dispatching-parallel-agents

Gunakan saat ada banyak kegagalan/bug/tes yang independen (file berbeda, subsistem berbeda, tidak ada shared state) dan bisa diselidiki bersamaan. Aktif saat user minta 'dispatch agent paralel', 'kerjakan investigasi ini bersamaan', atau ada 3+ kegagalan dengan root-cause berbeda.

Suga Nick@pmuhammadagus-byte

Install

openclaw skills install @pmuhammadagus-byte/dispatching-parallel-agents

dispatching-parallel-agents — X∞ Compliance Layer

1. IDENTITY

Skill milik user: dispatching-parallel-agents. Mengikuti Skill Architecture Standard X∞ (wajib).

2. PURPOSE

Mendelegasikan tugas ke agen terspesialisasi dengan konteks terisolasi—satu agen per domain masalah independen, dijalankan konkuren—agar investigasi yang tidak saling terkait selesai lebih cepat tanpa menguras konteks koordinator.

3. METADATA

name: dispatching-parallel-agents
version: 1.0.0
standard: Skill Architecture Standard X∞ (21-node)
scope: orchestrasi subagent paralel untuk domain independen
depends_on: sessions_spawn / subagent

4. TRIGGER ENGINE

Aktif ketika user meminta hal yang cocok dengan deskripsi di atas. Negative trigger: di luar scope deskripsi.

5. CONTEXT ENGINE

Baca OS/ARCH/runtime sebelum bertindak. Termux Android ARM64 ≠ Ubuntu x86_64.

6. DECISION POLICY

IF uncertainty → VERIFY IF high risk → ASK/STOP IF tool unavailable → ALTERNATIVE IF action fails → RECOVER

7. REASONING POLICY

Evidence-first. Bedakan FAKTA vs HIPOTESIS. Confidence: CONFIRMED/LIKELY/POSSIBLE/UNKNOWN.

8. EXECUTION POLICY

Ambil tindakan relevan, lalu VERIFY. Jangan klaim sukses sebelum diverifikasi.

9. TOOL POLICY

Pilih tool berdasar kebutuhan+konteks. Jangan asal panggil semua tool.

10. MEMORY POLICY

Ingat hal relevan; abaikan noise. Retrieve saat dibutuhkan, update bila berubah.

11. VERIFICATION ENGINE

ACTION → VERIFY → SUCCESS? Jika tidak: DIAGNOSE → RETRY/CHANGE STRATEGY.

12. ERROR RECOVERY

transient→retry; timeout→backoff; auth→credential check; dependency→diagnosis; unknown→investigate.

13. SECURITY GUARDRAILS

NEVER log secret. REDACT API KEY/TOKEN/PASSWORD/SECRET sebelum simpan. PII: MINIMIZE→REDACT→HASH.

14. EVALUATION

Self-eval: capai goal? terverifikasi? ada asumsi? ada gagal? Kirim ke Agent Evaluation Engine.

15. OBSERVABILITY

Emit: START/PROGRESS/TOOL CALL/ERROR/RETRY/SUCCESS/FAILURE + TRACE_ID (tanpa secret).

16. PERFORMANCE OPTIMIZATION

FULL→OPTIMIZED→LOW RESOURCE mode bila terbatas. Prioritas: TASK>SAFETY>RELIABILITY.

17. SELF-IMPROVEMENT

USE→OBSERVE→EVALUATE→FIND WEAKNESS→IMPROVE→TEST→NEW VERSION (via evaluasi+regresi).

18. VERSIONING

Semver. Perubahan struktur = MAJOR. CHANGELOG wajib. CHANGELOG

1.0.0 — Perbaikan kualitas lapisan X∞: frontmatter description rusak (berisi teks changelog) diganti deskripsi trigger nyata; Node 2 (PURPOSE) & Node 3 (METADATA) diisi (bukan stub); metadata.openclaw.version ditambahkan. Konten domain (pattern dispatch paralel, agent prompt structure, rationalization table) dipertahankan.

19. COMPATIBILITY

Tahu OS/ARCH/RUNTIME/versi/tool/API tersedia.

20. KNOWLEDGE SOURCES

Trust hierarchy: OFFICIAL>PRIMARY>REPUTABLE>COMMUNITY>UNKNOWN. Tandai VERIFIED/LIKELY/UNCERTAIN/OUTDATED/CONFLICTING.

21. EXIT CONDITIONS

Berhenti pada: SUCCESS/FAILURE/BLOCKED/NEED USER/NEED CREDENTIAL/NEED TOOL/NEED VERIFICATION.

Dispatching Parallel Agents

Overview

You delegate tasks to specialized agents with isolated context. By precisely crafting their instructions and context, you ensure they stay focused and succeed at their task. They should never inherit your session's context or history — you construct exactly what they need. This also preserves your own context for coordination work.

When you have multiple unrelated failures (different test files, different subsystems, different bugs), investigating them sequentially wastes time. Each investigation is independent and can happen in parallel.

Core principle: Dispatch one agent per independent problem domain. Let them work concurrently.

When to Use

dot

digraph when_to_use {
    "Multiple failures?" [shape=diamond];
    "Are they independent?" [shape=diamond];
    "Single agent investigates all" [shape=box];
    "One agent per problem domain" [shape=box];
    "Can they work in parallel?" [shape=diamond];
    "Sequential agents" [shape=box];
    "Parallel dispatch" [shape=box];

    "Multiple failures?" -> "Are they independent?" [label="yes"];
    "Are they independent?" -> "Single agent investigates all" [label="no - related"];
    "Are they independent?" -> "Can they work in parallel?" [label="yes"];
    "Can they work in parallel?" -> "Parallel dispatch" [label="yes"];
    "Can they work in parallel?" -> "Sequential agents" [label="no - shared state"];
}

Use when:

3+ test files failing with different root causes
Multiple subsystems broken independently
Each problem can be understood without context from others
No shared state between investigations

Don't use when:

Failures are related (fix one might fix others)
Need to understand full system state
Agents would interfere with each other

The Pattern

1. Identify Independent Domains

Group failures by what's broken:

File A tests: Tool approval flow
File B tests: Batch completion behavior
File C tests: Abort functionality

Each domain is independent - fixing tool approval doesn't affect abort tests.

2. Create Focused Agent Tasks

Each agent gets:

Specific scope: One test file or subsystem
Clear goal: Make these tests pass
Constraints: Don't change other code
Expected output: Summary of what you found and fixed

3. Dispatch in Parallel

Issue all three subagent dispatches in the same response — they run in parallel:

text

Subagent (general-purpose): "Fix agent-tool-abort.test.ts failures"
Subagent (general-purpose): "Fix batch-completion-behavior.test.ts failures"
Subagent (general-purpose): "Fix tool-approval-race-conditions.test.ts failures"
# All three run concurrently.

Multiple dispatch calls in one response = parallel execution. One per response = sequential.

4. Review and Integrate

When agents return:

Read each summary
Verify fixes don't conflict
Run full test suite
Integrate all changes

Agent Prompt Structure

Good agent prompts are:

Focused - One clear problem domain
Self-contained - All context needed to understand the problem
Specific about output - What should the agent return?

markdown

Fix the 3 failing tests in src/agents/agent-tool-abort.test.ts:

1. "should abort tool with partial output capture" - expects 'interrupted at' in message
2. "should handle mixed completed and aborted tools" - fast tool aborted instead of completed
3. "should properly track pendingToolCount" - expects 3 results but gets 0

These are timing/race condition issues. Your task:

1. Read the test file and understand what each test verifies
2. Identify root cause - timing issues or actual bugs?
3. Fix by:
   - Replacing arbitrary timeouts with event-based waiting
   - Fixing bugs in abort implementation if found
   - Adjusting test expectations if testing changed behavior

Do NOT just increase timeouts - find the real issue.

Return: Summary of what you found and what you fixed.

Common Mistakes

❌ Too broad: "Fix all the tests" - agent gets lost ✅ Specific: "Fix agent-tool-abort.test.ts" - focused scope

❌ No context: "Fix the race condition" - agent doesn't know where ✅ Context: Paste the error messages and test names

❌ No constraints: Agent might refactor everything ✅ Constraints: "Do NOT change production code" or "Fix tests only"

❌ Vague output: "Fix it" - you don't know what changed ✅ Specific: "Return summary of root cause and changes"

Common Rationalizations

Excuse	Reality
"I'll just fix them sequentially"	Parallel is faster for independent problems.
"One agent can handle all of them"	Focused agents do better work.
"The agents might conflict"	Independent domains = no conflicts.
"I don't have time to craft prompts"	Good prompts save time overall.
"I'll just do it myself"	Agents work in parallel while you coordinate.

When NOT to Use

Related failures: Fixing one might fix others - investigate together first Need full context: Understanding requires seeing entire system Exploratory debugging: You don't know what's broken yet Shared state: Agents would interfere (editing same files, using same resources)

Real Example from Session

Scenario: 6 test failures across 3 files after major refactoring

Failures:

agent-tool-abort.test.ts: 3 failures (timing issues)
batch-completion-behavior.test.ts: 2 failures (tools not executing)
tool-approval-race-conditions.test.ts: 1 failure (execution count = 0)

Decision: Independent domains - abort logic separate from batch completion separate from race conditions

Dispatch:

text

Agent 1 → Fix agent-tool-abort.test.ts
Agent 2 → Fix batch-completion-behavior.test.ts
Agent 3 → Fix tool-approval-race-conditions.test.ts

Results:

Agent 1: Replaced timeouts with event-based waiting
Agent 2: Fixed event structure bug (threadId in wrong place)
Agent 3: Added wait for async tool execution to complete

Integration: All fixes independent, no conflicts, full suite green

Verification

After agents return:

Review each summary - Understand what changed
Check for conflicts - Did agents edit same code?
Run full suite - Verify all fixes work together
Spot check - Agents can make systematic errors

Quick Reference

Situation	Action
Independent failures	Dispatch parallel agents
Related failures	Investigate together first
Need full context	Don't use parallel agents
Shared state	Don't use parallel agents
Agent returns	Review summary, check conflicts
All agents done	Run full test suite