返回顶部
b

batch-executor批量执行器

Full batch processor for corpus-scale task execution. Handles Google Drive dumps, ChatGPT exports, Apple Notes, or any large collection of mixed content (ideas + instructions + references + noise). Classifies items, spawns sub-agents for heavy work, checkpoints progress, and never loses input. Option C of the task management system. Use for 20+ items or when input is a file/folder dump rather than a chat message.

作者: admin | 来源: ClawHub
源自
ClawHub
版本
V 1.0.0
安全检测
已通过
80
下载量
免费
免费
0
收藏
概述
安装方式
版本历史

batch-executor

Batch Executor

Corpus-scale processing: classify → prioritize → spawn → checkpoint → reconcile.

Unlike task-extractor (for 3-12 inline tasks) or batch-cognition (for idea analysis), this skill EXECUTES at scale with sub-agent parallelism.

When to Use

  • - Google Drive folder dump (mixed docs, notes, spreadsheets)
  • ChatGPT conversation export (3K+ prompts)
  • Apple Notes dump (years of ideas)
  • Any input > 20 items or > 10K tokens of raw content
  • File-based input (not inline chat messages — use task-extractor for those)

Architecture

CODEBLOCK0

Phase 1: INGEST

Save ALL raw input to systems/batch-executor/corpus/YYYY-MM-DD-SOURCE.md BEFORE any processing.

For file inputs:

  • - PDF → extract text via pdf tool
  • CSV/JSON → parse, one item per row/object
  • Markdown → split on ## headers or --- separators
  • ChatGPT export → parse conversations.json, group by chain_id
  • Google Drive → process each file, flatten into items

Create the manifest:
CODEBLOCK1

Phase 2: CLASSIFY

For each item, assign:

TypeDescriptionAction
TASKHas a clear action verb + deliverableEXECUTE
IDEA
Speculative, "what if", product concept | SCORE (ICE) |
| REFERENCE | Link, citation, spec, documentation | CATALOG |
| DECISION | "We decided X", "going with Y" | RECORD |
| HALF_THOUGHT | Fragment, incomplete, trails off | COMPLETE then re-classify |
| MODEL_OUTPUT | AI-generated, assistant voice | EXTRACT core idea, discard wrapper |
| DUPLICATE | Same as item #X | MERGE |
| NOISE | Test, filler, meta-commentary | SKIP |

Effort per item:

  • - TRIVIAL (< 1 min): file rename, note capture, config change
  • QUICK (1-5 min): web search, small edit, API call
  • MEDIUM (5-30 min): build a page, write a doc, research topic
  • HEAVY (30+ min): full app build, deep research, multi-step workflow
  • BLOCKED: needs human input, credentials, or external dependency

Update manifest with Type + Effort columns.

Phase 3: TRIAGE

Score each TASK and IDEA using quick ICE:

  • - I (Impact): 1-5 — how much does this move the needle?
  • C (Cost): 1-5 — how cheap/fast to do? (inverted: 5 = trivial)
  • E (Exploit): 1-5 — how quickly does this produce value?
  • Score = I × C × E (max 125)

Sort by score descending. Group by dependency chains.

Create execution plan:
CODEBLOCK2

Phase 4: EXECUTE

Rules:

  1. 1. Max 3 sub-agents concurrent. Wait for one to complete before spawning another.
  2. QUICK items: execute inline (no sub-agent overhead for < 5 min tasks).
  3. MEDIUM/HEAVY items: spawn sub-agent with clear task description + acceptance criteria.
  4. Each sub-agent gets: the item content, relevant context from other items, and the target artifact path.
  5. Track in manifest: status → EXECUTING, then ✅ DONE / ❌ FAILED / ⚠️ PARTIAL.

Sub-agent spawn template:
CODEBLOCK3

Checkpoint every 5 completed items:

  • - Update manifest
  • Report to user: "[X]/[N] done. [Y] in progress. Top findings so far: [...]"
  • If user is idle (no response in 30s), continue
  • Commit progress to git

Phase 5: RECONCILE

After all waves complete (or all sub-agents return):

  1. 1. Re-read manifest
  2. For each ❌ FAILED: log reason, decide retry or escalate
  3. For each 🔄 sub-agent still running: check status, kill if stale (> 30 min no progress)
  4. For each ⚠️ PARTIAL: note what's left
  5. Retry failed items once (different approach if possible)

Phase 6: REPORT

Generate final report at systems/batch-executor/reports/YYYY-MM-DD-SOURCE-report.md:

CODEBLOCK4

Append to systems/batch-cognition/value-stack.md (shared with batch-cognition skill).
Log learnings to .learnings/LEARNINGS.md.

Commands

INLINECODE8 — show manifest progress
pause — stop spawning, let running agents finish
resume — continue from where we left off (re-read manifest)
skip [#] — skip item number
retry [#] — retry failed item
block [#] [reason] — mark as blocked
priority [#] — move item to top of queue
done — trigger report even if items remain

Key Rules

  1. 1. INGEST FIRST. Raw content hits disk before ANY processing.
  2. Max 3 concurrent sub-agents. More = chaos, dropped results, context confusion.
  3. Checkpoint every 5. Git commit progress. User update.
  4. Never mark ✅ without artifact evidence. File exists, build passes, URL responds.
  5. NOISE is not failure. Skipping noise is correct behavior. Report it transparently.
  6. Corpus items cross-reference. Item #14 may be context for item #27. Pass relevant context to sub-agents.
  7. Resume is first-class. If session dies, resume re-reads manifest and continues from last checkpoint.
  8. ICE scoring is fast. 30 seconds per item max. Don't overthink triage — execute.

Integration with Other Skills

  • - task-extractor: For inline chat messages (3-12 items). Batch-executor is for file/corpus scale (20+).
  • batch-cognition: For idea analysis (THINK-heavy). Batch-executor is for execution (PLAY-heavy).
  • orchestrator: Batch-executor can be invoked BY the orchestrator when it detects a corpus dump.
  • recorder: After batch-executor completes, route to recorder to update STATUS.md.

标签

skill ai

通过对话安装

该技能支持在以下平台通过对话安装:

OpenClaw WorkBuddy QClaw Kimi Claude

方式一:安装 SkillHub 和技能

帮我安装 SkillHub 和 batch-executor-1775923149 技能

方式二:设置 SkillHub 为优先技能安装源

设置 SkillHub 为我的优先技能安装源,然后帮我安装 batch-executor-1775923149 技能

通过命令行安装

skillhub install batch-executor-1775923149

下载

⬇ 下载 batch-executor v1.0.0(免费)

文件大小: 4.25 KB | 发布时间: 2026-4-12 09:08

v1.0.0 最新 2026-4-12 09:08
First release. Corpus-scale task execution with sub-agent waves, ICE triage, and checkpointing. Handles Google Drive, ChatGPT exports, Apple Notes dumps.

Archiver·手机版·闲社网·闲社论坛·羊毛社区· 多链控股集团有限公司 · 苏ICP备2025199260号-1

Powered by Discuz! X5.0   © 2024-2025 闲社网·线报更新论坛·羊毛分享社区·http://xianshe.com

p2p_official_large
返回顶部