Super Swarm Spark

am-will/codex-skills/skills/super-swarm-spark

作者 am-will9f954c3b63fda0d1875252009c196bf15072c1ca無授權條款1K 個星標收錄於 2026年10月9日更新於 2026年10月9日儲存庫2 個月前更新

Only to be triggered by explicit super-swarm-spark commands.

僅含說明AI & Agents
AI 產生的概覽

依據 markdown 計畫編排並行的 Sparky 子代理,使用最多 12 個並行工作者的滾動池。

功能
將 markdown 計畫檔案解析為任務,為每個任務建立包含標準檔案與資料夾路徑的脈絡包,並透過滾動排程器啟動 Sparky 子代理,在任務完成時立即補上空位。它會驗證每次完成情況,在並行工作中強制統一命名,並在任務完成時更新計畫檔案。全部任務結束後執行整合處理,新增或調整測試,執行測試並修正失敗,直到通過或回報阻塞。
適用情境
適用於開發計畫檔案中包含多個可獨立並行執行的子代理任務的情境。它面向明確的 super-swarm-spark 指令,可僅限於指定的任務 ID 子集。適合需要並行代理避免檔名與資料夾命名漂移,並期望最終進行整合與測試的情境。
執行需求
不附帶指令碼,僅為指示。需要一份 markdown 計畫檔案、能夠以 sparky 代理角色啟動子代理的能力,以及一個可供子代理讀取、編輯與提交檔案的程式碼儲存庫。

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)
  3. Build task list
  4. 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 editing2. Implement changes for all acceptance criteria3. Keep work atomic and committable4. For each file: read first, edit carefully, preserve formatting5. Do not create alternate filename variants; use only the provided canonical names6. If you need to touch/create a path not listed, stop and report it first7. Run validation if feasible8. 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 encountered9. 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 yielding11. 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

markdown
# 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]

來源與署名

來源:am-will/codex-skills位於skills/super-swarm-spark提交9f954c3

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