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workflow-execution工作流程执行

Agent Skill

workflow-execution 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

3,575

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152

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OpenClaw

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

MIT-0

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:workflow-execution(工作流程执行)
来源仓库:https://github.com/levineam/workflow-execution
安装命令:
openclaw skills install workflow-execution
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install workflow-execution

简介

workflow-execution 提供重要工作的计划优先与上下文打包管理方案。

  • 适用于关键任务拆解、跟踪问题创建和文档化协作场景。
  • 自动决定代码存放位置,并将上下文打包为可复用知识资产。
  • 安装命令为 openclaw skills install workflow-execution,适合重复性高的重要项目。
  • 建议结合版本控制与 CI/CD 流程,确保计划变更可追溯可回滚。

SKILL.md

name
workflow-execution
description
>

Workflow Execution

Run this workflow for any meaningful work. The core loop: plan → track → package context → route → hand off → execute → verify.

Core Principles

  • Plan before acting. The plan lives on the tracking issue, not in chat.
  • Package context as documents, not spawn strings. The executing agent should never depend on chat history.
  • Decide where code lives before writing any code.
  • Prefer the simplest approach that can pass verification.
  • Be explicit about proof, not optimism.

Phase 1: Plan

Enter planning before acting when any trigger is true:

  • Work requires 3 or more concrete steps
  • Work changes architecture, interfaces, data flow, or shared contracts
  • Work includes risky edits (security, auth, migrations, destructive operations, production config, or unknown blast radius)
  • Work will be handed off to another agent or subagent

Plan contents

  1. Goal — one sentence describing what done looks like.
  2. Done criteria — explicit, checkable conditions. Not "it works" but "tests pass, PR merged, deployed."
  3. Constraints — what must not break, budget limits, timeline, dependencies.
  4. Failure modes — what could go wrong and how you'll detect it.
  5. Ordered steps — small, each with a verification method (test, build, smoke check, log proof, diff).

Phase 2: Track

Before implementation starts, create or reference a tracking issue in your project management system.

What to do

  1. Create an issue with a clear title and the goal from Phase 1.
  2. Attach the plan as a document on the issue (key: plan). This is the source of truth — not a chat message, not a comment, a structured document.
  3. Link to parent issues if this work is part of a larger effort.

Why documents, not descriptions

  • Documents are revisioned — you can see how the plan evolved.
  • Documents are keyedplan, design, context each have a clear role.
  • Documents are agent-readable — any agent that picks up the issue gets the full context.
  • Documents survive context resets — when a session compacts or a new agent spawns, the context lives on the issue, not in memory.

Tracker reference implementations

This skill is tracker-agnostic. See references/ for how to do this with specific systems:

  • references/tracker-paperclip.md — Paperclip Issues + Documents API
  • references/tracker-github.md — GitHub Issues + issue body/comments
  • references/tracker-none.md — skip tracking, plan in a local file

Phase 3: Package Context

Before handing off to an executing agent, attach structured documents to the tracking issue:

Required: plan document

The plan from Phase 1. Always attached.

When applicable: design document

Attach when work involves:

  • New interfaces or API contracts
  • Architecture decisions with tradeoffs
  • User-facing UI/UX (include design brief: user flow, empty/loading/error states, copy, responsive behavior, accessibility)

When applicable: context document

Attach when the executing agent needs background that isn't obvious from the code:

  • Prior decisions and their rationale
  • Relevant code references (files, functions, patterns to follow)
  • Domain knowledge the agent won't have
  • Links to related issues or discussions

Packaging principle

Ask: *"If a brand new agent picked up this issue with zero chat history, could they do the work?"* If not, add more context documents.


Phase 4: Route

Before execution, decide where the code lives.

Decision criteria

SignalDestination
Work extends an existing project/repoExisting repo — branch off main
Work is reusable, publishable, or useful to othersNew repo — create it, then work there
Work is pure local glue, config, or one-off automationLocal workspace — but document why it's local

Routing rules

  • Default: existing repo. Most work extends something that already exists.
  • New repo trigger: If you find yourself thinking "other people could use this" or "this should be a skill/package," it's a new repo.
  • Local-only justification required. If code stays in the local workspace, document why — it should be because it's genuinely specific to this setup, not because it was easier.
  • Branch naming: Include the tracking issue identifier in the branch name (e.g., SUP-490/skill-rewrite).

Phase 5: Hand Off

Spawn the executing agent with an issue reference, not inline context.

Dispatch rule

Code handoffs MUST use sessions_spawn, not sessions_send.

sessions_spawn triggers the full enforcement pipeline (Lobster gate, spawn-code-lint, post-spawn PR creation). sessions_send bypasses all of it. Use sessions_send only for non-code work: status checks, coordination, questions.

The test: if the message asks the target agent to write, edit, or move codesessions_spawn. Everything else → sessions_send is fine.

Handoff protocol

  1. The spawn message includes: the tracking issue identifier, the repo/branch to work in, and any model/thinking preferences.
  2. The executing agent's first step is: read the issue, read attached documents (plan, design, context), then proceed.
  3. The executing agent updates the issue as it works — comments for progress, status changes for state transitions.

Subagent strategy

  • Spawn by default when work spans multiple files/systems, requires research, or includes long-running operations.
  • One clear objective per subagent with concrete deliverables.
  • Clean ownership boundaries — avoid overlapping edit zones.
  • Prefer fewer, well-scoped subagents over many tiny ones.

Phase 6: Execute

Minimal-impact changes

  • Implement the smallest change set that satisfies the goal.
  • Reuse existing patterns before inventing new abstractions.
  • Keep naming, structure, and style consistent with local code.
  • Avoid incidental cleanup unless it directly reduces risk.

Failure recovery hierarchy

When something goes wrong during execution, follow this priority order:

  1. Transient provider failure (429, timeout, model overload): OpenClaw's native

model fallback chain handles this automatically. Do not change tracker issue status. Continue in the same session once the request succeeds.

  1. Context reset or compaction: Re-read the plan, context, and design

documents from the tracking issue. Never reconstruct plan state from in-session memory after compaction — the issue documents are the source of truth.

  1. Durable blocker (missing dependency, unclear requirements, architectural gap):

Update the tracking issue status to blocked. Add a comment naming the specific blocker and what needs to resolve it.

  1. The tracker is an audit trail and coordination hub — not the place to manage transient retries.

Do not flip status on transient errors, partial progress, or model fallbacks.

Autonomous bug-fix behavior (guardrailed)

When bugs appear during execution:

  1. Reproduce and isolate the failing path.
  2. Form the smallest plausible fix hypothesis.
  3. Apply minimal-touch patch.
  4. Re-run impacted checks and one nearby regression check.
  5. Repeat until pass or a guardrail is hit.

Stop and escalate when:

  • Root cause remains unclear after multiple attempts.
  • Fix requires major architectural change.
  • Risk of data loss or security impact is non-trivial.

Demand elegance (balanced)

  • Reject hacks that create hidden fragility or repeat incidents.
  • Prefer clear structure over clever shortcuts.
  • Scale sophistication to task size — don't over-engineer obvious fixes.

Phase 7: Verify

Do not mark complete without proof.

Evidence types

  • Tests: targeted unit/integration/e2e checks.
  • Static checks: lint, typecheck, build.
  • Runtime checks: smoke test key affected flows.
  • Logs/output: command results or excerpts showing success.
  • Diff sanity: verify only intended files changed.

Governance

  • Significant code changes: branch + PR + review before merge.
  • CI must pass before merge.
  • Fix review comments before closing.

Close the loop

  1. Update the tracking issue status to done.
  2. Add a closing comment with verification evidence.
  3. If the work produced a reusable lesson, capture it durably.

Self-Correction Loop

If the correction cycle was triggered by a context reset or compaction, re-read the issue's plan, context, and design documents before resuming — do not reconstruct plan state from in-session memory.

After any correction cycle (failed check, rework, rollback):

  1. Record what failed and why (brief, concrete).
  2. Extract one reusable lesson/pattern.
  3. Apply that lesson immediately to remaining work.
  4. Capture a durable note when the lesson is broadly reusable.

Quick Checklist (Repeat Each Run)

  • [ ] Plan: goal, done criteria, constraints, failure modes, ordered steps
  • [ ] Track: issue created/referenced, plan document attached
  • [ ] Package: context documents attached (design, context as needed)
  • [ ] Route: code destination decided, branch created with issue ID
  • [ ] Hand off: agent spawned with issue reference, not inline context
  • [ ] Execute: minimal-impact implementation
  • [ ] Verify: evidence collected, checks pass, governance followed
  • [ ] Close: issue updated, evidence in closing comment, lessons captured

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能力 5

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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。

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