evanflow

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EvanFlow

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.
一种基于TDD驱动的、与Claude Code配合使用的软件开发迭代反馈循环。16个内聚技能+2个自定义子Agent将想法从头脑风暴→规划→执行→TDD→迭代全程落地,过程中设置多个检查点。包含垂直切片TDD、并行编码/监督审核、可执行内聚契约、上下文压缩等特性。绝不自动提交——所有Git操作均由用户掌控。

Single Entry Point:
evanflow-go

单一入口:
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.
当用户说出“让我们用EvanFlow处理这个”、“使用EvanFlow”、“用EvanFlow处理这个想法”、“通过EvanFlow运行这个”或类似表述时,调用
evanflow-go
。它是整个循环(头脑风暴→规划→执行→TDD→迭代→停止)的编排器,会宣布每个步骤、遵守检查点(设计批准、规划批准),并在每个阶段切换到对应的子技能。用户无需记住何时使用哪个子技能,即可获得完整的EvanFlow工作流。
evanflow-go
是指挥者而非自动驾驶——每个检查点都是真实存在的,用户可随时中断或切换路径。

Shared Vocabulary

共享术语

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.
所有
evanflow-*
技能均使用这套术语。此处可交叉引用,无需重复定义。
  • Module(模块) — 任何包含接口+实现的单元(函数、类、包)。与规模无关。
  • Interface(接口) — 完整的调用方认知:类型签名、不变量、顺序约束、错误模式、性能特征。
  • Depth(深度) — 小接口背后承载大逻辑=深度模块(优质)。大接口仅对应单薄逻辑=浅层模块(需避免)。
  • Seam(衔接点) — 接口所在的位置;无需原地修改即可切换逻辑的地方。
  • Adapter(适配器) — 在衔接点处满足接口要求的具体实现。
  • Deletion test(删除测试) — 删除该模块后,复杂度会分散到N个调用方,还是随之消失?前者是有效模块;后者是冗余代码。
  • Vertical slice(垂直切片) — 编写一个测试→实现对应功能→重复该过程。绝不要先写完所有测试再写所有代码(水平切片会针对想象中的逻辑编写测试)。
  • Behavior through public interface(通过公共接口定义行为) — 测试描述做什么,而非怎么做。这类测试能在重构后依然有效。如果重命名操作破坏了测试但逻辑未变,说明测试本身存在问题。
  • Grill — 可选的访谈模式,嵌入在规划类技能的标记章节中。在确定方案前进行压力测试。不属于EvanFlow中的独立技能调用。
  • Ubiquitous language(通用语言)
    CONTEXT.md
    中的标准领域术语。新术语会在发现后添加。
  • Mockup quick-mode(快速原型模式) — 当用户仅需视觉概念时,跳过规格/规划流程。直接以项目适用的形式生成原型(HTML文件、Figma框架、ASCII布局等)——无需完整设计循环。

Hard Rules (apply to every evanflow skill)

硬性规则(适用于所有EvanFlow技能)

  • 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.
  • 绝不自动提交、绝不自动暂存、绝不自动完成。 所有Git写入操作(
    commit
    push
    merge
    rebase
    tag
    branch -d/-D
    )都需要用户在当前对话轮次中明确要求。即使是
    git add
    也不应由Agent主动执行——保持文件未暂存状态,直到用户示意准备提交。
  • Agent不得主动启动“完成/集成”工作流。 实现+迭代完成后,Agent仅汇报已完成的工作并停止。由用户决定是否提交、合并、发起PR、继续迭代或改变方向。
  • 绝不要编造非权威来源的信息。 包括:文件路径、环境变量值、API密钥、保密值、ID(UUID、外键、第三方对象ID)、URL、端口号、主机名、版本号、第三方服务名称、未确认存在的函数名。若不确定,停止操作并询问——不要猜测。动作幻觉(Agent自信地执行错误操作)是智能体编码中最危险的故障模式(2026年行业研究)。询问仅需一次交互往返;基于幻觉信息操作的代价可能是灾难性的。
  • 警惕上下文漂移。 如果发现自己重复询问已确认的问题、与之前的决定矛盾、或忘记会话早期设定的约束,调用
    evanflow-compact
    来保留关键信息并建议执行
    /clear
    。约65%的智能体故障源于上下文漂移,而非原始令牌耗尽。
  • 无技能使用门槛。 临时问题无需调用技能。技能是工具,而非关卡。
  • 无强制规格/规划路径。 规格和规划可存储在用户指定的任意位置。仅当用户无偏好时默认使用
    docs/
    目录。
  • 无强制子技能调用链。 每个EvanFlow技能均可独立使用。技能切换是建议而非强制要求。
  • 完成前先验证。 运行项目的质量检查(类型检查、代码 lint、测试)并确认输出后,再汇报完成状态。

The Default Loop

默认循环

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. EXECUTE     evanflow-executing-plans  — task harness: critical review, TaskCreate, inline
                                          verification, blockers, quality checks. Step 0:
                                          parallelization check (offers coder-overseer).
        OR     evanflow-coder-overseer   — same harness role, parallel: contract → RED checkpoint →
                                          coders → per-coder overseers → integration overseer.

   ↳ INSIDE every code-writing task in EXECUTE:
       evanflow-tdd                      — vertical-slice RED → GREEN → REFACTOR per cycle.
                                          NOT a separate phase. The discipline that runs
                                          inside the task harness for any production code.

4.             evanflow-iterate          — self-review loop AFTER all tasks are done:
                                          re-read diff, fix issues, re-run checks,
                                          (UI) view the page. Repeat until clean.
5.             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.
1. (可选)  evanflow-brainstorming   — 明确意图,提出2-3种实现方案,内置Grill环节。
                                          仅需原型的请求使用快速原型模式。
                                          (针对复杂功能,会切换到evanflow-prd。)
2. (若任务非 trivial) evanflow-writing-plans — 文件结构规划、拆分小任务,内置Grill环节。
                                          步骤2.5:并行化检查——若存在3个及以上独立单元,
                                          提供coder-overseer模式。
3. 执行阶段     evanflow-executing-plans  — 任务管理:严格审核、TaskCreate、内联
                                          验证、障碍处理、质量检查。步骤0:
                                          并行化检查(提供coder-overseer模式)。
        或     evanflow-coder-overseer   — 同样的任务管理角色,采用并行模式:契约→RED检查点→
                                          编码人员→对应监督者→集成监督者。

   ↳ 在执行阶段的所有代码编写任务中:
       evanflow-tdd                      — 每个循环遵循垂直切片RED → GREEN → REFACTOR流程。
                                          这不是独立阶段,而是任何生产代码编写任务中需遵循的规范。

4.             evanflow-iterate          — 所有任务完成后的自我审查循环:
                                          重新查看代码差异、修复问题、重新运行检查、
                                          (UI场景)查看页面。重复操作直到无问题。
5.             停止。汇报已完成的工作。等待用户指令。
循环全程相互关联。 每个步骤会在条件匹配时主动推荐合适的下一步技能——包括在规划阶段(步骤2)和执行阶段(步骤3),当方案可并行时推荐
evanflow-coder-overseer
跨环节支持: 当出现上下文漂移症状或进入清晰的阶段边界时,
evanflow-compact
会伴随循环运行。不要等到令牌限制警告才处理——在阶段边界主动压缩上下文的质量远高于在流程中被动处理。
无自动提交、无自动完成、无自动集成步骤。 用户掌控提交、合并、推送、发起PR的时机。步骤5完成后,Agent仅汇报工作并等待指令。
临时问题、快速原型、探索性阅读:无需调用技能,直接回答即可。

When to Invoke Each Skill

各技能调用时机

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 tasks
evanflow-writing-plans
"Execute the plan" / picking up an existing plan doc
evanflow-executing-plans
Any production code change
evanflow-tdd
"Polish this" / "review this" / "make sure it's clean" / after implementation
evanflow-iterate
Plan has 3+ truly independent parallel tasks with a shared contract
evanflow-coder-overseer
(instead of
evanflow-executing-plans
)
Long session, drift symptoms, major phase boundary, or session feels heavy
evanflow-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 shape
evanflow-prd
"Refactor X" / "this file is too big" / architecture concerns
evanflow-improve-architecture
"Design the API for X" / interface design
evanflow-design-interface
"Update CONTEXT.md" / new domain term emerged
evanflow-glossary
"Debug Y" / unexpected behavior, root-cause needed
evanflow-debug
Code review (giving or receiving)
evanflow-review
"File a bug for X" / QA session
evanflow-qa
Token-heavy session, want compression
caveman
(upstream, kept as-is)
触发语技能
“让我们用EvanFlow处理这个” / “使用EvanFlow” / “用EvanFlow处理这个想法” / 任何类似“通过EvanFlow运行这个”的表述
evanflow-go
(入口点——执行完整循环)
“帮我梳理X的思路” / “我想开发Y” / 新功能范围界定(未提及“evanflow”)
evanflow-brainstorming
(若用户需要完整循环,可调用
evanflow-go
“规划Z的实现” / 已有规格,准备拆分为任务
evanflow-writing-plans
“执行规划” / 基于现有规划文档开展工作
evanflow-executing-plans
任何生产代码变更
evanflow-tdd
“优化这个” / “审查这个” / “确保代码整洁” / 实现完成后
evanflow-iterate
规划包含3个及以上真正独立的并行任务且有共享契约
evanflow-coder-overseer
(替代
evanflow-executing-plans
会话时长较长、出现漂移症状、进入主要阶段边界或会话负载过重
evanflow-compact
“提交这个” / “推送” / “合并” / “发起PR” — 仅用户主动发起时(无对应技能——仅在明确要求时直接执行)
“为X编写PRD” / 以PRD形式呈现新功能
evanflow-prd
“重构X” / “这个文件太大了” / 架构相关问题
evanflow-improve-architecture
“设计X的API” / 接口设计
evanflow-design-interface
“更新CONTEXT.md” / 出现新的领域术语
evanflow-glossary
“调试Y” / 出现意外行为,需排查根本原因
evanflow-debug
代码审查(发起或接收)
evanflow-review
“为X提交Bug” / QA环节
evanflow-qa
会话令牌占用过高,需要压缩
caveman
(上游技能,保持原样)

Compatible Tooling

兼容工具

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
.
EvanFlow是独立系统——以下工具均非必需。但如果已安装其他Claude Code技能集中的独立工具,部分工具可与EvanFlow良好配合:
  • Git工作区技能,用于隔离大型重构
  • 完成前验证规则(已内置到
    evanflow-executing-plans
    evanflow-iterate
    中)
  • 并行智能体调度模式(已在
    evanflow-design-interface
    evanflow-coder-overseer
    中使用)
  • 令牌压缩模式,适用于超长会话(补充
    evanflow-compact
    功能)
关于现有生态系统中的哪些技能启发了EvanFlow的技能设计,以及哪些技能被刻意未采用的历史记录,请查看
docs/skills-audit.md