feishu-task

feishu-task is a skill for Codex from DongLiStudio/personal-agent-foundation. It costs 193 tokens per session (4,362 once invoked), scanned A, original, Apache-2.0.

A procedure for creating, completing, finding, updating, and rereading tasks in Feishu/Lark. It also handles task details such as people, dates, status, workload, and attachments.

In plain words
What is it for?
Use it to search or create Feishu tasks, assign people, add followers and attachments, update task fields, and assess whether changes affect the user's schedule.
Why use it?
It turns requests or meeting material into consistent tasks and checks the result after writing it.

Skill for Codex

Written for Codex: agents/openai.yaml present. Also seen: installed under .agents/ (shared by several agents); mentions AGENTS.md.

Good fit Use it to search or create Feishu tasks, assign people, add followers and attachments, update task fields, and assess whether changes affect the user's schedule.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/donglistudio/personal-agent-foundation/feishu-task
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.

Any agent
npx skills add DongLiStudio/personal-agent-foundation --skill feishu-task
Clone the repo
git clone --depth 1 https://github.com/DongLiStudio/personal-agent-foundation

Made for: 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 feishu-task

README.md
[![agentmods](https://agentmods.dev/badge/skills/donglistudio/personal-agent-foundation/feishu-task/github.svg)](https://agentmods.dev/skills/donglistudio/personal-agent-foundation/feishu-task)
Your own site
<a href="https://agentmods.dev/skills/donglistudio/personal-agent-foundation/feishu-task"><img src="https://agentmods.dev/badge/skills/donglistudio/personal-agent-foundation/feishu-task/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.

agentmods 80×15 button for feishu-task

Your own site · 80×15
<a href="https://agentmods.dev/skills/donglistudio/personal-agent-foundation/feishu-task"><img src="https://agentmods.dev/badge/skills/donglistudio/personal-agent-foundation/feishu-task.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 193 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,362 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 5.1 $0.00193 $0.04362
Opus 5 $0.00097 $0.02181
Sonnet 5 $0.00039 $0.00872
Haiku 4.5 $0.00019 $0.00436

Measured 8d ago against content hash 740f5a940666, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

feishu-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 8d 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.

template/GLOBAL/.agents/skills/feishu-task/SKILL.md · 146 lines

How it starts

The opening of the file, as written. The whole thing — 146 lines — stays where its author put it; the contents beside it link to each section on GitHub.

飞书任务

固定依赖

  • 执行业务命令前先确认 lark-cli 可用:优先用当前 shell 的命令发现机制,例如 Get-Command lark-cli;Windows 下如命令不在 PATH,可按当前 npm 全局前缀或 %APPDATA%\npm 等用户级 shim 机制定位 lark-cli.cmd/lark-cli.ps1,不要硬编码单一用户名路径。仍不可用时,转 feishu-profile 做 CLI 安装、Profile 或 workspace 恢复,不直接进入任务业务调用。
  • 优先通过 lark-cli skills read lark-task 读取当前 CLI 内嵌、版本匹配的任务规则;读取操作引用时使用 lark-cli skills read lark-task references/<文件>。当前 CLI 不支持内嵌读取时,才使用已安装且版本匹配的 Skill 副本。
  • 使用 lark-task 执行搜索、创建、更新、成员、关注人、附件和回读;使用全局 feishu-profile 处理认证、Profile、user identity、换机恢复与配置冲突,并按需读取 CLI 内嵌 lark-shared 规则。
  • 涉及姓名解析时使用 lark-contact,不得猜测人员 open_id
  • 截图附件需要局部脱敏时使用 imagegen 或当前可用的等效图像编辑能力;完成后必须回查,不能把编辑成功等同于脱敏合格。
  • 按实际操作读取 create、update、search、followers、attachment 等引用;设置开始时间前必须确认当前 CLI 内嵌 lark-taskstart 的真实支持与语法。
  • 创建或更新 start 时以当前 CLI 的 skills readschema 和命令 --help 为准;若 shortcut 没有 start flag,则按当前 schema 使用原生 task tasks create --data ... / task tasks patch --data ... 或等价 JSON payload。更新 start 时必须按当前 schema 把 start 纳入更新字段。
  • 任务写入后的排程影响判断使用 personal-schedule-planner飞书任务排程联动契约scripts/task_schedule_handoff.py;通过当前已安装 Skill 入口解析脚本位置,不硬编码用户目录。

选择飞书账号与身份

每次执行按以下优先级解析 Profile,低优先级不得覆盖高优先级:

  1. 用户在当前请求中明确指定的账号、公司或 Profile。
  2. 当前项目中与目标主体或资源直接匹配的条件化路由。
  3. 当前项目 AGENTS.md、项目专属 Skill 或项目长期规则明确指定的项目默认 Profile。
  4. GLOBAL/LARK_PROFILES.md 记录的全局默认 Profile。

“当前一句话未提账号”不等于“项目或 GLOBAL 未指定账号”。先检查项目条件化路由和默认规则,再继承 GLOBAL 默认。确定 Profile 后立即通过 auth status 获取实际 Profile、身份类型、当前用户姓名和 open_id,并在本次任务的全部命令中保持同一 Profile 和 user identity。

  • 项目或用户明确指定 Profile 时,所有命令显式传入 --profile <Profile> --as user
  • 使用 GLOBAL 默认 Profile 时,从 GLOBAL/LARK_PROFILES.md 读取治理层默认值,后续命令显式固定该 Profile;CLI active 只用于核验和发现冲突,不得覆盖 GLOBAL 默认。
  • 若运行环境注入的临时配置、工作区绑定、环境变量或 CLI active/default 运行值覆盖项目或 GLOBAL 已解析的 Profile/身份,将其视为身份配置冲突。仅在当前命令进程中隔离冲突来源,再重新显式指定已解析的 Profile 和 --as user
  • 不修改全局 active Profile、全局配置或其他项目绑定,不绑定其他主体,不暴露凭据,不静默切换公司,不回退到 bot 身份。
  • 指定 Profile 不存在、默认 Profile 无效、登录用户不明或 user 授权不足时,在读取敏感数据或写入任务前转交全局 feishu-profile 检查和恢复;仅在主体不明或多个高优先级来源冲突时询问用户。

Read the full file on GitHub · 146 lines

Files

What ships with it

3 files 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.

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. 8d ago First seen · 146 lines · 193 tokens per session scan A 740f5a940666

Subscribe to this mod's changes

feishu-task is a skill published in the GitHub repository DongLiStudio/personal-agent-foundation (11 stars, last pushed 22d ago), licensed Apache-2.0. It adds 193 tokens to every session and 4,362 once invoked, about $0.0010 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

harness

Use when governing a workspace's control plane, code or not — the 01-TOOLS/ tooling layer, the 02-DOCS/ chaos→knowledge wiki, the root Knowledge map. Audits it, migrates legacy XX- folders, scaffolds provider tooling, sweeps the inbox, writes root CLAUDE.md/AGENTS.md. NOT the bootstrap front door (that is init, which…

ericrisco/rsc-harness · 94 tokens

swarmauri-add-standards-standalone

Add a first-class standalone Swarmauri package under pkgs/standards. Use when Codex needs package scaffolding, workspace membership, pyproject metadata, Swarmauri or Tigrbl branding, entry points, first-class citizenship registry rows, exports, tests, and validation.

swarmauri/swarmauri-sdk · 69 tokens

recipe-create-meet-space

Create a Google Meet meeting space and share the join link.

googleworkspace/cli · 18 tokens

workthreads

SpecStory Workthreads - a weekly work-thread rollup across a team's repos from SpecStory coding histories (any agent - Claude Code, Codex, Cursor, Gemini, and more). It groups the window's sessions into threads of work per project and labels each new / open / recently closed, so a lead sees what shipped, what is still…

specstoryai/getspecstory · 126 tokens

atmos-config

Atmos root configuration: atmos.yaml discovery, precedence, deep merging, basepath, imports, minimal bootstrap, and routing to narrower Atmos skills.

cloudposse/atmos · 31 tokens

story-readiness

Validate that a story file is implementation-ready. Checks for embedded GDD requirements, ADR references, engine notes, clear acceptance criteria, and no open design questions. Produces READY / NEEDS WORK / BLOCKED verdict with specific gaps. Use when user says 'is this story ready', 'can I start on this story', 'is…

Donchitos/Claude-Code-Game-Studios · 77 tokens