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parallel-agents

Orchestrate concurrent analysis or implementation across independent domains. Use when a task can be decomposed into independent workstreams (e.g., via simultaneous tool calls or background processes) — spec writing, code review, security audit, feature implementation.

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Parallel Agents & Concurrent Tool Execution

Overview

Some tasks are naturally parallelizable — they have independent domains that don't share state. As a highly-capable agent, you can drastically cut wall-clock time by leveraging concurrent tool execution (e.g., running multiple view_file calls, grep_search calls, or background terminal commands simultaneously) instead of investigating sequentially.

Core principle: Parallelism is a scheduling optimization, not a quality shortcut. Every concurrent workstream follows the same quality standards as a sequential task.

When to Use

  • Multi-surface implementation — A slice has independent surfaces (DB, API, UI, admin) that don't share implementation logic
  • Multi-domain analysis — Security audit + performance review + accessibility audit on the same codebase
  • Spec writing — Multiple IA shards need specs written from the same architecture doc
  • Code review — Large PR touches independent subsystems
  • Debugging — Multiple independent failures (see parallel-debugging skill for the full protocol)

When NOT to Use

  • Tasks share mutable state or edit the same files
  • Later tasks depend on output of earlier tasks (use sequential pipeline instead)
  • You don't fully understand the task decomposition yet (investigate first)
  • Simple task that one agent handles in < 5 minutes

The Protocol

1. Decompose

Break the task into independent domains. Each domain must satisfy ALL of:

RequirementWhy
Independent files — workstreams do not mutate the same filePrevents race conditions and tool call hash mismatches
Independent state — no shared mutable resources (DB tables, caches)Prevents race conditions
Self-contained context — stream can run without waiting on another's outputPrevents blocking
Clear deliverable — you can verify the stream's work in isolationPrevents integration surprises

If any requirement fails → that domain can't be parallelized. Run it sequentially.

2. Define Workstream Profiles

Instead of giving yourself a single massive objective, explicitly define the scope for each concurrent stream conceptually:

## Workstream: [Domain Name]
### Scope
[Exactly what this stream owns — files, features, concerns]

### Context
[Everything needed — paste relevant code, specs, error messages]

### Constraints
- Do NOT mutate files outside the defined scope
- Follow rule: boundary-not-placeholder for cross-stream dependencies

Scope quality rules:

  • ✅ Focused — one clear problem domain
  • ✅ Constrained — explicit file/scope boundaries
  • ❌ Shared Mutable State — running replace_file_content on the same file concurrently will fail or corrupt data.

3. Concurrent Execution

Launch the workstreams simultaneously using your concurrent tool execution capabilities. For example, if testing and formatting code, you might run npm run test in one background terminal and npx prettier --write in another, checking the statuses of both instead of waiting for one to finish before starting the other. When making file edits, batch disjoint replace_file_content tool calls in the same turn.

4. Synthesize

After ALL concurrent streams yield results, synthesize them into a single coherent picture before proceeding:

## Concurrent Synthesis

### Task Summary
[What was accomplished across all workstreams]

### Findings by Domain
| Domain | Finding/Result |
|--------|----------------|
| Stream 1 | [what was found] |
| Stream 2 | [what was found] |

### Consolidated Actions
1. **Critical**: [From Stream X]
2. **Important**: [From Stream Y]

### Integration Verification
- [ ] No file conflicts during concurrent editing
- [ ] Full test suite passes
- [ ] Changes reviewed for consistency

5. Verify Integration

Non-negotiable: After merging all agent outputs:

  1. Run the full validation suite (not just individual agent tests)
  2. Check for contradictions between agent recommendations
  3. Verify no files were modified by multiple agents
  4. Spot-check agent work — agents can make systematic errors

Task Decomposition Archetypes

These are suggested ways to slice concurrent workstreams:

ArchetypeDomain FocusTypical Sub-Skills
Security ReviewVulnerabilities, RBAC, input validationsecurity-scanning, code-review
Test QualityTest coverage, edge casestdd-workflow
Backend ImplementationAPI design, data layerrest-api-design, surrealdb-expert
Frontend ImplementationUI components, accessibilityfrontend-design, accessibility
Performance AuditBottlenecks, bundle sizeweb-performance-optimization
DocumentationAPI docs, architecture docs—
ACH DebuggingRoot cause investigationsystematic-debugging, parallel-debugging

Integration with Kit

  • With parallel-feature-development: When making concurrent file edits, use the strict file ownership protocol to prevent tool call conflicts (e.g. failing replace_file_content because the file hash changed).
  • With session-continuity Protocol 9: When you claim both a BE and FE task concurrently, the files: blocks are your guarantee that you can execute edits simultaneously safely.
  • With boundary-not-placeholder: If a concurrent stream hits a missing dependency, use // BOUNDARY: stubs. Don't block the stream indefinitely.

Common Mistakes

MistakeConsequenceFix
Concurrent edits to same fileOverwrites, hash mismatchesOne stream per file strictly
No synthesis stepContradictory logicAlways synthesize before committing changes
Shared dependencies not frozenBuild breaks unexpectedlyUse interface contracts first

TDD-Order Dispatch (Slice Implementation)

Triggering Condition

Enter parallel mode when the slice's tasks contain surface tags (BE, FE, QA). Proceed sequentially when no tags are found.

Core Principle

Tests are the rock. Code is malleable. Tests encode the acceptance criteria and must be comprehensive. Code adapts to pass tests, never the reverse.

5-Phase Dispatch Table

PhaseAgentResponsibilityDepends On
0OrchestratorContracts/schemas (untagged tasks)—
1QA (RED)Write comprehensive failing testsPhase 0
2BE + FE (parallel)Write code to make tests passPhase 1
3QA (GREEN)Verify all tests pass, anti-cheat auditPhase 2
4OrchestratorIterative correction loop if neededPhase 3

Dispatch Instructions

  1. Untagged tasks first — Contract/schema work runs sequentially by orchestrator (Phase 0) before any tagged dispatch.
  2. QA-RED — QA agent writes comprehensive failing tests for ALL acceptance criteria. Tests MUST fail. Read .claude/skills/session-continuity/protocols/09-parallel-claim.md. Every contract field and error type covered.
  3. BE + FE parallel — Code against tests and contracts simultaneously. Annotate spec-gap decisions with // DECISION: [what and why].
  4. QA-GREEN — Re-verify all tests pass, anti-cheat check, add integration tests.
  5. Iterative loop rule — If QA-GREEN fails → re-dispatch BE/FE → QA-GREEN again → repeat until all pass.
  6. File independence check — Verify no two tagged tasks touch the same files before dispatching (prevents tool call hash mismatches).

Progress Logging

Log each dispatch phase to .memory/pipeline/progress/slices/phase-NN-slice-NN.md under ## Dispatch Log.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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