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Agent Skill · 研究检索

dispatching-parallel-agents(调度并行 Agent)

dispatching-parallel-agents 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

dispatching-parallel-agents 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 47,657。

总安装 724周安装 29GitHub Stars 1下载 234核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:dispatching-parallel-agents(调度并行 Agent)
来源仓库:https://github.com/pixel-process-ug/superkit-agents
仓库路径:skills/dispatching-parallel-agents
安装命令:
npx skills add https://github.com/pixel-process-ug/superkit-agents --skill dispatching-parallel-agents
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/pixel-process-ug/superkit-agents --skill dispatching-parallel-agents

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

dispatching-parallel-agents 用于查找、检索和筛选相关信息,适合快速定位候选结果。适用于需要根据关键词或任务场景从来源线索中筛选信息的场景。通过 npx skills add 命令从指定 GitHub 仓库安装并使用该技能。安装前需确认权限范围和维护状态,注意可能触发联网或文件读写操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/dispatching-parallel-agents

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/pixel-process-ug/superkit-agents --skill dispa…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

dispatching-parallel-agents 怎么安装?

在终端执行 npx skills add https://github.com/pixel-process-ug/superkit-agents --skill dispatching-par…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

dispatching-parallel-agents 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

dispatching-parallel-agents 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

dispatching-parallel-agents 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

dispatching-parallel-agents 用的人多吗?

公开数据是累计安装 724 次,近一周安装 29 次,下载 234 次,GitHub 1 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

dispatching-parallel-agents 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
dispatching-parallel-agents

调度并行 Agent · 本页

7241需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Dispatching Parallel Agents

Overview

This skill coordinates multiple agents working concurrently on independent subtasks to reduce total execution time while maintaining correctness. It provides strict rules for identifying safe parallelization opportunities, writing focused agent prompts, and integrating results without conflicts. The key constraint is that no two agents may modify the same file.

Announce at start: "I'm using the dispatching-parallel-agents skill to run [N] independent tasks concurrently."

Agent Tool Reference

All dispatch uses the Agent tool. Parameters:

  • prompt (required) — task description with full context
  • description (required) — short label (3-5 words)
  • subagent_type — "Explore" (codebase search), "Plan" (architecture), "general-purpose" (default)
  • run_in_background — true for async (you'll be notified on completion)
  • model — optional override: "sonnet", "opus", "haiku"

Parallel: Multiple Agent calls in one message run concurrently. Background: run_in_background=true for non-blocking work. Named agents: Use subagent_type to reference installed agent templates (e.g., "superpowers:code-reviewer").

Trigger Conditions

  • A task decomposes into 2+ subtasks with no data dependencies between them
  • Each subtask operates on different files or different sections of the codebase
  • The combined result can be assembled after all agents complete
  • Total serial time would be significantly longer than parallel time
  • /decompose output reveals independent task clusters

Phase 1: Independence Verification

Goal: Confirm subtasks are truly independent and safe to parallelize.

Every subtask must satisfy ALL four independence criteria:

CriterionQuestionIf NO
No shared filesDo any two agents write to the same file?Serialize those tasks
No shared mutable stateDoes any agent depend on a side effect of another?Serialize dependent tasks
Self-contained contextCan each agent work with only its own inputs?Provide more context or serialize
Independent verificationCan each agent's output be validated alone?Combine into single task

Parallelization Decision Table

ScenarioParallelize?Reason
Different files, different concernsYesNo conflict possible
Same module, different filesYes (careful)Verify no shared imports change
Same file, different sectionsNoMerge conflicts inevitable
Task B uses Task A's outputNoSequential dependency
Both read same files, write differentYesReads are safe to parallelize
Both modify shared config fileNoConfig conflicts
Independent test filesYesTests are independent
One agent adds dep, another uses itNoPackage-level dependency

When NOT to Parallelize

  • Subtasks share mutable state or modify the same files
  • Task B depends on the output of Task A
  • The overhead of coordination exceeds the time saved
  • A single agent can complete the work in under 30 seconds
  • The task requires iterative refinement where each step informs the next

STOP — Do NOT dispatch agents (via the Agent tool) until:

  • All four independence criteria verified for every subtask pair
  • No two agents write to the same file
  • Each agent's context is self-contained

Phase 2: Prompt Construction

Goal: Write focused, unambiguous prompts that prevent scope creep and conflicts.

Each agent prompt MUST contain exactly four sections:

Section 1: Scope (What to Do)

Be specific about the exact task, files, and expected changes.

SCOPE: Add structured JSON logging to all API route handlers in src/api/.
Replace console.log calls with the logger from src/utils/logger.ts.
Files to modify: src/api/users.ts, src/api/orders.ts, src/api/products.ts.

Section 2: Context (Everything Needed)

Provide all information the agent needs without requiring it to explore.

CONTEXT:
- Logger API: logger.info(message, metadata), logger.error(message, error)
- Import: import { logger } from '../utils/logger'
- Current pattern in files: console.log('action', data)
- Target pattern: logger.info('action', { data, requestId: req.id })

Section 3: Output Format (What to Return)

Define exactly what the agent should produce.

OUTPUT: For each modified file, return:
1. The file path
2. A summary of changes made
3. Number of console.log calls replaced

Section 4: Constraints (What NOT to Do)

Prevent scope creep and conflicts explicitly.

CONSTRAINTS:
- Do NOT modify any files outside src/api/
- Do NOT change the logger utility itself
- Do NOT add new dependencies
- Do NOT refactor function signatures
- Do NOT modify test files
- If you encounter an issue outside your scope, report it but do not fix it

Agent Prompt Template

You are a focused agent with a single task.

## Scope
[Specific task description with exact files]

## Context
[All information needed to complete the task]
[Relevant code patterns, APIs, conventions]

## Output Format
[Exact structure of what to return]

## Constraints
- Do NOT modify files outside: [list]
- Do NOT change: [list things to leave alone]
- Do NOT add dependencies
- If you encounter an issue outside your scope, report it but do not fix it

Prompt Quality Checklist

CheckQuestion
Scope is specificCan the agent complete the task without guessing?
Context is completeDoes the agent need to explore the codebase? (should be no)
Output is definedWill the agent return what you need to integrate?
Constraints are explicitAre file boundaries and "do NOT" items clear?

STOP — Do NOT dispatch (via the Agent tool) until:

  • Every prompt has all 4 sections
  • No prompt requires the agent to explore beyond provided context
  • File boundaries are explicit in every constraint section

Phase 3: Dispatch and Monitor

Goal: Launch all agents (via the Agent tool) concurrently and track completion.

  1. Launch all agents concurrently by invoking multiple Agent tool calls in a single message
  2. Each agent works in isolation on its designated files
  3. Monitor for completion — wait for ALL agents to finish
  4. Collect outputs from every agent

Dispatch Tracking Table

| Agent | Task | Status | Files | Result |
|-------|------|--------|-------|--------|
| Agent 1 | Add logging to API | in_progress | src/api/*.ts | — |
| Agent 2 | Update unit tests | in_progress | tests/unit/*.ts | — |
| Agent 3 | Fix CSS layout | in_progress | src/styles/*.css | — |

Failure Handling During Dispatch

ScenarioAction
One agent fails, others succeedRetry failed agent independently (via the Agent tool)
Multiple agents fail independentlyRetry each independently (via the Agent tool)
Agent reports out-of-scope issueNote for post-integration review
Agent exceeds scope (modifies wrong files)Reject output, re-dispatch (via the Agent tool) with stricter constraints

Phase 4: Integration and Verification

Goal: Combine all agent outputs and verify the integrated result.

  1. Collect outputs — Gather results from every agent
  2. Check for conflicts — Verify no file was modified by multiple agents
  3. Apply changes — Integrate all outputs into the codebase
  4. Run integration checks — Execute the full test suite
  5. Resolve issues — If integration fails, identify which agent's changes caused it
  6. Commit atomically — All changes go in together or not at all

Integration Verification Checklist

CheckCommandMust Pass
No file conflictsDiff outputs for shared filesYes
Tests passFull test suiteYes
Build passesBuild commandYes
Lint passesLint commandYes
No regressionsCompare test count before/afterYes

Integration Failure Decision Table

Failure TypeDiagnosisAction
Test failure in Agent 1's filesAgent 1's changes have a bugRe-dispatch Agent 1 (via the Agent tool) with test failure context
Test failure in unrelated filesCross-cutting regressionIdentify root cause, fix manually or re-dispatch (via the Agent tool)
Build failureImport/type issueCheck which agent's changes caused it, fix
Merge conflictAgents touched same file (should not happen)Rollback, serialize those tasks

STOP — Do NOT commit until:

  • All agent outputs collected
  • No file conflicts detected
  • Full test suite passes
  • Build and lint pass

Common Parallel Patterns

Pattern Decision Table

PatternWhen to UseExample
By ModuleIndependent modules or packagesOne Agent call per microservice
By LayerLayers touch different filesAPI agent, service agent, data agent
By Feature AreaIndependent vertical slicesAuth agent, profile agent, billing agent
By Task TypeCode, tests, docs touch different filesCode agent, test agent, docs agent

Example: Full Dispatch

TASK: "Update the API to v2, add tests, and update OpenAPI spec"

AGENT 1 - API Routes:
  Scope: Update route handlers in src/routes/v2/
  Context: [v2 API spec, breaking changes list]
  Output: Modified files list, breaking changes implemented
  Constraints: Do NOT touch tests or docs

AGENT 2 - Tests:
  Scope: Write tests in tests/v2/
  Context: [v2 API spec, test conventions, existing v1 tests as reference]
  Output: New test files, coverage summary
  Constraints: Do NOT modify source code

AGENT 3 - OpenAPI Spec:
  Scope: Update openapi/v2.yaml
  Context: [v2 API spec, OpenAPI 3.1 format]
  Output: Updated spec file
  Constraints: Do NOT modify code or tests

Anti-Patterns / Common Mistakes

Anti-PatternWhy It FailsCorrect Approach
Two agents modifying the same fileMerge conflicts, data lossOne file owner per Agent dispatch
Shared mutable state between agentsRace conditions, inconsistencyEliminate shared state
Incomplete context in promptsAgents explore and step on each otherProvide ALL needed context
Vague file boundariesAgents guess scope, modify wrong filesExplicit file lists in constraints
No integration check after completionCross-cutting bugs go undetectedFull test suite after integration
Parallelizing sequential tasksAgent B needs Agent A's outputVerify independence first
Not tracking which agent touched which fileCannot diagnose integration failuresMaintain dispatch tracking table
Dispatching too many agents (10+)Coordination overhead exceeds savings2-5 Agent calls per dispatch round
Skipping rollback preparationCannot recover from integration failureKeep pre-dispatch state recoverable

Anti-Rationalization Guards

If you catch yourself thinking:

  • "These agents probably won't conflict..." — Verify. Do not assume.
  • "The integration will be fine..." — Run the full test suite. Always.
  • "I can merge their changes to the same file manually..." — No. One file, one owner.

Integration Points

SkillRelationshipWhen
task-decompositionUpstream — identifies independent task clustersBefore dispatching
subagent-driven-developmentComplementary — provides review gatesQuality gates for agent output
executing-plansUpstream — may delegate independent tasksDuring plan execution
verification-before-completionDownstream — verifies integrated resultAfter integration
code-reviewDownstream — reviews integrated changesAfter all agents complete
resilient-executionOn failure — retries failed agentsWhen individual agents fail

Parallelism Safety Rules Summary

RuleRationale
No two agents modify the same filePrevents merge conflicts and race conditions
No shared mutable stateEliminates data races
Each agent gets complete contextPrevents agents from exploring and stepping on each other
Define file boundaries explicitlyMakes ownership unambiguous
Review integration after completionCatches cross-cutting issues
Atomic commit for all changesAll in or all out
Always have a rollback pathKeep pre-dispatch state recoverable

Skill Type

RIGID — Follow this process exactly. Independence verification is mandatory. All four prompt sections are mandatory. Integration verification is mandatory. No shortcuts on parallelism safety.

平台分布

Codex

36.21%
按下载量换算85

Claude

29.87%
按下载量换算70

Cursor

18.12%
按下载量换算42

Gemini CLI

8.16%
按下载量换算19

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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