affaan-m/ECC

parallel-execution-optimizer

当用户希望通过并行工作、并发 agents、批量工具调用、隔离 worktree 或多条独立验证通道来大幅加速任务、同时不损失正确性时使用。

64Collecting
See how to use itView GitHub source
npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/parallel-execution-optimizer"
Automated source guide

Source checked Jul 28, 2026·Refresh due Oct 26, 2026

Reorganized from the pinned upstream SKILL.md

Turn parallel-execution-optimizer's source instructions into a guide you can follow

According to the pinned SKILL.md from affaan-m/ECC: 当速度来自同时处理相互独立的工作时,使用此技能: 仓库巡检、文件读取、API 检查、浏览器检查、构建/测试通道、 部署回读,或多 worktree 的实现批次。

npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/parallel-execution-optimizer"
Check the pinned source

Best fit

  • 当用户希望通过并行工作、并发 agents、批量工具调用、隔离 worktree 或多条独立验证通道来大幅加速任务、同时不损失正确性时使用。

Bring this context

  • A concrete task that matches the documented purpose of parallel-execution-optimizer.
  • The files, examples, or context the task depends on.
  • Your constraints, target environment, and definition of done.

Expected outputs

  • A result that follows the pinned parallel-execution-optimizer instructions.
  • A concise record of assumptions, inputs used, and unresolved questions.
  • A final check against the source workflow and relevant permission signals.

Key source sections

Read parallel-execution-optimizer through these 5 source sections

Sections are extracted automatically from the pinned SKILL.md and link back to the source.

01

核心模式

1. 定义目标和完成信号。 2. 把工作拆分成通道(lane)。 3. 给每条通道标注执行方式:并行、串行或门控。 4. 把相互独立的读取/检查放在一起执行。 5. 让写入按文件、worktree、分支、服务或数据集相互隔离。 6. 只有在证据表明各通道相互兼容后才合并。 7. 以一张验证表收尾,而不是一句模糊的"变快了"。

SKILL.md · 核心模式
定义目标和完成信号。把工作拆分成通道(lane)。给每条通道标注执行方式:并行、串行或门控。
02

通道矩阵

Review the “通道矩阵” section in the pinned source before continuing.

SKILL.md · 通道矩阵
Review and apply the “通道矩阵” source section.
03

执行规则

把文件读取、搜索、状态检查和元数据查询批量化。

SKILL.md · 执行规则
把文件读取、搜索、状态检查和元数据查询批量化。对大型且互不相关的实现通道使用隔离的 worktree。长时间运行的测试、构建、回填和部署放到独立会话中启动,
04

输出形态

Review the “输出形态” section in the pinned source before continuing.

SKILL.md · 输出形态
Review and apply the “输出形态” source section.
05

失败模式

更多并发反而制造了相互冲突的编辑。

SKILL.md · 失败模式
更多并发反而制造了相互冲突的编辑。在给工具跑分,而不是在完成任务。在正确性得到证明之前就把"快"当成"做完了"。

SkillSignal prompt templates

Provide the task, context, and acceptance criteria

These prompts were written by SkillSignal from the source structure; they are not upstream text.

Task-start prompt

Confirm source fit, inputs, and outputs before acting.

Use parallel-execution-optimizer to help me with: [specific task]. Context: [files, data, or background]. Constraints: [environment, scope, and prohibited actions]. Before acting, check the pinned SKILL.md and explain which sections apply, what inputs are still missing, and what you will deliver.

Source-guided execution

Make the Agent explicitly follow the key extracted sections.

Apply the pinned parallel-execution-optimizer source to [task]. Pay particular attention to these source sections: “核心模式”, “通道矩阵”, “执行规则”, “输出形态”, “失败模式”. Preserve the important decision at each step. Mark facts not covered by the source as “needs confirmation” instead of inventing them. Then verify the result against my acceptance criteria: [criteria].

Result-review prompt

Check omissions, permissions, and source drift before delivery.

Review the current parallel-execution-optimizer result: (1) does it satisfy the original task; (2) were any applicable steps or limits in the pinned SKILL.md missed; (3) did it perform any unauthorized file, command, network, or data action; and (4) which conclusions remain unverified? List issues first, then fix only what the source or user authorization supports.

Output checklist

Verify each item before delivery

The task matches the purpose documented in the SKILL.md.

The source section “核心模式” has been checked.

The source section “通道矩阵” has been checked.

The source section “执行规则” has been checked.

The source section “输出形态” has been checked.

Inputs, constraints, and acceptance criteria are explicit.

Unverified facts, compatibility, and outcome claims are clearly marked.

Any file, command, network, or data action has been reviewed.

Choose a different workflow

When another Skill is the better fit

parallel-execution-optimizer

Use when the user wants a task done much faster through parallel work, concurrent agents, batched tool calls, isolated worktrees, or many independent verification lanes without losing correctness.

A separate implementation from affaan-m/ECC; compare its source, maintenance signals, and permission requirements.

Open source detail

ab-testing

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program

A separate implementation from coreyhaines31/marketingskills; compare its source, maintenance signals, and permission requirements.

Open source detail

churn-prevention

When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o

A separate implementation from coreyhaines31/marketingskills; compare its source, maintenance signals, and permission requirements.

Open source detail

FAQ

What does parallel-execution-optimizer do?

当速度来自同时处理相互独立的工作时,使用此技能: 仓库巡检、文件读取、API 检查、浏览器检查、构建/测试通道、 部署回读,或多 worktree 的实现批次。

How do I start using parallel-execution-optimizer?

The catalog detected this source-specific install command: npx skills add https://github.com/affaan-m/ECC --skill "docs/zh-CN/skills/parallel-execution-optimizer". Inspect the command and pinned source before running it.

Which Agent platforms does it declare?

No dedicated Agent platform is declared in the pinned source record.

Repository stars
234,327
Repository forks
35,711
Quality
64/100
Source repository last pushed

Quality breakdown

Based on traceable docs and repository signals; stars are not treated as quality.

64/100
Documentation17/30
Specificity15/25
Maintenance20/20
Trust signals12/25

Compare before choosing

Related Agent Skills and source variants

These links are selected from shared tasks, functions, stacks, platforms, and same-name variants. Compare the source owner, documentation, permissions, and maintenance signals.

parallel-execution-optimizer by affaan-m

Use when the user wants a task done much faster through parallel work, concurrent agents, batched tool calls, isolated worktrees, or many independent verification lanes without losing correctness.

ab-testing by coreyhaines31

When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program

churn-prevention by coreyhaines31

When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o

design-intelligence by event4u-app

Grounded design brief from the adopted corpus — style, WCAG-checked color tokens, typography, layout pattern, anti-patterns. Use on ui-design-brief or any which-style/palette/font/chart decision.

design-system-capture by event4u-app

Write and maintain DESIGN.md + PRODUCT.md — captures visual decisions and interaction patterns so design tasks stay consistent across sessions without re-scanning past work.

View original Skill.mdThis page is parsed directly from the repository SKILL.md without editorial rewriting. Collected: Jul 28, 2026 · about 1 min

并行执行优化器

当速度来自同时处理相互独立的工作时,使用此技能: 仓库巡检、文件读取、API 检查、浏览器检查、构建/测试通道、 部署回读,或多 worktree 的实现批次。

核心模式

行动之前,先把紧迫感转化为依赖图。

  1. 定义目标和完成信号。
  2. 把工作拆分成通道(lane)。
  3. 给每条通道标注执行方式:并行、串行或门控。
  4. 把相互独立的读取/检查放在一起执行。
  5. 让写入按文件、worktree、分支、服务或数据集相互隔离。
  6. 只有在证据表明各通道相互兼容后才合并。
  7. 以一张验证表收尾,而不是一句模糊的"变快了"。

通道矩阵

在大规模推进之前,写一张紧凑的矩阵:

Lane | Can run in parallel? | Write surface | Risk | Verification
Repo scan | yes | none | low | rg/git status outputs
Backend patch | maybe | src/api | medium | unit tests
Frontend patch | maybe | app/components | medium | browser screenshot
Deploy readback | after build | remote service | high | live URL + logs

只有当各通道的写入面互不冲突时,才并行运行。

执行规则

  • 把文件读取、搜索、状态检查和元数据查询批量化。
  • 对大型且互不相关的实现通道使用隔离的 worktree。
  • 长时间运行的测试、构建、回填和部署放到独立会话中启动, 然后有节奏地主动轮询。
  • 如果某条通道发现了会改变计划的阻塞点,暂停依赖它的通道 并更新矩阵。
  • 除非用户明确要求持续运行的服务,绝不让后台进程存活超过本轮。
  • 没有明确门控时,不要并行执行破坏性命令、数据迁移、对同一张表的写入, 或影响线上客户的部署。

输出形态

汇报时使用:

Parallel execution result:
- Lanes run: 5
- Lanes completed: 4
- Blocked lane: deploy readback, waiting on DNS propagation
- Fast path found: batched repo scan + focused tests
- Verification: lint pass, unit pass, live smoke pass

失败模式

  • 更多并发反而制造了相互冲突的编辑。
  • 在给工具跑分,而不是在完成任务。
  • 在正确性得到证明之前就把"快"当成"做完了"。
  • 忘记轮询正在运行的会话。
  • 用一句成功摘要掩盖被跳过的检查。
Source repo
affaan-m/ECC
Skill path
docs/zh-CN/skills/parallel-execution-optimizer/SKILL.md
Commit SHA
4e973d3eaf92
Repository license
MIT
Data collected