plan
- Repo stars 175
- Author updated Live
- Author repo Rlues
- Domain
- Other
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @WenJunDuan · no license declared
- Token usage
- Lean
- Setup complexity
- Plug-and-play
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Network behavior
- Local-only
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools,默认拥有全部工具权限。
---
name: plan
description: > !cat .ai_state/project.json 2>/dev/null | head -5 !head -5 .ai_state/design.md 2>/dev/null 如果需…
category: other
runtime: no special runtime
---
# plan output preview
## PART A: Task fit
- Use case: > !cat .ai_state/project.json 2>/dev/null | head -5 !head -5 .ai_state/design.md 2>/dev/null 如果需求清晰 (如 "给 API 加 rate limiting") → 跳到技术调研。 如果需求模糊 → superpowers brainstorming skill 会自动激活, 引导用户逐步明确。 runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more..
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “当前状态 / R₀ 需求精炼 / R 技术调研” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “> !cat .ai_state/project.json 2>/dev/null | head -5 !head -5 .ai_state/design.md 2>/dev/null 如果需求清晰 (如 "给 API 加 rate limiting") → 跳到技术调研。 如果需求模糊 → superpowers brainstorming skill 会自动激活, 引导用户逐步明确。 runs entirely locally. Works with Claude Code, Cursor, Cline and 23 more.”.
- **02** When the source has headings, the agent prioritizes “当前状态 / R₀ 需求精炼 / R 技术调研” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files; mostly runs locally; usually needs no extra API key.
## Running Rules
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. The source mentions slash commands such as `/review`, `/codex`, `/api`; use them first when your agent supports command triggers.
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files.
Start with a small task and check whether the result follows “当前状态 / R₀ 需求精炼 / R 技术调研”. Inspect diffs, logs, previews, or tests before expanding scope.
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: plan
description: > !cat .ai_state/project.json 2>/dev/null | head -5 !head -5 .ai_state/design.md 2>/dev/null 如果需…
category: other
source: WenJunDuan/Rlues
---
# plan
## When to use
- > !cat .ai_state/project.json 2>/dev/null | head -5 !head -5 .ai_state/design.md 2>/dev/null 如果需求清晰 (如 "给 API 加 rate l…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “当前状态 / R₀ 需求精炼 / R 技术调研” and keep inference separate from source facts.
- read files, write/modify files; mostly runs locally; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "plan" {
input -> user goal + target files + boundaries + acceptance criteria
context -> 当前状态 / R₀ 需求精炼 / R 技术调研
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files | mostly runs locally
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
} Plan Skill: 需求 → 设计 → Sprint Contract
当前状态
!cat .ai_state/project.json 2>/dev/null | head -5
!head -5 .ai_state/design.md 2>/dev/null
R₀ 需求精炼
目标: 把用户说的变成可验收的 Spec。
如果需求清晰 (如 "给 API 加 rate limiting") → 跳到技术调研。 如果需求模糊 → superpowers brainstorming skill 会自动激活, 引导用户逐步明确。
无论用什么方式精炼, 最终必须:
- 写入 .ai_state/design.md: 需求摘要 + MUST/SHOULD/COULD + 验收标准
- 每条验收标准必须可测试 (如 "无效邮箱输入时返回 400")
- 明确列出不做什么
约束:
- superpowers brainstorming 可能把设计写到
docs/superpowers/plans/→ 必须整理到 .ai_state/design.md - 验收标准不能是模糊的 "用户体验好" → 必须可测试
用户确认: cunzhi MCP DESIGN_READY 检查点 (如可用), 或直接问用户确认 design.md。
R 技术调研
目标: 验证关键技术可行, 排除风险。
- Grep 搜索项目中的相关实现
- augment-context-engine 做语义搜索 (如可用) — 跨文件关联分析
ctx7 library {{库名}}搜索库 →ctx7 docs {{库ID}} "关键API"查文档- 读 .ai_state/lessons.md — 有没有踩过相关的坑
- 追加到 design.md: 接口签名 + 依赖版本 + 已知风险和缓解方案
D 方案定稿
目标: 锁定方案, 用户确认。
审查方式 (选一):
- @evaluator 独立评审 → VERDICT: APPROVED/REVISE
/review(CC 内置) 快速审查
约束: /codex:adversarial-review 只能审查代码变更, D 阶段没有代码, 不要用。
审查通过后 → 从 design.md 的验收标准生成 Sprint Contract:
用户确认: cunzhi MCP SPRINT_CONTRACT 检查点 (如可用), 或直接问用户确认。
# tasks.md 示例
## 待办
- [ ] F001/T001: 创建 User model — 验收: schema 含 email(unique), passwordHash, createdAt
- [ ] F001/T002: 实现 POST /api/register — 验收: 有效输入注册成功, 无效输入返回 400
- [ ] F002/T001: 实现 POST /api/login — 验收: 正确凭据返回 token, 错误凭据返回 401
写入 .ai_state/tasks.md → 用户确认。
P 计划排期
目标: 确定依赖和执行顺序。
- 标注 Task 间依赖 (如 T002 依赖 T001)
- 确定执行顺序
- 为每个 Task 规划测试策略
- 补充到 tasks.md
产出: tasks.md 完整的 Task 清单 + 执行顺序 门控: tasks.md 非空 → 进入 E 阶段
Gotchas
- ❌ 验收标准写 "用户体验好" → ✅ 写 "输入无效邮箱时显示错误提示"
- ❌ 跳过技术调研直接写方案 → ✅ 至少 Grep 搜索 + 查一个关键库文档
- ❌ 生成 100 个 Task → ✅ 一个 Sprint 控制在 5-15 个 Task
Decide Fit First
Design Intent
How To Use It
Boundaries And Review