make_plan

A planning skill that asks another agent for a concrete, ordered plan and then carries out that plan itself. It can also save the plan in the project workspace.

In plain words
What is it for?
Use it to break down migrations, multi-step changes, or other complex tasks, save a dated plan, refine unclear steps, and execute the work.
Why use it?
It helps when a task spans several files, systems, or roles and the correct order is unclear. The plan includes dependencies, checkpoints, and ways to verify the result.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/mateaix/mateclaw/make_plan
Any agent
npx skills add mateaix/mateclaw --skill make_plan
Clone the repo
git clone --depth 1 https://github.com/mateaix/mateclaw

Made for: Claude Code, Codex.

Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 941 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00039 $0.00941
Opus 5 $0.00019 $0.00470
Sonnet 5 $0.00008 $0.00188
Haiku 4.5 $0.00004 $0.00094

Measured 2d ago against content hash c79940a8b134, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

make_plan 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 2d 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.

mateclaw-server/src/main/resources/skills/make_plan/SKILL.md · 134 lines

What it actually says

制定计划

本技能的目标:向更强 Agent 要计划,自己来执行。不是把任务外包出去,而是获得一份可落地的执行路径。

何时使用

应该使用

  • 任务需要多步拆解,步骤之间有依赖关系
  • 不确定执行顺序或关键检查点
  • 涉及多个模块、文件、系统或角色
  • 用户明确要求先给出计划
  • 想在动手前获得更完整、更稳妥的执行路径

不应使用

  • 任务很简单,一步就能完成
  • 真正缺的是一个小事实,而不是计划
  • 连任务目标都没理解清楚(先理解目标,再要计划)
  • 其实是想让对方直接替你执行任务(用 chat_with_agent

工作流程

第一步:查询可用 Agent

listAvailableAgents()

根据描述选择能力最强或最匹配任务领域的 Agent(没有合适的就用 default)。

第二步:请求计划

delegateToAgent(
  agentName="strong-agent",
  task="[来自 Agent my-agent 的请求] 请为以下任务制定执行计划。你不需要执行任务,只需要输出计划。

任务:
<描述要做什么>

目标:
<最终想达到什么结果>

约束:
- <限制条件1>
- <限制条件2>

计划要求:
1. 拆成明确、可执行的步骤
2. 标明推荐顺序
3. 指出关键依赖和检查点
4. 包含验证方式

输出格式:请输出 4-8 个编号步骤,每步具体说明。"
)

关键原则

  • 明确说明"只要计划,不要代执行"
  • 步骤必须具体,不接受"先分析,再实现"这类泛泛建议

第三步:保存计划文件(推荐)

将收到的计划写入工作区,方便后续追踪和恢复:

skillFileTool(
  action="write",
  path="plans/{YYYY-MM-DD}-{task-slug}.md",
  content="# 计划:{任务标题}\n\n{计划正文}"
)

文件名规范:plans/2026-04-23-migrate-database.md

好处:

  • 执行中断后可恢复进度
  • 用户可以审阅和修改计划
  • 多步任务完成后作为执行记录

第四步:提炼并执行

收到计划后:

  1. 提炼出真正可执行的步骤
  2. 按照当前环境做必要微调
  3. 由当前 Agent 自己执行这些步骤

收到计划不等于任务完成,计划是输入,执行才是输出。

第五步(如需细化):追问

如果计划某步骤不够具体,再次调用:

delegateToAgent(
  agentName="strong-agent",
  task="[来自 Agent my-agent 的请求] 请基于刚才的计划,细化第 3 步。仍然只需要补充计划细节,不需要代执行。

刚才的计划摘要:
<粘贴上次回复的关键内容>

需要细化的问题:
<具体的疑问>"
)

计划质量标准

合格的计划必须满足:

  • 有明确步骤,不是泛泛建议
  • 步骤顺序清楚
  • 每步是可执行的具体动作
  • 关键依赖被点明
  • 有必要的验证点

若收到的是空泛建议,继续追问细化,直到满足以上标准。

护栏

  • 不要把"请帮我规划"说成"请你直接做完"
  • 不要请求对方执行代码、命令或变更
  • 拿到计划后仍要结合当前环境判断,不要照单全收
  • 目标不清楚时,先弄清楚目标,再要计划
Changes

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.

  1. 2d ago First seen · 134 lines · 39 tokens per session scan A c79940a8b134

Subscribe to this mod's changes

make_plan is a skill published in the GitHub repository mateaix/mateclaw (1,061 stars, last pushed 2d ago), licensed Apache-2.0. It adds 39 tokens to every session and 941 once invoked, about $0.0002 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 2026-08-30.

Related

Other skills, from other repositories

make-skill

Use this skill when sedimenting a session into a reusable workspace skill. Triggers when the user wants to turn the current conversation, workflow, or troubleshooting path into a SKILL.md. Phrases like 'turn this into a skill', 'remember how I did X', 'save this workflow', 'make a skill from this', and any /make-skill…

agentscope-ai/QwenPaw · 85 tokens

make-skill

用于把当前会话沉淀为可复用的 workspace skill。当用户希望把当前对话、工作流或排错路径写成 SKILL.md 时触发。触发表达包括「把这个变成 skill」「记住我是怎么做 X 的」「保存这个工作流」「make a skill from this」以及任何 /make-skill 调用。.

agentscope-ai/QwenPaw · 84 tokens

terraform-skill

Use when working with Terraform or OpenTofu - creating modules, writing tests (native test framework, Terratest), setting up CI/CD pipelines, reviewing configurations, choosing between testing approaches, debugging state issues, implementing security scanning (trivy, checkov), or making infrastructure-as-code…

agentscope-ai/QwenPaw · 62 tokens

docx

Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when…

agentscope-ai/QwenPaw · 168 tokens

docx

当用户需要创建、读取、编辑或处理 Word 文档(.docx)时,使用此技能。触发场景包括提到“Word 文档”、“.docx”,或要求生成带目录、标题、页码、信头等格式的专业文档;也包括提取或重组 .docx 内容、插入或替换图片、在 Word 文件中查找替换、处理修订或批注,以及将内容整理为正式 Word 文档。如果用户要求生成“报告”“备忘录”“信函”“模板”等 Word / .docx 交付物,也应使用此技能。不要用于 PDF、电子表格、Google Docs,或与文档生成无关的一般编程任务。.

agentscope-ai/QwenPaw · 161 tokens

multi_agent_collaboration

Use this skill when another agent's expertise or context is needed, or when the user explicitly asks to involve another agent. First list agents, then use qwenpaw agents chat for two-way communication with replies.

agentscope-ai/QwenPaw · 47 tokens