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evanflowevanflow 搜索

Agent Skill

evanflow 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 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

192

周安装

8

GitHub Stars

337

下载量

64
CodexClaudeCursorGemini CLI

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

unknown

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:evanflow(evanflow 搜索)
来源仓库:https://github.com/evanklem/evanflow
仓库路径:skills/evanflow
安装命令:
npx skills add https://github.com/evanklem/evanflow --skill evanflow
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 npx skills 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。

skills.shnpx skills
npx skills add https://github.com/evanklem/evanflow --skill evanflow

简介

evanflow 是基于 TDD 的迭代开发工作流,从构思到交付包含 16 个协同技能模块。

  • 适用于软件项目全生命周期管理,支持垂直切片开发、并行编码监督和质量门禁。
  • 使用时需先明确任务范围,再按脑暴→计划→执行→测试→迭代的循环推进。
  • 安装前请确认仓库权限和维护状态,禁止自动提交代码,所有 git 操作需用户手动确认。
  • evanflow 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

EvanFlow

A TDD-driven iterative feedback loop for software development with Claude Code. 16 cohesive skills + 2 custom subagents walk an idea from brainstorm → plan → execute → tdd → iterate, with checkpoints throughout. Vertical-slice TDD, parallel coder/overseer review, executable cohesion contracts, context compaction. Never auto-commits — the user controls every git op.

Single Entry Point: evanflow-go

When the user says "let's evanflow this", "use evanflow", "evanflow this idea", "run this through evanflow", or anything similar — invoke evanflow-go. It's the orchestrator that walks the entire loop end-to-end (brainstorm → plan → execute → tdd → iterate → STOP), announces each step, respects checkpoints (design approval, plan approval), and hands off to the right sub-skill at each phase. The user gets the full EvanFlow workflow without having to remember which sub-skill applies when.

evanflow-go is conductor, not autopilot — every checkpoint is real and the user can interrupt or switch paths anytime.

Shared Vocabulary

Every evanflow-* skill speaks this. Cross-reference here, don't redefine.

  • Module — any unit with interface + implementation (function, class, package). Scale-agnostic.
  • Interface — complete caller knowledge: type signature, invariants, ordering constraints, error modes, performance characteristics.
  • Depth — large behavior behind a small interface = deep (good). Large interface, thin behavior = shallow (avoid).
  • Seam — where an interface lives; a place behavior can shift without editing in place.
  • Adapter — concrete implementation satisfying an interface at a seam.
  • Deletion test — does removing this module concentrate complexity across N callers, or does complexity vanish? The first is a real module; the second is bloat.
  • Vertical slice — one test → one impl → repeat. Never write all tests first then all code (horizontal slicing produces tests of imagined behavior).
  • Behavior through public interface — tests describe *what*, not *how*. They survive refactors. If a rename breaks a test but behavior didn't change, the test was wrong.
  • Grill — opt-in interview pattern, embedded as a labeled section inside planning skills. Stress-test before committing to a path. Not a separate skill invocation in EvanFlow.
  • Ubiquitous language — canonical domain terms in CONTEXT.md. New terms added as discovered.
  • Mockup quick-mode — when user just wants visual concepts, skip spec/plan ceremony. Produce mockups directly in whatever form the project uses (HTML files, Figma frames, ASCII layouts, etc.) — no full design loop required.

Hard Rules (apply to every evanflow skill)

  • Never auto-commit, never auto-stage, never auto-finish. Every git write op (commit, push, merge, rebase, tag, branch -d/-D) requires the user to explicitly ask for it in the current turn. Even git add should not happen on the agent's initiative — leave files unstaged until the user signals they're about to commit.
  • No "finish/integrate" workflow on the agent's initiative. After implementation + iterate, the agent reports what was done and stops. The user decides whether to commit, merge, open a PR, keep iterating, or change direction.
  • Never invent values you don't authoritatively have. This includes: file paths, env var values, API keys, secret values, IDs (UUIDs, foreign keys, third-party object IDs), URLs, port numbers, hostnames, version numbers, third-party service names, function names you haven't verified exist. If unsure, STOP and ask — don't guess. Action-hallucination (an agent confidently doing the wrong thing) is the most dangerous failure mode in agentic coding (industry research, 2026). The cost of asking is one round-trip; the cost of acting on a hallucinated value is potentially catastrophic.
  • Watch for context drift. If you find yourself re-asking established questions, contradicting earlier decisions, or losing track of constraints set earlier in the session, invoke evanflow-compact to preserve anchors and propose a /clear. ~65% of agent failures trace to context drift, not raw token exhaustion.
  • No skill tax. Ad-hoc questions don't require a skill invocation. Skills are tools, not a tollbooth.
  • No forced spec/plan paths. Specs and plans live wherever the user wants. Default to docs/ only if no preference is stated.
  • No forced sub-skill chains. Each evanflow skill stands alone. Hand-offs are suggestions, not mandates.
  • Verify before claiming done. Run the project's quality checks (typecheck, lint, test) and confirm output before reporting completion.

The Default Loop

1. (optional)  evanflow-brainstorming   — clarify intent, propose 2-3 approaches, embedded grill.
                                          Mockup-only requests use mockup quick-mode.
                                          (Hands off to evanflow-prd for substantial features.)
2. (if non-trivial) evanflow-writing-plans — file structure, bite-sized tasks, embedded grill.
                                          Step 2.5: parallelization check — offers
                                          coder-overseer if 3+ independent units exist.
3.             evanflow-executing-plans  — Step 0: parallelization check (offers coder-overseer).
                                          Otherwise task-by-task sequential with inline verification.
        OR     evanflow-coder-overseer   — if user picked parallel path: contract → RED checkpoint →
                                          coders (vertical-slice TDD) → per-coder overseers →
                                          integration overseer (runs touchpoint tests).
4. (always)    evanflow-tdd              — vertical slices for any production code.
                                          Used INSIDE executing-plans tasks AND inside coder-overseer
                                          coders.
5.             evanflow-iterate          — self-review loop: re-read diff, fix issues, re-run checks,
                                          (UI) view the page. Repeat until clean.
6.             STOP. Report what was done. Await user direction.

The loop is interlinked end-to-end. Each step actively offers the right next-step skill when conditions match — including offering evanflow-coder-overseer at both planning time (step 2) and execution time (step 3) when the plan is parallelizable.

Cross-cutting: evanflow-compact runs alongside the loop whenever context drift symptoms appear or at clean phase boundaries. Don't wait for token-limit warnings — proactive compaction at boundaries is far higher quality than reactive mid-flow compaction.

There is no auto-commit, no auto-finish, no auto-integration step. The user controls when to commit, when to merge, when to push, when to open a PR. After step 5, the agent reports and waits.

Ad-hoc questions, quick mockups, exploratory reads: no skill invoked. Just answer.

When to Invoke Each Skill

TriggerSkill
"Let's evanflow this" / "use evanflow" / "evanflow this idea" / any "run this through evanflow"evanflow-go (entry point — walks the whole loop)
"Help me think through X" / "I want to build Y" / new feature scoping (without saying "evanflow")evanflow-brainstorming (or invoke evanflow-go if user wants the full loop)
"Plan out Z" / spec exists, ready to break into tasksevanflow-writing-plans
"Execute the plan" / picking up an existing plan docevanflow-executing-plans
Any production code changeevanflow-tdd
"Polish this" / "review this" / "make sure it's clean" / after implementationevanflow-iterate
Plan has 3+ truly independent parallel tasks with a shared contractevanflow-coder-overseer (instead of evanflow-executing-plans)
Long session, drift symptoms, major phase boundary, or session feels heavyevanflow-compact
"Commit this" / "push" / "merge" / "open a PR" — user-initiated only(no skill — just do it directly when explicitly asked)
"Write a PRD for X" / new feature in PRD shapeevanflow-prd
"Refactor X" / "this file is too big" / architecture concernsevanflow-improve-architecture
"Design the API for X" / interface designevanflow-design-interface
"Update CONTEXT.md" / new domain term emergedevanflow-glossary
"Debug Y" / unexpected behavior, root-cause neededevanflow-debug
Code review (giving or receiving)evanflow-review
"File a bug for X" / QA sessionevanflow-qa
Token-heavy session, want compressioncaveman (upstream, kept as-is)

Compatible Tooling

EvanFlow is self-contained — none of these are required. But some standalone utilities from other Claude Code skill sets compose well alongside if you happen to have them installed:

  • A git worktrees skill, for isolating big refactors
  • A verification-before-completion rule (already baked into evanflow-executing-plans and evanflow-iterate)
  • A parallel-agents dispatch pattern (already used inside evanflow-design-interface and evanflow-coder-overseer)
  • A token-compression mode for very long sessions (complements evanflow-compact)

For the historical record of which existing-ecosystem skills inspired which EvanFlow skills, and which were deliberately not adopted, see docs/skills-audit.md.

适合场景

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用户想查找某类 Agent Skill 时

02

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03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

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。

平台分布

Codex

32.61%
按下载量换算21

Claude

33.23%
按下载量换算21

Cursor

18.75%
按下载量换算12

Gemini CLI

10.38%
按下载量换算7

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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