lark-task

lark-task is a skill for Claude Code, Codex from yokingma/weclaws. It costs 125 tokens per session (2,776 once invoked), scanned A, a copy of lark-task, MIT.

A Lark task-management skill for working with to-dos, task lists, subtasks, assignments, attachments, and task agents.

In plain words
What is it for?
Creating, searching, updating, assigning, and organizing tasks, uploading attachments, and managing task-agent records.
Why use it?
It provides one place to handle task information instead of manually tracking task status, ownership, and related files.

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/yokingma/weclaws/lark-task
Any agent
npx skills add yokingma/weclaws --skill lark-task
Clone the repo
git clone --depth 1 https://github.com/yokingma/weclaws

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for lark-task

README.md
[![agentmods](https://agentmods.dev/badge/skills/yokingma/weclaws/lark-task.svg)](https://agentmods.dev/skills/yokingma/weclaws/lark-task)
Your own site
<a href="https://agentmods.dev/skills/yokingma/weclaws/lark-task"><img src="https://agentmods.dev/badge/skills/yokingma/weclaws/lark-task.svg" alt="Measured on agentmods" height="20"></a>
Per session 125 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,776 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod 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 $0.00125 $0.02776
Opus 5 $0.00063 $0.01388
Sonnet 5 $0.00025 $0.00555
Haiku 4.5 $0.00013 $0.00278

Measured 4d ago against content hash de46893379ad, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

lark-task 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 4d 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.

Origin

This is a copy

100% identical to lark-task — 0 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.

resources/skills/managed/lark-task/SKILL.md · 166 lines

How it starts

The opening of the file, as written. The whole thing — 166 lines — stays where its author put it; the contents beside it link to each section on GitHub.

task (v2)

CRITICAL — 开始前 MUST 先用 Read 工具读取 ../lark-shared/SKILL.md,其中包含认证、权限处理

任务搜索技巧:先区分用户是否特地指定使用搜索 skill,以及是否真的提供了查询关键字(例如任务名称、关键词、片段描述)。如果用户特地指定使用搜索 skill,或明确给出了任务查询关键字,则目标是任务时优先使用 +search。如果用户没有特地指定使用搜索 skill,且意图里没有查询关键字,只有范围条件(例如“今年以来”“已完成”“由我创建”“我关注的”),并且使用 +search+get-related-tasks / +get-my-tasks 都能达到目的时,应优先使用列表型能力,而不是搜索型能力。其中,“与我相关 / 我关注的 / 由我创建”等优先考虑 +get-related-tasks;“我负责的 / 分配给我”的列表优先考虑 +get-my-tasks。不要把时间范围词(例如“今年以来”)本身误当成 query 去走搜索。 任务清单搜索技巧:任务清单也遵循同样的判断逻辑。先区分用户是否特地指定使用搜索 skill,以及是否真的提供了清单查询关键字(例如清单名称、关键词、片段描述)。如果用户特地指定使用搜索 skill,或明确给出了清单查询关键字,则优先使用 +tasklist-search。如果用户没有特地指定使用搜索 skill,且意图里没有查询关键字,只有范围条件(例如“由我创建的任务清单”“今年以来创建的清单”),并且使用搜索或原生列取清单都能达到目的时,应优先使用原生 tasklists.list 接口列取清单(先 schema task.tasklists.list,再 lark-cli task tasklists list --as user ...),再按 creatorcreated_at 等字段做本地筛选和分页控制。 意图区分补充:像“搜索飞书中今年以来我关注的任务”这类表达,虽然字面带有“搜索”,但如果没有真正的查询关键字,且本质是在限定“与我相关 + 时间范围”,则应优先走 +get-related-tasks;像“搜索飞书中由我创建的任务清单”这类表达,如果没有清单关键字,且本质是在限定“清单范围 + 创建者”,则应优先走原生 tasklists.list 后筛选,而不是直接走搜索型 shortcut。 用户身份识别:在用户身份(user identity)场景下,如果用户提到了“我”(例如“分配给我”、“由我创建”),请默认获取当前登录用户的 open_id 作为对应的参数值。 术语理解:如果用户提到 “todo”(待办),应当思考其是否是指“task”(任务),并优先尝试使用本 Skill 提供的命令来处理。 友好输出:在输出任务(或清单)的执行结果给用户时,建议同时提取并输出命令返回结果中的 url 字段(任务链接),以便用户可以直接点击跳转查看详情。

创建/更新注意

  1. 只有在设置了 due(截止时间)的情况下,才能设置 repeat_rule(重复规则)和 reminder(提醒时间)。
  2. 若同时设置了 start(开始时间)和 due(截止时间),开始时间必须小于或等于截止时间。
  3. 使用 tenant_access_token(应用身份)时,无法跨租户添加任务成员。

查询注意

  1. 在输出任务详情时,如果需要渲染负责人、创建人等人员字段,除了展示 id (例如 open_id) 外,还必须通过其他方式(例如调用通讯录技能)尝试获取并展示这个人的真实名字,以便用户更容易识别。
  2. 在输出清单详情时,如果需要渲染 owner、member、角色成员等人员字段,也必须像任务成员展示一样,除了展示 id 外,尽量解析并展示对应人员的真实名字。
  3. 在输出任务或清单详情时,如果需要渲染创建时间、截止时间等字段,需要使用本地时区来渲染(格式为2006-01-02 15:04:05)。

Task GUID 定义: Task OpenAPI 中用于更新/操作任务的 guid 是任务的全局唯一标识(GUID),不是客户端展示的任务编号(例如 t104121 / suite_entity_num)。 对于 Feishu 的任务 applink(例如 .../client/todo/task?guid=...),必须使用 URL query 里的 guid 参数作为 task guid。

Read the full file on GitHub · 166 lines

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. 4d ago First seen · 166 lines · 125 tokens per session scan A de46893379ad

Subscribe to this mod's changes

lark-task is a skill published in the GitHub repository yokingma/weclaws (38 stars, last pushed 3mo ago), licensed MIT. It adds 125 tokens to every session and 2,776 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to lark-task, differing in 0 lines, and is treated as a copy.

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