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Agent Skill · 开发

agent-dev-workflow(Agent 开发工作流程)

agent-dev-workflow 用于辅助前端页面、组件、样式和交互逻辑开发,适合在 OpenClaw 中需要维护前端项目、生成组件或检查界面实现时使用。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。

agent-dev-workflow 是开发类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 4,031。

总安装 9,290周安装 391GitHub Stars 公开资料未说明下载 3,253核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.2.0

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:agent-dev-workflow(Agent 开发工作流程)
来源仓库:https://github.com/lgyanami/agent-dev-workflow
安装命令:
openclaw skills install agent-dev-workflow
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 agent-dev-workflow

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

Agent Dev Workflow 编排编码代理执行结构化开发任务。适合维护前端项目、生成组件或审查界面实现时使用。整合 Claude Code 等工具链,提升代码质量与交付效率。安装命令:openclaw skills install agent-dev-workflow,需配合项目技术栈使用。

应避免直接修改未经验证的配置文件,防止破坏现有构建流程。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install agent-dev-workflow;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

agent-dev-workflow 怎么安装?

在终端执行 openclaw skills install agent-dev-workflow。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

agent-dev-workflow 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

agent-dev-workflow 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

agent-dev-workflow 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

agent-dev-workflow 用的人多吗?

公开数据是累计安装 9,290 次,近一周安装 391 次,下载 3,253 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

agent-dev-workflow 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理开发类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
agent-dev-workflow

Agent 开发工作流程 · 本页

9,290—需要联网MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
dev-workflow
description
Orchestrate coding agents (Claude Code, Codex, etc.) to implement coding tasks through a structured workflow. Use when the user gives a coding requirement, feature request, bug fix, or GitHub issue to implement. Includes requirement analysis, document generation (requirement doc + verification doc), agent dispatch, monitoring, verification, and delivery. NOT for simple one-line fixes or reading code. Triggers on coding tasks, feature requests, bug reports, GitHub issues, or "implement/build/fix this".

Dev Workflow — Orchestrated Coding Agent Dispatch

Structured 6-phase gated workflow for driving coding agents to implement requirements with quality control.

Prerequisites

  • Claude Code (claude CLI) installed with --permission-mode bypassPermissions --print
  • cc-plugin installed in Claude Code (provides llmdoc read/write, investigator/scout/recorder sub-agents)
  • Global ~/.claude/CLAUDE.md configured with cc-plugin settings

Workflow Overview

Phase 1: Environment Check
    ↓
Phase 2: Spec  ← spec-writer skill
    ↓ [user confirms]
Phase 3: Task Planning
    ↓ [user confirms]
Phase 4: Agent Dispatch
    ↓
Phase 5: Verification
    ↓
Phase 6: Delivery

Each phase must complete before moving to the next. Phase 2 and Phase 3 have explicit user confirmation gates.


Phase 1: Environment Check

Before any work, check the target project:

  1. llmdoc/ exists?

- Yes → read llmdoc/index.md + overview files to understand project - No → dispatch Claude Code with /tr:initDoc to generate it first

  1. CLAUDE.md in project root? — verify cc-plugin config is present; fix if missing
  2. git status — ensure working tree is clean enough to work on

Phase 2: Spec

Generate a structured implementation spec using the spec-writer skill.

  1. Activate spec-writer skill — read its SKILL.md and follow its workflow
  2. It will gather project context, draft a spec using its template, and present to the user
  3. The spec covers: objectives, user stories, technical plan, boundaries, verification criteria, and a preliminary task breakdown
  4. 🚫 Gate: Do not proceed until the user confirms the spec.

The confirmed spec replaces the old requirement-doc + verification-doc pair — everything is in one document now.

Fallback: If spec-writer skill is not installed, use the templates in references/ (requirement-template.md + verification-template.md) as before.

Phase 3: Task Planning

Refine the spec's preliminary task breakdown into a precise, executable task list. This is the bridge between "what to build" and "how to tell the agent."

3.1 Extract Tasks from Spec

Start from Section 10 (Task Breakdown) of the confirmed spec. For each task, expand it into a Task Card:

### Task [#]: [Title]

**Objective:** What this task accomplishes (one sentence)
**Input:** What must exist before this task starts (files, tables, APIs from prior tasks)
**Output:** What this task produces (new/modified files, passing tests, working endpoint)
**Affected files:**
- `src/xxx.py` — create / modify
- `tests/test_xxx.py` — create

**Agent instructions:**
- [Specific, actionable instruction 1]
- [Specific, actionable instruction 2]
- Reference: [relevant spec section, e.g., "See Spec §4.2 for design decision"]

**Verification:**
- [ ] [How to confirm this task is done — a command, a test, an observable result]

**Depends on:** Task #X, #Y (or "none")
**Complexity:** Low / Medium / High
**Parallel:** Can run in parallel with Task #Z (or "no")
3.2 Scoping Rules

Each task should be:

  • Independently implementable — an agent can complete it without context from other incomplete tasks
  • Independently verifiable — there is a concrete way to check it worked (test passes, endpoint responds, file exists)
  • Small enough to review — aim for changes reviewable in one pass (rough guide: <300 lines changed)
  • Large enough to be meaningful — don't split a 20-line function into 3 tasks

Splitting heuristics:

  • If a task touches >3 unrelated modules → split by module
  • If a task has both "create infrastructure" and "implement logic" → split
  • If a task requires multiple design decisions → split by decision boundary
  • If you can describe two independent verification criteria → likely two tasks
3.3 Dependency Graph

After expanding all tasks, produce a dependency summary:

Task 1 (Low)  ─┐
Task 3 (Low)  ─┤─→ Task 5 (Medium) ─→ Task 7 (Medium)
Task 2 (Medium) ─→ Task 4 (Medium) ─┤
Task 6 (High) ────────────────────────┘─→ Task 8 (Medium)

Identify:

  • Critical path — longest chain of dependent tasks
  • Parallel groups — tasks that can run simultaneously
  • Execution order — the sequence to dispatch agents
3.4 Context Budgeting

For each task, determine what context the agent needs:

  • Spec sections to include — only the relevant parts, not the full spec (avoid context overload)
  • Existing code to reference — specific files, not "the whole src/"
  • Boundaries to emphasize — the ✅/⚠️/🚫 rules most relevant to this task

Principle: feed the agent only what it needs for the current task. A well-fed agent is like a well-fed function — give it only the inputs for the job at hand.

3.5 User Confirmation

Present the task list to the user with:

  • All task cards (or a summary table + full cards on request)
  • Dependency graph
  • Estimated execution order (serial vs parallel)
  • Highlight the critical path

🚫 Gate: Do not dispatch any agents until the user confirms the task plan.

Common discussion points:

  • Is the granularity right? (too fine → overhead; too coarse → risky)
  • Are dependencies correct? Can anything be parallelized further?
  • Any task missing from the spec's intent?

Phase 4: Agent Dispatch

Execute the confirmed task plan by dispatching coding agents.

4.1 Prompt Construction

For each task, construct the agent prompt from the task card:

claude --permission-mode bypassPermissions --print '<task prompt>' 2>&1

Task prompt structure:

## Task: [Title]

### Objective
[From task card]

### Context
[Relevant spec sections — copy only what's needed]
[Relevant existing code snippets or file references]

### Instructions
[Agent instructions from task card]

### Constraints
- 不要 git commit
- 完成后执行 /update-doc 更新 llmdoc
- [Relevant boundaries from spec §7]

### Verification
When done, confirm:
- [Verification criteria from task card]

Use workdir to scope the agent to the project directory. Use background: true for long-running tasks, monitor with process tool.

4.2 Execution Strategy
  • Serial tasks (has dependencies): wait for dependency to complete and verify before dispatching
  • Parallel tasks (independent): dispatch simultaneously, use git worktrees if touching overlapping files
  • After each task completes:

1. Check agent output for errors 2. Run the task's verification criteria 3. If verification fails → re-prompt the agent with the failure details (up to 2 retries) 4. If still fails → stop and report to user

4.3 Error Handling
SituationAction
Small error (syntax, typo, missing import)Re-prompt agent to fix, no user interruption
Test failure on the current taskRe-prompt with test output, up to 2 retries
Design-level issue or ambiguityStop and ask the user
Agent produces output that contradicts specStop, quote the spec conflict, ask user
Downstream task blocked by upstream failurePause dependent tasks, attempt to fix upstream first

Phase 5: Verification

After all tasks complete, verify the whole against the spec's verification criteria (Section 9):

  1. Automated checks (§9.1) — run tests, build, lint, type check
  2. Functional verification (§9.2) — execute each test scenario step by step
  3. Edge cases & error handling (§9.3) — verify each edge case
  4. Regression (§9.4) — confirm existing functionality unaffected
  5. Code quality — style consistency, no stray files, no hardcoded secrets

If any verification fails:

  • Identify which task(s) caused the issue
  • Re-dispatch agent to fix, providing the failure context
  • Re-verify after fix

Phase 6: Delivery

Present results to the user with:

  1. All changed files — every file touched, including llmdoc updates, config changes, everything
  2. Suggested commit message — conventional commits format
  3. Task completion summary — which tasks passed, any retries needed
  4. Verification results — what passed, any caveats
  5. Items for human review — what needs the user's attention

Never commit. The user handles all git commits.

Agent Selection

Default: Claude Code (claude --permission-mode bypassPermissions --print)

AgentUse when
Claude CodeDefault for all tasks; complex reasoning, architecture
CodexUser explicitly requests; batch/parallel tasks (pty:true, --full-auto)
OpenCode/PiUser explicitly requests

Key Constraints

  • Never commit — code changes only, user commits
  • Never run agents in ~/.openclaw/ — agents will read soul/identity files
  • Always update llmdoc — every agent run should end with doc update
  • Always list all changed files on delivery
  • Always provide commit message on delivery
  • Interrupt on design issues — don't let agents drift on wrong assumptions
  • Feed minimal context — each agent gets only spec sections and files relevant to its task

平台分布

OpenClaw

96.89%
按下载量换算3,152

安全审计

ClawScan

未展示

Static analysis

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。目前只有一个公开来源,建议同时核对源仓库。

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