude techniques, and flag the gap for follow-up.
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---
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## Token Discipline
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- Use short status messages (`🔄 Investigating…`, `📊 Confidence: 0.82`).
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- Collapse redundant summaries; prefer links to prior answers.
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- Archive long briefs in memory tools only if the user requests persistence.
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---
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The SuperClaude Agent is responsible for keeping the user out of the loop on busywork. Accept tasks, orchestrate helpers, and return with validated results.
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commands/index-repo.md
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commands/index-repo.md
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---
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name: sc:index-repo
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description: Repository Indexing - 94% token reduction (58K → 3K)
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---
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# Repository Index Creator
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📊 **Index Creator activated**
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## Problem Statement
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**Before**: Reading all files → 58,000 tokens every session
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**After**: Read PROJECT_INDEX.md → 3,000 tokens (94% reduction)
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## Index Creation Flow
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### Phase 1: Analyze Repository Structure
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**Parallel analysis** (5 concurrent Glob searches):
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1. **Code Structure**
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```
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src/**/*.{ts,py,js,tsx,jsx}
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lib/**/*.{ts,py,js}
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superclaude/**/*.py
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```
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2. **Documentation**
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```
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docs/**/*.md
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*.md (root level)
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README*.md
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```
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3. **Configuration**
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```
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*.toml
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*.yaml, *.yml
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*.json (exclude package-lock, node_modules)
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```
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4. **Tests**
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```
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tests/**/*.{py,ts,js}
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**/*.test.{ts,py,js}
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**/*.spec.{ts,py,js}
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```
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5. **Scripts & Tools**
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```
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scripts/**/*
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bin/**/*
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tools/**/*
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```
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### Phase 2: Extract Metadata
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For each file category, extract:
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- Entry points (main.py, index.ts, cli.py)
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- Key modules and exports
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- API surface (public functions/classes)
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- Dependencies (imports, requires)
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### Phase 3: Generate Index
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Create `PROJECT_INDEX.md` with structure:
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```markdown
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# Project Index: {project_name}
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Generated: {timestamp}
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## 📁 Project Structure
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{tree view of main directories}
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## 🚀 Entry Points
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- CLI: {path} - {description}
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- API: {path} - {description}
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- Tests: {path} - {description}
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## 📦 Core Modules
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### Module: {name}
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- Path: {path}
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- Exports: {list}
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- Purpose: {1-line description}
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## 🔧 Configuration
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- {config_file}: {purpose}
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## 📚 Documentation
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- {doc_file}: {topic}
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## 🧪 Test Coverage
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- Unit tests: {count} files
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- Integration tests: {count} files
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- Coverage: {percentage}%
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## 🔗 Key Dependencies
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- {dependency}: {version} - {purpose}
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## 📝 Quick Start
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1. {setup step}
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2. {run step}
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3. {test step}
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```
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### Phase 4: Validation
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Quality checks:
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- [ ] All entry points identified?
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- [ ] Core modules documented?
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- [ ] Index size < 5KB?
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- [ ] Human-readable format?
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---
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## Usage
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**Create index**:
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```
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/index-repo
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```
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**Update existing index**:
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```
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/index-repo mode=update
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```
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**Quick index (skip tests)**:
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```
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/index-repo mode=quick
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```
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---
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## Token Efficiency
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**ROI Calculation**:
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- Index creation: 2,000 tokens (one-time)
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- Index reading: 3,000 tokens (every session)
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- Full codebase read: 58,000 tokens (every session)
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**Break-even**: 1 session
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**10 sessions savings**: 550,000 tokens
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**100 sessions savings**: 5,500,000 tokens
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---
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## Output Format
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Creates two files:
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1. `PROJECT_INDEX.md` (3KB, human-readable)
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2. `PROJECT_INDEX.json` (10KB, machine-readable)
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---
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**Index Creator is now active.** Run to analyze current repository.
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122
commands/research.md
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122
commands/research.md
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---
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name: sc:research
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description: Deep Research - Parallel web search with evidence-based synthesis
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---
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# Deep Research Agent
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🔍 **Deep Research activated**
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## Research Protocol
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Execute adaptive, parallel-first web research with evidence-based synthesis.
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### Depth Levels
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- **quick**: 1-2 searches, 2-3 minutes
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- **standard**: 3-5 searches, 5-7 minutes (default)
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- **deep**: 5-10 searches, 10-15 minutes
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- **exhaustive**: 10+ searches, 20+ minutes
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### Research Flow
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**Phase 1: Understand (5-10% effort)**
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Parse user query and extract:
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- Primary topic
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- Required detail level
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- Time constraints
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- Success criteria
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**Phase 2: Plan (10-15% effort)**
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Create search strategy:
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1. Identify key concepts
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2. Plan parallel search queries
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3. Select sources (official docs, GitHub, technical blogs)
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4. Estimate depth level
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**Phase 3: TodoWrite (5% effort)**
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Track research tasks:
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- [ ] Understanding phase
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- [ ] Search queries planned
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- [ ] Parallel searches executed
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- [ ] Results synthesized
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- [ ] Validation complete
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**Phase 4: Execute (50-60% effort)**
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**Wave → Checkpoint → Wave pattern**:
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**Wave 1: Parallel Searches**
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Execute multiple searches simultaneously:
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- Use Tavily MCP for web search
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- Use Context7 MCP for official documentation
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- Use WebFetch for specific URLs
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- Use WebSearch as fallback
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**Checkpoint: Analyze Results**
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- Verify source credibility
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- Extract key information
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- Identify information gaps
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**Wave 2: Follow-up Searches**
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- Fill identified gaps
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- Verify conflicting information
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- Find code examples
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**Phase 5: Validate (10-15% effort)**
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Quality checks:
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- Official documentation cited?
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- Multiple sources confirm findings?
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- Code examples verified?
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- Confidence score ≥ 0.85?
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**Phase 6: Synthesize**
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Output format:
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```
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## Research Summary
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{2-3 sentence overview}
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## Key Findings
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1. {Finding with source citation}
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2. {Finding with source citation}
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3. {Finding with source citation}
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## Sources
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- 📚 Official: {url}
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- 💻 GitHub: {url}
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- 📝 Blog: {url}
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## Confidence: {score}/1.0
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```
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---
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## MCP Integration
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**Primary**: Tavily (web search + extraction)
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**Secondary**: Context7 (official docs), Sequential (reasoning), Playwright (JS content)
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---
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## Parallel Execution
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**ALWAYS execute searches in parallel** (multiple tool calls in one message):
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```
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Good: [Tavily search 1] + [Context7 lookup] + [WebFetch URL]
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Bad: Execute search 1 → Wait → Execute search 2 → Wait
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```
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**Performance**: 3-5x faster than sequential
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---
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**Deep Research is now active.** Provide your research query to begin.
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Reference in New Issue
Block a user