Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/appleweiping/WEIPING_WIKInpx agentmods add skills/appleweiping/weiping_wiki/lark-skill-makerWrote 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/appleweiping/weiping_wiki/lark-skill-maker)<a href="https://agentmods.dev/skills/appleweiping/weiping_wiki/lark-skill-maker"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-skill-maker/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/appleweiping/weiping_wiki/lark-skill-maker"><img src="https://agentmods.dev/badge/skills/appleweiping/weiping_wiki/lark-skill-maker.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 | $0.00046 | $0.00717 |
| Opus 5 | $0.00023 | $0.00358 |
| Sonnet 5 | $0.00009 | $0.00143 |
| Haiku 4.5 | $0.00005 | $0.00072 |
Grade A, and why
lark-skill-maker 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 7d 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.
This is a copy
91% identical to lark-skill-maker — 2 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Skill Maker
基于 lark-cli 创建新 Skill。Skill = 一份 SKILL.md,教 AI 用 CLI 命令完成任务。
CLI 核心能力
lark-cli <service> <resource> <method> # 已注册 API
lark-cli <service> +<verb> # Shortcut(高级封装)
lark-cli api <METHOD> <path> [--data/--params] # 任意飞书 OpenAPI
lark-cli schema <service.resource.method> # 查参数定义
优先级:Shortcut > 已注册 API > api 裸调。
调研 API
# 1. 查看已有的 API 资源和 Shortcut
lark-cli <service> --help
# 2. 查参数定义
lark-cli schema <service.resource.method>
# 3. 未注册的 API,用 api 直接调用
lark-cli api GET /open-apis/vc/v1/rooms --params '{"page_size":"50"}'
lark-cli api POST /open-apis/vc/v1/rooms/search --data '{"query":"5F"}'
如果以上命令无法覆盖需求(CLI 没有对应的已注册 API 或 Shortcut),使用 lark-openapi-explorer 从飞书官方文档库逐层挖掘原生 OpenAPI 接口,获取完整的方法、路径、参数和权限信息,再通过 lark-cli api 裸调完成任务。
通过以上流程确定需要哪些 API、参数和 scope。
SKILL.md 模板
文件放在 skills/lark-<name>/SKILL.md:
---
name: lark-<name>
description: "<功能描述>。当用户需要<触发场景>时使用。"
metadata:
requires:
bins: ["lark-cli"]
---
# <标题>
> **前置条件:** 先阅读 [`../lark-shared/SKILL.md`](../lark-shared/SKILL.md)。
## 命令
\```bash
# 单步操作
lark-cli api POST /open-apis/xxx --data '{...}'
# 多步编排:说明步骤间数据传递
# Step 1: ...(记录返回的 xxx_id)
# Step 2: 使用 Step 1 的 xxx_id
\```
## 权限
| 操作 | 所需 scope |
|------|-----------|
| xxx | `scope:name` |
关键原则
- description 决定触发 — 包含功能关键词 + "当用户需要...时使用"
- 认证 — 说明所需 scope,登录用
lark-cli auth login --domain <name> - 安全 — 写入操作前确认用户意图,建议
--dry-run预览 - 编排 — 说明数据传递、失败回滚、可并行步骤
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.
- 7d ago First seen · 84 lines · 46 tokens per session scan A 6652bd1e4ffa
lark-skill-maker is a skill published in the GitHub repository appleweiping/WEIPING_WIKI (122 stars, last pushed 15d ago), licensed MIT. It adds 46 tokens to every session and 717 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 91% identical to lark-skill-maker, differing in 2 lines, and is treated as a copy.
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