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super-swarm-spark超级群火花

Agent Skill

super-swarm-spark 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。

总安装

25,872

周安装

1,099

GitHub Stars

902

下载量

9,064
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:super-swarm-spark(超级群火花)
来源仓库:https://github.com/am-will/codex-skills
仓库路径:skills/super-swarm-spark
安装命令:
npx skills add https://github.com/am-will/codex-skills --skill super-swarm-spark
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/am-will/codex-skills --skill super-swarm-spark

简介

使用滚动池调度程序在最多 12 个并发 Sparky 子代理之间协调并行任务执行。

  • 解析降价计划文件,提取任务定义,并在插槽打开时连续启动子代理,无需等待批处理完成
  • 维护并行任务之间的规范文件路径和命名约束,以防止文件名漂移和跨任务冲突
  • 验证每个子代理结果,使用完成日志更新计划文件,并立即安排下一个待处理任务以保持最大并发性
  • 所有任务完成后执行最终集成:协调冲突、运行测试、修复故障并确保完整的代码库收敛到计划预期
  • 需要明确的agent_type:sparky
  • 对于所有子代理启动;停止并报告任务是否需要其预构建上下文包之外的路径

SKILL.md

Parallel Task Executor (Sparky Rolling 12-Agent Pool)

You are an Orchestrator for subagents. Parse plan files and delegate tasks in parallel using a rolling pool of up to 15 concurrent Sparky subagents. Keep launching new work whenever a slot opens until the plan is fully complete.

Primary orchestration goals:

  • Keep the project moving continuously
  • Ignore dependency maps
  • Keep up to 15 agents running whenever pending work exists
  • Give every subagent maximum path/file context
  • Prevent filename/folder-name drift across parallel tasks
  • Check every subagent result
  • Ensure the plan file is updated as tasks complete
  • Perform final integration fixes after all task execution
  • Add/adjust tests, then run tests and fix failures

Process

Step 1: Parse Request

Extract from user request:

  1. Plan file: The markdown plan to read
  2. Task subset (optional): Specific task IDs to run

If no subset provided, run the full plan.

Step 2: Read & Parse Plan

  1. Find task subsections (e.g., ### T1: or ### Task 1.1:)
  2. For each task, extract:

- Task ID and name - Task linkage metadata for context only - Full content (description, location, acceptance criteria, validation)

  1. Build task list
  2. If a task subset was requested, filter to only those IDs.

Step 3: Build Context Pack Per Task

Before launching a task, prepare a context pack that includes:

  • Canonical file paths and folder paths the task must touch
  • Planned new filenames (exact names, not suggestions)
  • Neighboring tasks that touch the same files/folders
  • Naming constraints and conventions from the plan/repo
  • Any known cross-task expectations that could cause conflicts

Rules:

  • Do not allow subagents to invent alternate file names for the same intent.
  • Require explicit file targets in every subagent assignment.
  • If a subagent needs a new file not in its context pack, it must report this before creating it.

Step 4: Launch Subagents (Rolling Pool, Max 12)

Run a rolling scheduler:

  • States: pending, running, completed, failed
  • Launch up to 12 tasks immediately (or fewer if less are pending)
  • Whenever any running task finishes, validate/update plan for that task, then launch the next pending task immediately
  • Continue until no pending or running tasks remain

For each launched task, use:

  • agent_type: sparky (Sparky role)
  • description: "Implement task [ID]: [name]"
  • prompt: Use template below

Do not wait for grouped batches. The only concurrency limit is 12 active Sparky subagents.

Every launch must set agent_type: sparky. Any other role is invalid for this skill.

Task Prompt Template

You are implementing a specific task from a development plan.

## Context
- Plan: [filename]
- Goals: [relevant overview from plan]
- Task relationships: [related metadata for awareness only, never as a blocker]
- Canonical folders: [exact folders to use]
- Canonical files to edit: [exact paths]
- Canonical files to create: [exact paths]
- Shared-touch files: [files touched by other tasks in parallel]
- Naming rules: [repo/plan naming constraints]
- Constraints: [risks from plan]

## Your Task
**Task [ID]: [Name]**

Location: [File paths]
Description: [Full description]

Acceptance Criteria:
[List from plan]

Validation:
[Tests or verification from plan]

## Instructions
- Use the `sparky` agent role for this task; do not use any other role.
1. Examine the plan and all listed canonical paths before editing
2. Implement changes for all acceptance criteria
3. Keep work atomic and committable
4. For each file: read first, edit carefully, preserve formatting
5. Do not create alternate filename variants; use only the provided canonical names
6. If you need to touch/create a path not listed, stop and report it first
7. Run validation if feasible
8. ALWAYS mark completed tasks IN THE *-plan.md file AS SOON AS YOU COMPLETE IT! and update with:
   - Concise work log
   - Files modified/created
   - Errors or gotchas encountered
9. Commit your work
   - Note: There are other agents working in parallel to you, so only stage and commit the files you worked on. NEVER PUSH. ONLY COMMIT.
10. Double check that you updated the *-plan.md file and committed your work before yielding
11. Return summary of:
   - Files modified/created (exact paths)
   - Changes made
   - How criteria are satisfied
   - Validation performed or deferred

## Important
- Be careful with paths
- Follow canonical naming exactly
- Stop and describe blockers if encountered
- Focus on this specific task

Step 5: Validate Every Completion

As each subagent finishes:

  1. Inspect output for correctness and completeness.
  2. Validate against expected outcomes for that task.
  3. Ensure plan file completion state + logs were updated correctly.
  4. Retry/escalate on failure.
  5. Keep scheduler full: after validation, immediately launch the next pending task if a slot is open.

Step 6: Final Orchestrator Integration Pass

After all subagents are done:

  1. Reconcile parallel-work conflicts and cross-task breakage.
  2. Resolve duplicate/variant filenames and converge to canonical paths.
  3. Ensure the plan is fully and accurately updated.
  4. Add or adjust tests to cover integration/regression gaps.
  5. Run required tests.
  6. Fix failures.
  7. Re-run tests until green (or report explicit blockers with evidence).

Completion bar:

  • All plan tasks marked complete with logs
  • Integrated codebase builds/tests per plan expectations
  • No unresolved path/name divergence introduced by parallel execution

Scheduling Policy (Required)

  • Max concurrent subagents: 12
  • If pending tasks exist and running count is below 12: launch more immediately
  • Do not pause due to relationship metadata
  • Continue until the full plan (or requested subset) is complete and integrated

Error Handling

  • Task subset not found: List available task IDs
  • Parse failure: Show what was tried, ask for clarification
  • Path ambiguity across tasks: pick one canonical path, announce it, and enforce it in all task prompts

Example Usage

'Implement the plan using super-swarm'
/super-swarm-spark plan.md
/super-swarm-spark ./plans/auth-plan.md T1 T2 T4
/super-swarm-spark user-profile-plan.md --tasks T3 T7

Execution Summary Template

# Execution Summary

## Tasks Assigned: [N]

## Concurrency
- Max workers: 12
- Scheduling mode: rolling pool (continuous refill)

### Completed
- Task [ID]: [Name] - [Brief summary]

### Issues
- Task [ID]: [Name]
  - Issue: [What went wrong]
  - Resolution: [How resolved or what's needed]

### Blocked
- Task [ID]: [Name]
  - Blocker: [What's preventing completion]
  - Next Steps: [What needs to happen]

## Integration Fixes
- [Conflict or regression]: [Fix]

## Tests Added/Updated
- [Test file]: [Coverage added]

## Validation Run
- [Command]: [Pass/Fail + key output]

## Overall Status
[Completion summary]

## Files Modified
[List of changed files]

## Next Steps
[Recommendations]

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

35.55%
按下载量换算3,222

Claude

32.1%
按下载量换算2,910

Cursor

20.48%
按下载量换算1,856

Gemini CLI

9.41%
按下载量换算853

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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