跳到正文
cccskills
免费在 GitHub 公开中文介绍

dynamic-workflow-mode

为重复的代理任务设计专用执行流程,整理目标、输入输出、合格检查、进度记录与交接信息,并帮助将多个团队或项目共用的流程整理成共享技能。

原文查看原文说明

Design task-local harnesses, eval gates, and reusable skill extraction for Claude dynamic workflow mode and other adaptive agent harnesses. Use when building a task-local harness, adding eval gates, or extracting a reusable skill from ad-hoc work.

AI 评分100分/ 100查看安装方法

适用场景

  • 设计重复任务的执行流程
  • 为流程加入合格与否的检查
  • 将重复步骤整理为共享技能
  • 整理跨会话进度与交接信息

中文介绍

功能

此技能为重复的代理任务设计专用执行框架,即支撑任务运行的机制。它整理目标、输入、成果、合格与否的检查及交接信息,规定从核对当前状态、更新成果,到验证和记录的完整流程。对于多个团队或项目共同使用的步骤,也会帮助判断是否应整理为共享的SKILL.md。

适用场景

适合更换输入后反复执行同一任务,或需要多个代理遵循一致流程的情况。任务跨越多个会话时,它会记录计划、负责人、执行状态、验证结果和未解决事项,为下一位接手者准备恢复工作所需的信息。

使用示例

  • “请整理这个重复任务的目标与输入输出,设计专用执行流程和合格检查。”
  • “请将经常使用的步骤整理为共享技能,并准备验证方法与交接信息。”

注意事项

一次性任务直接处理,不另建专用机制。存在安全风险的任务需要设置基于评估的停止条件,并在合并前取得人工批准。只有其他接手者也能重新执行验证,流程才能作为共享技能使用。

本介绍由 AI(OpenAI Codex)根据公开的 SKILL.md 撰写。准确的规格请查看下方原文。

客观评估

AI 仅根据 SKILL.md 的内容,从 4 个方面进行了评估。星标数和热度不计入评估。

指令清晰度能否看出何时使用、做什么
A良好明确说明专用执行框架设计、增加评估关卡及将重复流程提取为共享技能等用途。
步骤具体性步骤、输入输出和示例是否具体
A良好提供决策步骤、执行循环模板、按任务类型划分的评估方法及成果报告项目。
安全性发送数据、删除文件、执行命令等是否有说明
A良好要求遇到不安全的外部操作时停止,并为有安全风险的任务设置评估关卡和人工合并审批。
安装难易度所需工具和 API 密钥是否少且有说明
A良好没有必需的额外工具或API密钥,仅在已启用时使用ECC2状态管理。

总分按每项 A=25 分、B=15 分、C=5 分相加。 由 AI(OpenAI Codex)于 2026年10月19日 评估。仅供参考,安装前请同时查看原文。

如果您认为评估有误,请申请复核

请写明哪一项有误以及原因。无需登录。我们会对照 SKILL.md 重新评估,并在此处更新结果。

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

包含的文件(1)

  • SKILL.md5.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Dynamic Workflow Mode

Use this skill when a coding agent can generate or adapt a task-local harness instead of only following a static command flow. The goal is to turn dynamic workflow mode into a disciplined system: temporary harnesses for one-off work, shared skill extraction for repeated work, and observable control pane checkpoints for teams.

When To Activate

  • The user mentions dynamic workflows, custom harnesses, harness-per-task, adaptive workflows, or Claude Code dynamic workflow mode.
  • A task needs a custom loop, evaluator, crawler, fixture generator, watcher, or local dashboard.
  • Multiple agents need the same repeatable process but the process is not yet captured as a shared skill.
  • A workflow needs durable handoff artifacts, eval evidence, or operator approval before merge.

Core Contract

Dynamic workflow mode should produce a task-local harness only when the harness is cheaper and safer than manually driving the same steps. The harness must have:

  • Objective: the outcome it owns and the outcome it explicitly does not own.
  • Inputs: files, URLs, prompts, data sources, credentials policy, and user-provided constraints.
  • Outputs: commits, reports, screenshots, status files, or control pane snapshots.
  • Eval: at least one pass/fail check tied to the task, not only "it ran".
  • Handoff: a short artifact that tells the next operator what happened, what is blocked, and how to resume.

Dynamic Harness Decision Tree

  1. One-shot task: keep it inline. Do not invent a harness.
  2. Repeated task with changing inputs: create a task-local harness and keep it under a temp or project-local working area.
  3. Repeated task across teammates or repos: extract the pattern into a shared skill.
  4. Task with external state, queueing, or approvals: add control pane visibility before adding more automation.
  5. Task with safety risk: add an eval gate and a human merge gate before autonomous execution.

Task-Local Harness Template

Use this structure before writing code:

# Dynamic Workflow Harness

Objective:
- Ship:
- Do not ship:

Inputs:
- Repo or workspace:
- External systems:
- Credentials policy:

Loop:
1. Discover current state.
2. Generate or update the smallest useful artifact.
3. Run eval checks.
4. Record status and handoff.
5. Stop on failed gate, unclear ownership, or unsafe external action.

Eval:
- Command:
- Expected pass signal:
- Failure owner:

Handoff:
- Status:
- Evidence:
- Next action:

Shared Skill Extraction

Promote a task-local harness into a shared skill only when at least two of these are true:

  • The same workflow appears in multiple sessions, repos, teams, or launches.
  • The workflow needs specific language, tool, or safety sequencing.
  • Failures repeat because operators skip a gate or lose context.
  • The workflow has a stable input/output contract.
  • The workflow benefits from a control pane, status board, or team handoff.

When extracting, write the skill first in skills/<name>/SKILL.md. Add command shims only if a legacy slash-entry surface is still required.

Control Pane Checkpoints

Dynamic workflow mode becomes team-usable when it exposes state. Record these checkpoints whenever the task spans more than one session:

  • Plan: objective, owner, acceptance criteria, and risky external systems.
  • Queue: work items, assigned agent role, branch/worktree, and dependency edges.
  • Run: active harness, current loop step, recent eval result, and token/cost signal if available.
  • Gate: test results, browser screenshots, security review, and merge readiness.
  • Handoff: what is done, what failed, what needs a human decision.

If the repo has ECC2 state enabled, prefer adding or reading checkpoints through the ECC control pane or state-store-backed scripts instead of scattering untracked notes.

Eval Gates

Every dynamic harness needs a task-specific eval. Pick the cheapest reliable gate:

Work TypeEval Gate
Code featureFocused test, lint, coverage, and one integration path
UI/control paneBrowser smoke with screenshot and overflow/error checks
Agent workflowFixture transcript or seeded work item with expected routing
Research/contentSource-neutral brief, claim checklist, and publish-ready outline
IntegrationDry-run command, config validation, and no-secret scan

Do not claim a dynamic workflow is reusable until the eval can be rerun by another teammate.

Anti-Patterns

  • Generating scripts that hide the real decision logic from the operator.
  • Treating dynamic workflow mode as permission to skip tests.
  • Creating one-off docs when a shared skill or status artifact is the real product.
  • Running multiple agents without ownership, merge gate, or conflict policy.
  • Letting raw private research data leak into public docs.

Output Standard

Finish with:

  • The harness or skill path.
  • The eval commands and results.
  • The control pane or handoff artifact path.
  • The next reusable extraction candidate.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Design and audit interfaces for Web, iOS, and Android using WCAG 2.2 accessibility guidance. Check screen-reader labels, keyboard navigation, contrast, and control sizes to identify barriers and guide implementation for people using assistive technology.

中文简介正在准备中。当前显示英语简介。

  • Adding descriptive labels to icon-only buttons
  • Reviewing keyboard navigation and modal focus
  • Checking contrast and control sizes
affaan-m/ECC28.4万2026年10月16日 更新

agent-architecture-audit

免费有简介AI 评分 80分

从指令、记忆、工具执行和界面显示等十二个层面排查人工智能代理故障,依据代码和日志梳理原因,按严重程度列出问题并提出修复方案。

  • 排查仅在应用内出现的故障
  • 调查旧对话混入回答的原因
  • 核对工具漏执行或虚报执行
affaan-m/ECC28.4万2026年10月16日 更新

agent-eval

免费有简介AI 评分 80分

用实际开发任务比较多个编程智能体,记录成功率、可获取的API费用、耗时和重复运行的稳定性,为工具选型及更新后的性能评估提供数据。

  • 用实际开发任务比较智能体
  • 采用新工具或模型前进行评估
  • 检查智能体更新后的性能
affaan-m/ECC28.4万2026年10月16日 更新

Design and refine an AI agent’s available actions, tool inputs, and result formats. Define recovery steps for errors, manage the information kept in context, and evaluate changes through completion rates, retries, and cost per successful task.

中文简介正在准备中。当前显示英语简介。

  • Define an AI agent’s tool set and input formats
  • Make tool results and next steps easier to interpret
  • Specify safe retries and stopping conditions
affaan-m/ECC28.4万2026年10月16日 更新

agent-introspection-debugging

免费有简介AI 评分 100分

根据错误信息和执行环境,分析AI代理反复失败或重复操作的原因。通过小范围、可撤销的恢复操作检验假设,并将结果与依据整理成可供交接的报告。

  • 诊断代理连续失败
  • 调查重复调用工具的循环
  • 检查上下文积累导致的输出退化
affaan-m/ECC28.4万2026年10月5日 更新

agent-introspection-debugging

免费有简介AI 评分 100分

在AI代理反复失败或重复操作时,记录错误与环境前提、排查原因,采取影响有限的恢复操作,并汇总结果和证据,为有依据的重试与交接提供支持。

  • 排查重复调用工具的原因
  • 调查对话膨胀导致的质量下降
  • 核对文件路径与环境差异
affaan-m/ECC28.4万2026年10月16日 更新

查看 affaan-m 的全部技能

报告此技能的问题