Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add qqabcv520/my-claude-marketplaces --skill planninggit clone --depth 1 https://github.com/qqabcv520/my-claude-marketplacesWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/qqabcv520/my-claude-marketplaces/planning)<a href="https://agentmods.dev/skills/qqabcv520/my-claude-marketplaces/planning"><img src="https://agentmods.dev/badge/skills/qqabcv520/my-claude-marketplaces/planning/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/qqabcv520/my-claude-marketplaces/planning"><img src="https://agentmods.dev/badge/skills/qqabcv520/my-claude-marketplaces/planning.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00065 | $0.04046 |
| Opus 5 | $0.00032 | $0.02023 |
| Sonnet 5 | $0.00013 | $0.00809 |
| Haiku 4.5 | $0.00006 | $0.00405 |
Grade A, and why
planning scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 456 lines — stays where its author put it; the contents beside it link to each section on GitHub.
交互式计划制定 Skill
概述
此 skill 用于把模糊需求收敛成一份可审查、可执行、可交接的实施计划。
它的核心目标不是“尽快开始写代码”，而是先回答四个问题：
- 要解决什么问题
- 哪些范围必须做，哪些不做
- 推荐采用什么方案，为什么
- 任何执行者如何按计划稳定落地
默认采用 5 个阶段推进：深度理解 → 方案设计 → 审查对齐 → 最终计划 → 退出规划。
何时使用
在以下场景使用此 skill：
- 用户说“帮我制定计划”“把任务拆解一下”“规划一下这个需求”
- 需求还不完整，需要先澄清边界、角色、流程或约束
- 存在多个技术方案，需要比较后再决定
- 任务规模较大，直接开始实现风险高
- 需要输出
docs/spec/下的计划文件，供/ps-exec或人工执行 - 需要在编码前先完成风险评估、范围确认和验收标准定义
何时不要使用
以下情况通常不必进入完整规划流程：
- 需求已经非常明确，且只是低风险的小改动
- 单文件、小范围修复，用户明确要求直接实现
- 当前任务重点是排查 bug，应优先使用调试类 skill
- 当前任务重点是立即编码，应优先遵循实现类 workflow
如果不确定是否要进入完整流程，先做复杂度判定。
核心规则
-
规划阶段默认只读
- 允许读取代码、文档、配置、测试。
- 只允许写计划文件，不修改业务代码或配置。
-
先理解，再设计，再承诺
- 不要在需求和约束未清之前给出最终方案。
- 不要在方案未收敛之前输出详细执行步骤。
-
用户决策点必须显式确认
- 在 Claude Code 插件环境中，所有正式提问都使用
AskUserQuestion。 - 若当前环境没有该工具，使用等价的结构化提问方式代替。
- 每次只问一组相关问题，控制在 2-4 个独立问题内。
- 在 Claude Code 插件环境中，所有正式提问都使用
-
复杂任务才强制重流程
- 并行子代理探索、WBS 分解、模块规约、技术性验收标准，只在中等及以上复杂度逐步引入。
- 不要把系统级流程硬套到简单任务上。
-
计划文件必须面向零上下文执行者
- 最终计划默认假设执行者对代码库不熟悉。
- 执行步骤必须包含精确路径、关键代码片段、验证命令和预期结果。
-
先删范围，再加细节
- 先确认必须做什么，再细化如何做。
- 任何“可有可无”的功能都先经过 YAGNI 检查。
复杂度适配
| 复杂度 | 典型特征 | 必做步骤 | 可跳过步骤 |
|---|---|---|---|
| 简单 | 单模块、小范围、低风险、方案明确 | Phase 1、Phase 2、简化 Phase 3 | WBS、模块规约、技术性 AC |
| 中等 | 2-3 个模块、中等风险、需要拆解 | WBS、范围确认、风险检查 | 模块规约、技术性 AC |
| 复杂 | 多模块、高风险、涉及架构或接口设计 | 全流程；并行子代理探索；WBS；模块规约；技术性 AC | 无 |
| 系统级 | 从零构建系统，多服务/多端/数据库/API 联动 | 全流程；每个模块都要完整规约 | 无 |
默认判定规则：
- 从零搭建一个系统，默认按“系统级”处理
- 涉及数据库设计、接口设计、前端页面三者中的两项及以上，至少按“复杂”处理
- 涉及 4 个及以上功能模块，或预计开发超过 7 天，至少按“复杂”处理
- 仅单文件或单模块修改，通常是“简单”或“中等”
工作流
Phase 1：深度理解
目标： 搞清楚需求、现状、约束和待决策问题。
1. 先判定复杂度
先根据任务规模、风险和模块数量判断是简单、中等、复杂还是系统级。
这一步决定后续是否必须使用并行子代理、WBS 分解和模块规约。
2. 收集上下文
至少完成以下内容：
- 阅读相关命令、文档、模板和关键代码
- 找出现有实现模式、可复用模块和约束
- 识别关键文件、依赖关系和验证方式
3. 按复杂度决定是否并行探索
简单任务：
- 主 Agent 直接读取关键文件即可
中等任务：
- 如信息分散，可按 2-3 个维度启动并行探索子代理
复杂/系统级任务：
- 必须先做维度分析，再为每个维度启动独立探索子代理并行探索
- 不要把多个不相关维度塞进同一个子代理
推荐探索维度：
- 现有实现模式
- 相关模块与依赖
- 测试与验证方式
- 文档、规范与外部约束
4. 用 5 维度框架梳理需求
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 12d ago First seen · 456 lines · 65 tokens per session scan A 9522d1cdb6b8
planning is a skill published in the GitHub repository qqabcv520/my-claude-marketplaces (2 stars, last pushed 5mo ago), licensed MIT. It adds 65 tokens to every session and 4,046 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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