Verify tasks are truly independent (no shared files, no data flow between them)
Match each task to the correct specialized agent
Create complete briefs with scope, files, output, and success criteria
Launch ALL agents in a SINGLE message with multiple Agent tool calls

Launching agents without verification = conflicts, wasted work, merge hell

This is not optional. Parallel execution requires independence verification.

Run Parallel Agents Feature Build

MANDATORY FIRST RESPONSE PROTOCOL

Before launching ANY parallel agents, you MUST complete this checklist:

☐ Count tasks — are there 3+ independent tasks?
☐ Check dependencies — do any tasks depend on others?
☐ Check file overlap — do tasks modify the same files?
☐ Match agents — assign correct agent type per task
☐ Prepare briefs — scope, files, output, success criteria for each
☐ Announce to user — "Launching N agents in parallel for [tasks]"

Launching agents WITHOUT completing this checklist = conflicts and failures.

Overview

Automatically detect opportunities for parallel execution and orchestrate multiple specialized agents working concurrently on independent features, modules, or investigations. Match each task to the appropriate domain expert and coordinate their work to deliver faster results without sacrificing quality.

When to Use This Skill

Use this skill automatically when:

Task List Indicators:

The task list contains 3 or more independent tasks or phases
Receiving a large plan with multiple unrelated features
Tasks are clearly scoped and don't overlap
Each task can be understood without context from others
No shared state or cross-dependencies between tasks

User Triggers:

"Build in parallel"
"Split this work across agents"
"Use multiple agents for this"
"Speed this up with parallel execution"

Common Scenarios:

Building independent features or endpoints (e.g., wishlist API, checkout flow, user dashboard)
Implementing multiple UI components or microservices simultaneously
Generating documentation or schema files for several modules
Analyzing multiple code files for specific issues
Debugging failures in isolated subsystems
Processing multiple data files or resources

When NOT to Use This Skill

Do NOT use parallel agents when:

Dependencies Exist:

Tasks have sequential dependencies (Task B needs Task A's output)
Shared state, data, or ownership between tasks
The sequence of execution affects the outcome
Agents would interfere with each other's work

Problem Not Decomposed:

The problem isn't yet broken into independent units
Need to understand full system state first
Related failures where fixing one might fix others
Careful coordination or debugging across layers is required

Single Cohesive Task:

Working on a single integrated feature
Refactoring that touches multiple interconnected parts
Tasks that require constant communication between components

Core Workflow

Step 1: Analyze the Task List or Request

Examine the current task list or user request to identify:

Number of independent work streams - Are there 3+ separate features/tasks?
Dependencies - Can each task be completed without waiting for others?
Shared state - Do tasks modify the same files or data structures?
Scope clarity - Is each task clearly defined with known requirements?

If all conditions for parallelization are met, proceed to Step 2.

Step 2: Match Features to Specialized Agents

For each independent task, determine the best agent type based on:

Technology Stack Detection:

Laravel backend → laravel-senior-engineer
Next.js frontend or full-stack → nextjs-senior-engineer
React + Vite + Tailwind frontends → react-vite-tailwind-engineer
Express.js APIs → express-senior-engineer
Node.js CLI tools → nodejs-cli-senior-engineer
Python backend, Django, data pipelines → python-senior-engineer
FastAPI specifically, async DB, JWT auth → fastapi-senior-engineer
Go backend, services → go-senior-engineer
Go CLI tools → go-cli-senior-engineer
iOS/macOS, Swift, SwiftUI → ios-macos-senior-engineer
Expo React Native mobile → expo-react-native-engineer
AWS infrastructure, CDK → devops-aws-senior-engineer
Docker, containers → devops-docker-senior-engineer
General tasks (exploration, research) → general-purpose

File Pattern Analysis:

*.php + /app/ + /routes/ → Laravel
*.tsx + /app/ or /pages/ + next.config.* → Next.js
*.tsx + vite.config.* + tailwind.config.* → React/Vite/Tailwind
*.ts + express imports → Express
*.ts + commander/inquirer imports → Node CLI
*.py + fastapi imports → FastAPI
*.py + django/flask/general → Python
*.go + go.mod → Go
*.swift + Package.swift or *.xcodeproj → iOS/macOS
*.tsx + app.json (Expo) → Expo React Native
Dockerfile + docker-compose.* → Docker
CDK, CloudFormation, Terraform → AWS DevOps

Step 3: Prepare Agent Briefs

For each agent, create a clear, focused brief containing:

Required Elements:

Scope of work - Exactly what to build/analyze/fix
Expected output - What deliverables to produce
Context - Relevant file paths, existing patterns, constraints
Success criteria - How to verify completion

Brief Template:

Build [feature name]:
- Scope: [specific feature boundaries]
- Files: [relevant paths or patterns]
- Requirements: [bullet points]
- Output: [expected deliverables]
- Patterns: [existing code patterns to follow]

Step 4: Launch Agents in Parallel

Execute all agents simultaneously using a single message with multiple Agent tool calls:

Use the Agent tool with these parameters for each task:
- prompt: Complete brief (scope, files, output, success criteria)
- subagent_type: Matched agent from the Agent Table
- isolation: "worktree" (MANDATORY for parallel file modifications)
- run_in_background: true (for concurrent execution)
- model: "opus" for complex tasks, "sonnet" for straightforward tasks

Critical Requirements:

Send ALL Agent tool calls in ONE message (this is what makes them parallel)
Use isolation: "worktree" — without this, parallel agents clobber each other's files
Use run_in_background: true — without this, agents run sequentially
Each agent gets its complete brief in the prompt parameter
No placeholder values — all parameters must be complete
For web browsing tasks, use browse --session <agent-name> for session isolation

Step 5: Monitor and Aggregate Results

After agents complete:

Collect outputs from each agent
Verify deliverables match expected outputs
Check for conflicts (e.g., overlapping file changes)
Merge results into a coherent summary
Report to user with consolidated findings

Aggregation Template:

Parallel execution complete. Results:

**[Feature 1]** (via [agent-type])
- Status: [completed/blocked/partial]
- Delivered: [summary]
- Files modified: [list]

**[Feature 2]** (via [agent-type])
- Status: [completed/blocked/partial]
- Delivered: [summary]
- Files modified: [list]

**Overall:** [X/Y features completed, any conflicts, next steps]

Step 6: Verification (MANDATORY)

After aggregating results, verify the parallel execution was successful:

Check 1: All Agents Completed

Every launched agent returned a result
No agents timed out or crashed

Check 2: No File Conflicts

No two agents modified the same file
If conflicts exist, they are resolved

Check 3: Deliverables Match Briefs

Each agent delivered what was specified
Output matches expected format

Check 4: No Integration Issues

Features work together (if they interact)
No broken imports or references

Check 5: User Informed

Completion announced with summary
Any issues or partial results documented

Gate: Do NOT mark task complete until all 5 checks pass.

Example Scenarios

Example A: Feature Build

User Says: "Build the wishlist API, checkout summary, and user dashboard in parallel."

Execution:

Detect three separate feature scopes
Match agents:
- Wishlist API → laravel-senior-engineer (backend)
- Checkout summary → nextjs-senior-engineer (frontend)
- User dashboard → nextjs-senior-engineer (frontend/UI)
Launch all three in a single message with Agent tool
Aggregate results into merged summary

Output:

Built 3 features in parallel:
- Wishlist API: Complete (app/Http/Controllers/WishlistController.php, routes/api.php)
- Checkout summary: Complete (app/checkout/summary/page.tsx)
- User dashboard: Complete (app/dashboard/page.tsx)

Example B: Debug Parallel Subsystems

User Says: "Run parallel agents to debug these failing tests."

Execution:

Cluster failures by subsystem:
- Laravel backend tests
- Next.js frontend tests
- Node.js API tests
Spawn agents:
- laravel-senior-engineer for Laravel failures
- nextjs-senior-engineer for Next.js failures
- express-senior-engineer for Node API failures
Let each diagnose and fix independently
Gather results, merge patches, re-run tests
Output consolidated fix report

Example C: Code Analysis

User Says: "Analyze these 5 code files in parallel for performance bottlenecks."

Execution:

Split files across appropriate agents based on file type
Run analysis concurrently (each agent gets 1-2 files)
Merge findings into summarized report with:
- File-by-file breakdown
- Common patterns across files
- Prioritized recommendations

Agent Type Reference

Quick reference for matching tasks to agents:

Agent Type	Best For	Key Indicators
`laravel-senior-engineer`	Laravel backends, APIs, Eloquent models	`*.php`, `/app/`, Eloquent, Artisan
`nextjs-senior-engineer`	Next.js apps, React Server Components, App Router	`.tsx`, `/app/`, `/pages/`, `next.config.`
`react-vite-tailwind-engineer`	React + Vite + Tailwind TypeScript frontends	`.tsx`, `vite.config.`, `tailwind.config.*`
`express-senior-engineer`	Express.js APIs, middleware, REST endpoints	`.js/.ts`, `express` imports
`nodejs-cli-senior-engineer`	Node.js CLI tools, commander.js, inquirer	`commander`, `inquirer`, `ora`, CLI patterns
`python-senior-engineer`	Python backends, Django, data pipelines	`*.py`, `requirements.txt`, `pyproject.toml`
`fastapi-senior-engineer`	FastAPI, async DB, JWT auth	`*.py`, `fastapi` imports, `uvicorn`
`go-senior-engineer`	Go backends, services, APIs	`*.go`, `go.mod`, `go.sum`
`go-cli-senior-engineer`	Go CLI tools, cobra, viper	`*.go`, `cobra` imports, CLI patterns
`ios-macos-senior-engineer`	Swift, SwiftUI, Xcode, SPM, StoreKit	`.swift`, `Package.swift`, `.xcodeproj`
`expo-react-native-engineer`	Expo mobile apps, cross-platform	`*.tsx`, `app.json`, Expo modules
`devops-aws-senior-engineer`	AWS infrastructure, CDK, CloudFormation	CDK, CloudFormation, Terraform, AWS
`devops-docker-senior-engineer`	Docker, Docker Compose, containerization	`Dockerfile`, `docker-compose.*`
`general-purpose`	Exploration, research, general tasks	Non-framework-specific work

See references/agent_matching_logic.md for detailed matching rules and edge cases.

Best Practices

Scoping Tasks Effectively

Good Task Scopes:

"Build user authentication endpoint with JWT"
"Create product listing page with filters"
"Implement cart total calculation service"

Poor Task Scopes:

"Build the entire checkout flow" (too broad, likely has dependencies)
"Fix the app" (undefined, not decomposed)
"Refactor database layer" (touches too many interconnected parts)

Handling Conflicts

If agents modify overlapping files:

Review changes from each agent
Identify conflicts (same lines modified)
Merge intelligently or ask user for guidance
Re-test affected areas

Communication Pattern

Always inform the user BEFORE launching parallel agents:

I've identified 3 independent features that can be built in parallel:
1. [Feature 1] - using [agent-type]
2. [Feature 2] - using [agent-type]
3. [Feature 3] - using [agent-type]

Launching agents now...

Handling Partial Success

If an agent fails or gets blocked:

Continue with successful agents
Report partial results
Provide clear next steps for blocked work
Don't retry automatically without user input

Quality Checklist (Must Score 8/10)

Score yourself honestly before marking parallel execution complete:

Independence Verification (0-2 points)

0 points: Launched without checking dependencies
1 point: Checked some dependencies
2 points: Full dependency check (files, data flow, state)

Agent Matching (0-2 points)

0 points: Wrong agents for tasks
1 point: Agents assigned without justification
2 points: Each task matched to correct agent with indicators

Brief Quality (0-2 points)

0 points: No briefs or generic briefs
1 point: Partial briefs (missing fields)
2 points: Complete briefs with scope, files, output, success criteria

Execution Correctness (0-2 points)

0 points: Agents launched sequentially
1 point: Parallel launch but incomplete briefs
2 points: Single message with all Agent tool calls, complete briefs

Result Aggregation (0-2 points)

0 points: No summary provided
1 point: Partial summary
2 points: Complete summary with status, deliverables, conflicts, next steps

Minimum passing score: 8/10

Common Rationalizations (All Wrong)

These are excuses. Don't fall for them:

"These tasks look independent" → STILL check for file overlap
"I know the right agents" → STILL document the matching rationale
"Briefs are obvious" → STILL write complete scope, files, output, success criteria
"Sequential is safer" → If tasks are independent, parallel is FASTER with no downside
"I'll merge conflicts later" → Check for conflicts BEFORE launching
"One message is too long" → ALL Agent tool calls MUST be in one message
"The user just wants it done" → Correct execution = faster completion
"Two tasks don't need parallel agents" → Correct, need 3+ tasks

Failure Modes

Failure Mode 1: Launching Dependent Tasks in Parallel

Symptom: Agents fail or produce conflicting output because Task B needed Task A's result Fix: Run dependency checks. If Output(A) ∈ Input(B), execute sequentially.

Failure Mode 2: Wrong Agent Assignment

Symptom: Laravel work done by nextjs-senior-engineer, poor results Fix: Use technology detection patterns. Match *.php → Laravel agent.

Failure Mode 3: Sequential Launch Instead of Parallel

Symptom: Sent multiple messages with Agent tool calls, agents ran one at a time Fix: ALL Agent tool calls in a SINGLE message. This is critical for parallel execution.

Failure Mode 4: Incomplete Briefs

Symptom: Agents ask clarifying questions or deliver wrong output Fix: Every brief must have Scope, Files, Output, Success criteria. No placeholders.

Failure Mode 5: No Conflict Check After Completion

Symptom: Agents modified same files, changes overwrite each other Fix: After aggregation, check file overlap. If conflicts, merge intelligently.

Quick Workflow Summary

STEP 1: ANALYZE
├── Count tasks (need 3+)
├── Check dependencies
├── Check file overlap
└── Gate: Tasks are independent

STEP 2: MATCH AGENTS
├── Identify technology per task
├── Assign correct agent type
└── Document matching rationale

STEP 3: PREPARE BRIEFS
├── Scope, Files, Output, Success criteria
└── No placeholders allowed

STEP 4: LAUNCH PARALLEL
├── Single message with ALL Agent tool calls
├── Do NOT wait between launches
└── Gate: All agents launched

STEP 5: AGGREGATE RESULTS
├── Collect outputs
├── Check for conflicts
└── Merge into summary

STEP 6: VERIFICATION
├── All agents completed
├── No file conflicts
├── Deliverables match briefs
└── Gate: All 5 checks pass

Completion Announcement

When parallel execution is complete, announce:

Parallel execution complete.

**Quality Score: X/10**
- Independence Verification: X/2
- Agent Matching: X/2
- Brief Quality: X/2
- Execution Correctness: X/2
- Result Aggregation: X/2

**Results:**
- Features completed: X/Y
- Agents used: [list]
- Conflicts: [none/resolved/pending]

**Summary:**
[Brief description of what was delivered]

**Next steps:**
[Any remaining work or follow-up needed]

Integration with Other Skills

The run-parallel-agents-feature-build skill integrates with:

plan-to-task-list-with-dag — Use to generate a structured plan, then this skill to execute it
plan-founder-review — Review the plan before execution (quality gate)
start — Use start to identify if parallel agents are appropriate
run-parallel-agents-feature-debug — For debugging, use the debug variant instead
codemap — Use codemap search and codemap deps when preparing briefs to understand what code exists and what each file depends on
browse — For parallel web testing, use browse --session <agent-name> to isolate each agent's browser state

Workflow: start → plan-to-task-list-with-dag → plan-founder-review → run-parallel-agents-feature-build

Resources

references/

agent_matching_logic.md - Detailed rules for matching features to agent types, edge cases, and technology detection patterns

This skill does not require scripts or assets - it orchestrates existing Claude Code agent capabilities.