Communitygithub.com

项目流程运维

跨GitHub和Linear协调问题与拉取请求的流转,开展issue与PR分类、链接活跃工作,保持GitHub对外可见而Linear作为内部执行层。适用于需要管控待办任务、分类PR或协调GitHub与Linear的场景。

项目流程运维 是什么?

该技能将分散在 GitHub 和 Linear 中的 issue、PR 和任务整合为一个统一的执行流程。它专门解决协作协调问题,而非编码问题。当用户需要分类 PR 或 issue 待办、决定哪些内容应转入 Linear、将活跃的 GitHub 工作链接到内部执行轨道、或将 PR 分类为合并、迁移、关闭或暂缓时,都可调用此技能。其工作模式基于清晰的分层原则:GitHub 作为公共社区的真实来源,Linear 作为主动已排期工作的内部真实来源,并非所有 GitHub issue 都需要创建对应的 Linear 任务。核心流程包括:先读取公共视图(GitHub issue/PR 状态、作者、分支、审查评论及 CI 状态),再对每项工作进行分类(合并、迁移/重建、关闭、暂缓),最后决定是否需要在 Linear 中创建或更新记录。技能同时提供明确的输出格式,包含公开状态、分类结果、Linear 操作建议及下一步操作。对于 CI 失败或产品方向性阻塞等真实问题,技能要求直言不讳,避免用工具借口掩盖实际障碍。

兼容平台~Claude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/project-flow-ops

在你喜欢的 AI 中提问

打开一个已预加载此 Agent Skill 的新对话。

文档

项目流程运维 是做什么的?

此技能将分散的 GitHub issue、PR 和 Linear 任务整合成一个统一的执行流程。

当问题是协调而非编码时使用此技能。

使用时机

  • 对开放的 PR 或 issue 待办进行分诊
  • 判断哪些内容应放入 Linear,哪些应仅保留在 GitHub
  • 将活跃的 GitHub 工作链接到内部执行轨道
  • 将 PR 分类为:合并、迁移/重建、关闭、暂缓
  • 审计审查评论、CI 失败或过时 issue 是否阻碍了执行

工作模式

  • GitHub 是公开和社区的真实来源
  • Linear 是主动已排期工作的内部执行真实来源
  • 并非所有 GitHub issue 都需要创建 Linear issue
  • 仅当工作属于以下情况时,才在 Linear 中创建或更新记录:
    • 活跃进行中
    • 已委派
    • 已排期
    • 跨职能
    • 重要性足够需要在内部追踪

核心工作流程

1. 首先读取公共视图

收集:

  • GitHub issue 或 PR 状态
  • 作者与分支状态
  • 审查评论
  • CI 状态
  • 已关联的 issue

2. 对工作进行分类

每个项目最终应归入以下状态之一:

状态含义
合并独立完整、符合策略、已就绪
迁移/重建有价值的想法,但应手动在 ECC 内部重新落地
关闭方向错误、过时、不安全或重复
暂缓可能有价值,但当前未排期

3. 判断是否需要创建 Linear 记录

仅当满足以下条件时,才在 Linear 中创建或更新记录:

  • 执行已被积极策划
  • 涉及多个仓库或工作流
  • 工作需要内部所有权或排序
  • 该 issue 属于更大的项目轨道

不要机械地镜像所有内容。

4. 保持两个系统一致

当工作处于活跃状态时:

  • GitHub issue/PR 应说明公开层面正在发生什么
  • Linear 应在内部记录负责人、优先级和执行轨道

当工作完成或被拒绝时:

  • 将公开决议结果发布回 GitHub
  • 相应地在 Linear 中标记任务

审查规则

  • 切勿仅凭标题、摘要或个人信任直接合并;必须查看完整差异
  • 源自外部的功能,如果价值高但不独立完整,应在 ECC 内部重建
  • CI 为红色意味着需分类并修复或阻止,不要假装它已达到可合并状态
  • 如果真正的阻碍是产品方向问题,就直言相告,而不是躲在工具背后

输出格式

返回:

公开状态
- issue / PR 状态
- CI / 审查状态

分类
- 合并 / 迁移-重建 / 关闭 / 暂缓
- 一段解释

LINEAR 操作
- 创建 / 更新 / 无需 Linear 项目
- 项目 / 轨道(如适用)

下一步操作者行动
- 确切的下一个步骤

良好使用场景

  • “审计开放的 PR 待办列表,告诉我哪些应该合并,哪些需要重建”
  • “将 GitHub issue 映射到我们的 ECC 1.x 和 ECC 2.0 程序轨道”
  • “检查此 issue 是否需要创建 Linear 记录,还是应仅保留在 GitHub”

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

End-to-end marketing campaign planning and execution. Covers audience research, positioning, campaign angle definition, landing page copy, email sequences, social posts, ad copy, short-form video scripts, and content calendars. Use as the orchestration layer for multi-channel product launches. Use when planning or executing a multi-channel product launch, or producing landing page, email, social, or ad copy.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

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