Multi-Agent Orchestration
Meta-orchestration patterns mined from 597+ real agent dispatches across production codebases. This skill tells you WHICH strategy to use, HOW to structure prompts, and WHEN to use background vs foreground.
Core principle: Choose the right orchestration strategy for the work, partition agents by independence, inject context to enable parallelism, and adapt review overhead to trust level.
Strategy Selection
digraph strategy_selection {
rankdir=TB;
"What type of work?" [shape=diamond];
"Research / knowledge gathering" [shape=box];
"Independent feature builds" [shape=box];
"Sequential dependent tasks" [shape=box];
"Same transformation across partitions" [shape=box];
"Codebase audit / assessment" [shape=box];
"Greenfield project kickoff" [shape=box];
"Research Swarm" [shape=box style=filled fillcolor=lightyellow];
"Epic Parallel Build" [shape=box style=filled fillcolor=lightyellow];
"Sequential Pipeline" [shape=box style=filled fillcolor=lightyellow];
"Parallel Sweep" [shape=box style=filled fillcolor=lightyellow];
"Multi-Dimensional Audit" [shape=box style=filled fillcolor=lightyellow];
"Full Lifecycle" [shape=box style=filled fillcolor=lightyellow];
"What type of work?" -> "Research / knowledge gathering";
"What type of work?" -> "Independent feature builds";
"What type of work?" -> "Sequential dependent tasks";
"What type of work?" -> "Same transformation across partitions";
"What type of work?" -> "Codebase audit / assessment";
"What type of work?" -> "Greenfield project kickoff";
"Research / knowledge gathering" -> "Research Swarm";
"Independent feature builds" -> "Epic Parallel Build";
"Sequential dependent tasks" -> "Sequential Pipeline";
"Same transformation across partitions" -> "Parallel Sweep";
"Codebase audit / assessment" -> "Multi-Dimensional Audit";
"Greenfield project kickoff" -> "Full Lifecycle";
}
| Strategy | When | Agents | Background | Key Pattern |
|---|---|---|---|---|
| Research Swarm | Knowledge gathering, docs, SOTA research | 10-60+ | Yes (100%) | Fan-out, each writes own doc |
| Epic Parallel Build | Plan with independent epics/features | 20-60+ | Yes (90%+) | Wave dispatch by subsystem |
| Sequential Pipeline | Dependent tasks, shared files | 3-15 | No (0%) | Implement -> Review -> Fix chain |
| Parallel Sweep | Same fix/transform across modules | 4-10 | No (0%) | Partition by directory, fan-out |
| Multi-Dimensional Audit | Quality gates, deep assessment | 6-9 | No (0%) | Same code, different review lenses |
| Full Lifecycle | New project from scratch | All above | Mixed | Research -> Plan -> Build -> Review -> Harden |
Strategy 1: Research Swarm
Mass-deploy background agents to build a knowledge corpus. Each agent researches one topic and writes one markdown document. Zero dependencies between agents.
When to Use
- •Kicking off a new project (need SOTA for all technologies)
- •Building a skill/plugin (need comprehensive domain knowledge)
- •Technology evaluation (compare multiple options in parallel)
The Pattern
Phase 1: Deploy research army (ALL BACKGROUND)
Wave 1 (10-20 agents): Core technology research
Wave 2 (10-20 agents): Specialized topics, integrations
Wave 3 (5-10 agents): Gap-filling based on early results
Phase 2: Monitor and supplement
- Check completed docs as they arrive
- Identify gaps, deploy targeted follow-up agents
- Read completed research to inform remaining dispatches
Phase 3: Synthesize
- Read all research docs (foreground)
- Create architecture plans, design docs
- Use Plan agent to synthesize findings
Prompt Template: Research Agent
Research [TECHNOLOGY] for [PROJECT]'s [USE CASE]. Create a comprehensive research doc at [OUTPUT_PATH]/[filename].md covering: 1. Latest [TECH] version and features (search "[TECH] 2026" or "[TECH] latest") 2. [Specific feature relevant to project] 3. [Another relevant feature] 4. [Integration patterns with other stack components] 5. [Performance characteristics] 6. [Known gotchas and limitations] 7. [Best practices for production use] 8. [Code examples for key patterns] Include code examples where possible. Use WebSearch and WebFetch to get current docs.
Key rules:
- •Every agent gets an explicit output file path (no ambiguity)
- •Include search hints: "search [TECH] 2026" (agents need recency guidance)
- •Numbered coverage list (8-12 items) scopes the research precisely
- •ALL agents run in background -- no dependencies between research topics
Dispatch Cadence
- •3-4 seconds between agent dispatches
- •Group into thematic waves of 10-20 agents
- •15-25 minute gaps between waves for gap analysis
Strategy 2: Epic Parallel Build
Deploy background agents to implement independent features/epics simultaneously. Each agent builds one feature in its own directory/module. No two agents touch the same files.
When to Use
- •Implementation plan with 10+ independent tasks
- •Monorepo with isolated packages/modules
- •Sprint backlog with non-overlapping features
The Pattern
Phase 1: Scout (FOREGROUND)
- Deploy one Explore agent to map the codebase
- Identify dependency chains and independent workstreams
- Group tasks by subsystem to prevent file conflicts
Phase 2: Deploy build army (ALL BACKGROUND)
Wave 1: Infrastructure/foundation (Redis, DB, auth)
Wave 2: Backend APIs (each in own module directory)
Wave 3: Frontend pages (each in own route directory)
Wave 4: Integrations (MCP servers, external services)
Wave 5: DevOps (CI, Docker, deployment)
Wave 6: Bug fixes from review findings
Phase 3: Monitor and coordinate
- Check git status for completed commits
- Handle git index.lock contention (expected with 30+ agents)
- Deploy remaining tasks as agents complete
- Track via Sibyl tasks or TodoWrite
Phase 4: Review and harden (FOREGROUND)
- Run Codex/code-reviewer on completed work
- Dispatch fix agents for critical findings
- Integration testing
Prompt Template: Feature Build Agent
**Task: [DESCRIPTIVE TITLE]** (task_[ID]) Work in /path/to/project/[SPECIFIC_DIRECTORY] ## Context [What already exists. Reference specific files, patterns, infrastructure.] [e.g., "Redis is available at `app.state.redis`", "Follow pattern from `src/auth/`"] ## Your Job 1. Create `src/path/to/module/` with: - `file.py` -- [Description] - `routes.py` -- [Description] - `models.py` -- [Schema definitions] 2. Implementation requirements: [Detailed spec with code snippets, Pydantic models, API contracts] 3. Tests: - Create `tests/test_module.py` - Cover: [specific test scenarios] 4. Integration: - Wire into [main app entry point] - Register routes at [path] ## Git Commit with message: "feat([module]): [description]" Only stage files YOU created. Check `git status` before committing. Do NOT stage files from other agents.
Key rules:
- •Every agent gets its own directory scope -- NO OVERLAP
- •Provide existing patterns to follow ("Follow pattern from X")
- •Include infrastructure context ("Redis available at X")
- •Explicit git hygiene instructions (critical with 30+ parallel agents)
- •Task IDs for traceability
Git Coordination for Parallel Agents
When running 10+ agents concurrently:
- •Expect index.lock contention -- agents will retry automatically
- •Each agent commits only its own files -- prompt must say this explicitly
- •No agent should run
git add .-- only specific files - •Monitor with
git log --oneline -20periodically - •No agent should push -- orchestrator handles push after integration
Strategy 3: Sequential Pipeline
Execute dependent tasks one at a time with review gates. Each task builds on the previous task's output. Use superpowers:subagent-driven-development for the full pipeline.
When to Use
- •Tasks that modify shared files
- •Integration boundary work (JNI bridges, auth chains)
- •Review-then-fix cycles where each fix depends on review findings
- •Complex features where implementation order matters
The Pattern
For each task:
1. Dispatch implementer (FOREGROUND)
2. Dispatch spec reviewer (FOREGROUND)
3. Dispatch code quality reviewer (FOREGROUND)
4. Fix any issues found
5. Move to next task
Trust Gradient (adapt over time):
Early tasks: Implement -> Spec Review -> Code Review (full ceremony)
Middle tasks: Implement -> Spec Review (lighter)
Late tasks: Implement only (pattern proven, high confidence)
Trust Gradient
As the session progresses and patterns prove reliable, progressively lighten review overhead:
| Phase | Review Overhead | When |
|---|---|---|
| Full ceremony | Implement + Spec Review + Code Review | First 3-4 tasks |
| Standard | Implement + Spec Review | Tasks 5-8, or after patterns stabilize |
| Light | Implement + quick spot-check | Late tasks with established patterns |
| Cost-optimized | Use model: "haiku" for reviews | Formulaic review passes |
This is NOT cutting corners -- it's earned confidence. If a late task deviates from the pattern, escalate back to full ceremony.
Strategy 4: Parallel Sweep
Apply the same transformation across partitioned areas of the codebase. Every agent does the same TYPE of work but on different FILES.
When to Use
- •Lint/format fixes across modules
- •Type annotation additions across packages
- •Test writing for multiple modules
- •Documentation updates across components
- •UI polish across pages
The Pattern
Phase 1: Analyze the scope
- Run the tool (ruff, ty, etc.) to get full issue list
- Auto-fix what you can
- Group remaining issues by module/directory
Phase 2: Fan-out fix agents (4-10 agents)
- One agent per module/directory
- Each gets: issue count by category, domain-specific guidance
- All foreground (need to verify each completes)
Phase 3: Verify and repeat
- Run the tool again to check remaining issues
- If issues remain, dispatch another wave
- Repeat until clean
Prompt Template: Module Fix Agent
Fix all [TOOL] issues in the [MODULE_NAME] directory ([PATH]). Current issues ([COUNT] total): - [RULE_CODE]: [description] ([count]) -- [domain-specific fix guidance] - [RULE_CODE]: [description] ([count]) -- [domain-specific fix guidance] Run `[TOOL_COMMAND] [PATH]` to see exact issues. IMPORTANT for [DOMAIN] code: [Domain-specific guidance, e.g., "GTK imports need GI.require_version() before gi.repository imports"] After fixing, run `[TOOL_COMMAND] [PATH]` to verify zero issues remain.
Key rules:
- •Provide issue counts by category (not just "fix everything")
- •Include domain-specific guidance (agents need to know WHY patterns exist)
- •Partition by directory to prevent overlap
- •Run in waves: fix -> verify -> fix remaining -> verify
Strategy 5: Multi-Dimensional Audit
Deploy multiple reviewers to examine the same code from different angles simultaneously. Each reviewer has a different focus lens.
When to Use
- •Major feature complete, need comprehensive review
- •Pre-release quality gate
- •Security audit
- •Performance assessment
The Pattern
Dispatch 6 parallel reviewers (ALL FOREGROUND):
1. Code quality & safety reviewer
2. Integration correctness reviewer
3. Spec completeness reviewer
4. Test coverage reviewer
5. Performance analyst
6. Security auditor
Wait for all to complete, then:
- Synthesize findings into prioritized action list
- Dispatch targeted fix agents for critical issues
- Re-review only the dimensions that had findings
Prompt Template: Dimension Reviewer
[DIMENSION] review of [COMPONENT] implementation. **Files to review:** - [file1.ext] - [file2.ext] - [file3.ext] **Analyze:** 1. [Specific question for this dimension] 2. [Specific question for this dimension] 3. [Specific question for this dimension] **Report format:** - Findings: numbered list with severity (Critical/Important/Minor) - Assessment: Approved / Needs Changes - Recommendations: prioritized action items
Strategy 6: Full Lifecycle
For greenfield projects, combine all strategies in sequence:
Session 1: RESEARCH (Research Swarm)
-> 30-60 background agents build knowledge corpus
-> Architecture planning agents synthesize findings
-> Output: docs/research/*.md + docs/plans/*.md
Session 2: BUILD (Epic Parallel Build)
-> Scout agent maps what exists
-> 30-60 background agents build features by epic
-> Monitor, handle git contention, track completions
-> Output: working codebase with commits
Session 3: ITERATE (Build-Review-Fix Pipeline)
-> Code review agents assess work
-> Fix agents address findings
-> Deep audit agents (foreground) assess each subsystem
-> Output: quality-assessed codebase
Session 4: HARDEN (Sequential Pipeline)
-> Integration boundary reviews (foreground, sequential)
-> Security fixes, race condition fixes
-> Test infrastructure setup
-> Output: production-ready codebase
Each session shifts orchestration strategy to match the work's nature. Parallel when possible, sequential when required.
Background vs Foreground Decision
digraph bg_fg {
"What is the agent producing?" [shape=diamond];
"Information (research, docs)" [shape=box];
"Code modifications" [shape=box];
"Does orchestrator need it NOW?" [shape=diamond];
"BACKGROUND" [shape=box style=filled fillcolor=lightgreen];
"FOREGROUND" [shape=box style=filled fillcolor=lightyellow];
"Does next task depend on this task's files?" [shape=diamond];
"FOREGROUND (sequential)" [shape=box style=filled fillcolor=lightyellow];
"FOREGROUND (parallel)" [shape=box style=filled fillcolor=lightyellow];
"What is the agent producing?" -> "Information (research, docs)";
"What is the agent producing?" -> "Code modifications";
"Information (research, docs)" -> "Does orchestrator need it NOW?";
"Does orchestrator need it NOW?" -> "FOREGROUND" [label="yes"];
"Does orchestrator need it NOW?" -> "BACKGROUND" [label="no - synthesize later"];
"Code modifications" -> "Does next task depend on this task's files?";
"Does next task depend on this task's files?" -> "FOREGROUND (sequential)" [label="yes"];
"Does next task depend on this task's files?" -> "FOREGROUND (parallel)" [label="no - different modules"];
}
Rules observed from 597+ dispatches:
- •Research agents with no immediate dependency -> BACKGROUND (100% of the time)
- •Code-writing agents -> FOREGROUND (even if parallel)
- •Review/validation gates -> FOREGROUND (blocks pipeline)
- •Sequential dependencies -> FOREGROUND, one at a time
Prompt Engineering Patterns
Pattern A: Role + Mission + Structure (Research)
You are researching [DOMAIN] to create comprehensive documentation for [PROJECT]. Your mission: Create an exhaustive reference document covering ALL [TOPIC] capabilities. Cover these areas in depth: 1. **[Category]** -- specific items 2. **[Category]** -- specific items ... Use WebSearch and WebFetch to find blog posts, GitHub repos, and official docs.
Pattern B: Task + Context + Files + Spec (Feature Build)
**Task: [TITLE]** (task_[ID]) Work in /absolute/path/to/[directory] ## Context [What exists, what to read, what infrastructure is available] ## Your Job 1. Create `path/to/file` with [description] 2. [Detailed implementation spec] 3. [Test requirements] 4. [Integration requirements] ## Git Commit with: "feat([scope]): [message]" Only stage YOUR files.
Pattern C: Review + Verify + Report (Audit)
Comprehensive audit of [SCOPE] for [DIMENSION]. Look for: 1. [Specific thing #1] 2. [Specific thing #2] ... 10. [Specific thing #10] [Scope boundaries -- which directories/files] Report format: - Findings: numbered with severity - Assessment: Pass / Needs Work - Action items: prioritized
Pattern D: Issue + Location + Fix (Bug Fix)
**Task:** Fix [ISSUE] -- [SEVERITY] **Problem:** [Description with file:line references] **Location:** [Exact file path] **Fix Required:** 1. [Specific change] 2. [Specific change] **Verify:** 1. Run [command] to confirm fix 2. Run tests: [test command]
Context Injection: The Parallelism Enabler
Agents can work independently BECAUSE the orchestrator pre-loads them with all context they need. Without this, agents would need to explore first, serializing the work.
Always inject:
- •Absolute file paths (never relative)
- •Existing patterns to follow ("Follow pattern from
src/auth/jwt.py") - •Available infrastructure ("Redis at
app.state.redis") - •Design language/conventions ("SilkCircuit Neon palette")
- •Tool usage hints ("Use WebSearch to find...")
- •Git instructions ("Only stage YOUR files")
For parallel agents, duplicate shared context:
- •Copy the same context block into each agent's prompt
- •Explicit exclusion notes ("11-Sibyl is handled by another agent")
- •Shared utilities described identically
Monitoring Parallel Agents
When running 10+ background agents:
- •Check periodically --
git log --oneline -20for commits - •Read output files --
tailthe agent output files for progress - •Track completions -- Use Sibyl tasks or TodoWrite
- •Deploy gap-fillers -- As early agents complete, identify missing work
- •Handle contention -- git index.lock is expected, agents retry automatically
Status Report Template
## Agent Swarm Status **[N] agents deployed** | **[M] completed** | **[P] in progress** ### Completed: - [Agent description] -- [Key result] - [Agent description] -- [Key result] ### In Progress: - [Agent description] -- [Status] ### Gaps Identified: - [Missing area] -- deploying follow-up agent
Common Mistakes
DON'T: Dispatch agents that touch the same files -> merge conflicts DO: Partition by directory/module -- one agent per scope
DON'T: Run all agents foreground when they're independent -> sequential bottleneck DO: Use background for research, foreground for code that needs coordination
DON'T: Send 50 agents with vague "fix everything" prompts DO: Give each agent a specific scope, issue list, and domain guidance
DON'T: Skip the scout phase for build sprints DO: Always Explore first to map what exists and identify dependencies
DON'T: Keep full review ceremony for every task in a long session DO: Apply the trust gradient -- earn lighter reviews through consistency
DON'T: Let agents run git add . or git push
DO: Explicit git hygiene in every build prompt
DON'T: Dispatch background agents for code that needs integration DO: Background is for research only. Code agents run foreground.
Integration with Other Skills
| Skill | Use With | When |
|---|---|---|
superpowers:subagent-driven-development | Sequential Pipeline | Single-task implement-review cycles |
superpowers:dispatching-parallel-agents | Parallel Sweep | Independent bug fixes |
superpowers:writing-plans | Full Lifecycle | Create the plan before Phase 2 |
superpowers:executing-plans | Sequential Pipeline | Batch execution in separate session |
superpowers:brainstorming | Full Lifecycle | Before research phase |
superpowers:requesting-code-review | All strategies | Quality gates between phases |
superpowers:verification-before-completion | All strategies | Final validation |