Agent skill

Dingtalk Teambition

by LeoYeAI in LeoYeAI/openclaw-master-skills

A skill your agent uses for anything related to Teambition tasks and projects.

MITAuto-check passedDevelopment

Install Dingtalk Teambition

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dingtalk-teambition-project .claude/skills/dingtalk-teambition && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
dingtalk-teambition
GitHub stars
2.2k
Token cost
~3.7k tokens
SKILL.md length
775 words
Files
34 (incl. scripts, references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses for anything related to Teambition tasks and projects.

  • Works in 12 steps: me():TQL 中查询"我的"任务/项目,必须用 executorId =… → 时区:create_task.py / update_task.py /… → ID→名称:API 返回的各类 ID 字段均为原始 ID… → …
  • Anything related to Teambition tasks and projects
  • SKILL.md covers 适用场景, 环境准备, 核心规则 and 脚本速查, plus 3 more sections
  • Runs Python scripts from its folder; calls uv; reaches teambition.com and xxx.com; needs TEAMBITION_USER_TOKEN

What it does

Dingtalk Teambition is an agent skill from LeoYeAI/openclaw-master-skills. Use for anything related to Teambition tasks and projects. Triggers on: checking my todos, what tasks are due today or this week, create a task, update task status or priority or assignee or note, mark task as done, query overdue tasks, search tasks by keyword, view task details, upload file to task, check team members, query project list, add task comment with @mention, track task progress. NOT for: non-Teambition platforms or Git operations.

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 35 other files, including scripts and reference files (for example `README.md`, `_meta.json` and `package.json`).

It sits in Development. It works with Git. The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.

When your agent uses it

  • Anything related to Teambition tasks and projects
  • : checking my todos
  • What tasks are due today
  • Update task status

Example prompts

  • “/dingtalk-teambition”

Requirements

  • Python 3
  • A credential in TEAMBITION_USER_TOKEN

Workflow steps

12 steps, taken from the first numbered list in SKILL.md.

  1. me():TQL 中查询"我的"任务/项目,必须用 executorId = me(),禁止硬编码用户 ID
  2. 时区:create_task.py / update_task.py / manage_sprint.py 已内置东八区→UTC 转换,直接传本地时间即可;不要手动传 UTC 时间(会被再次转换导致偏差)。转换逻辑参考
  3. ID→名称:API 返回的各类 ID 字段均为原始 ID 字符串,展示给用户前必须转换为可读名称,禁止直接展示原始 ID。
  4. 优先级:数值含义为 0=紧急 1=高 2=中 3=低,但企业通常会自定义优先级名称,脚本输出的 priorityLabel 仅为系统默认值,不代表该企业的真实配置。
  5. 归档 vs 删除:归档任务会移入回收站,不在正常列表显示,可通过 --restore 恢复;归档不等于删除
  6. 动态 vs 进展:动态(activity)是系统自动记录的操作历史(状态变更、字段修改等);进展(trace)是用户手动填写的阶段性状态更新
  7. 迭代操作顺序:先用 --action create --project-id --name <名> 创建迭代获取 sprint-id,再用 --action start --project-id --sprint-id 开始,完成后用 --action complete…
  8. 状态查询优先:更新任务状态时,优先使用 get_task_statuses.py 直接查询该任务的工作流状态列表,无需先获取 projectId;只有创建任务需要初始状态时才用 get_taskflow_statuses.py
  9. 按需读文档:TQL 语法 → references/tql.md;进展/评论/动态/归档 → references/task-ops.md;错误处理 → references/error-handling.md
  10. 文件上传流程:先用 upload_file.py 上传文件获取 fileToken,再用 create_comment.py --file-tokens 将文件附加到评论;两步均走脚本,无需直接调 API
  11. ID 链接渲染:当回复中涉及任务 ID 或项目 ID 时,必须将其渲染为可点击的链接,格式如下
  12. 任务的 content = 标题:API 返回的 content 字段就是任务的标题,向用户展示时统一使用"标题"而非"内容",避免混淆;create_task.py 和 update_task.py 都统一使用 --title 参数

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 9 files in scripts/ (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • teambition.com
    • xxx.com

    Also links to:

    • open.teambition.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • TEAMBITION_USER_TOKEN

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dingtalk Teambition loads about 3.7k tokens when it runs, and up to ~8.7k if it reads all its reference files. Until then it costs about 117 tokens; SKILL.md has 775 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~117
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~8.7k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 775 words, ~3,681 tokens.

Download SKILL.mdSave it as .claude/skills/dingtalk-teambition/SKILL.md (or your agent's skills folder). This skill also uses 33 other files; get the full folder from GitHub.
name
dingtalk-teambition
description
Use for anything related to Teambition tasks and projects. Triggers on: checking my todos, what tasks are due today or this week, create a task, update task status or priority or assignee or note, mark task as done, query overdue tasks, search tasks by keyword, view task details, upload file to task, check team members, query project list, add task comment with @mention, track task progress. NOT for: non-Teambition platforms or Git operations.
version
1.0.0

适用场景

✅ 适合使用本技能:

  • 查询我的待办任务、今天/本周到期的任务、逾期任务
  • 创建、更新、归档任务
  • 更新任务状态、优先级、执行人、备注
  • 管理任务进展、评论(支持 @提及)、动态
  • 上传文件到任务
  • 查询项目列表、项目详情
  • 查询企业成员
  • 管理迭代(创建/开始/完成)

❌ 不适用场景:

  • 操作非 Teambition 平台(Jira、Asana 等)
  • Git 操作或代码管理 → 直接使用 git
  • 管理脚本未覆盖的 Teambition 组织/管理员设置

环境准备

获取 User Token:Teambition 开放平台

bash
# 方式 1:环境变量
export TEAMBITION_USER_TOKEN="your_token"

# 方式 2:在 dingtalk-teambition/ 目录下创建 user-token.json
# {"userToken": "your_token"}

cd dingtalk-teambition && uv sync

核心规则

  1. me():TQL 中查询"我的"任务/项目,必须用 executorId = me(),禁止硬编码用户 ID

  2. 时区:create_task.py / update_task.py / manage_sprint.py 已内置东八区→UTC 转换,直接传本地时间即可;不要手动传 UTC 时间(会被再次转换导致偏差)。转换逻辑参考:

    python
    from datetime import datetime, timedelta
    user_date = "2026-03-15"
    dt = datetime.strptime(user_date, "%Y-%m-%d") - timedelta(hours=8)
    iso_date = dt.strftime("%Y-%m-%dT%H:%M:%S.000Z")
    # 结果:2026-03-14T16:00:00.000Z
  3. ID→名称:API 返回的各类 ID 字段均为原始 ID 字符串,展示给用户前必须转换为可读名称,禁止直接展示原始 ID。

    • 需要转换的常见 ID 字段:
      字段含义转换方式
      executorId执行人query_members.py --user-ids <ID> 批量查询
      creatorId创建人query_members.py --user-ids <ID> 批量查询
      involveMembers参与人列表query_members.py --user-ids <ID1,ID2,...> 批量查询
      sprintId所属迭代query_project_detail.py <projectId> 获取迭代列表后匹配
      stageId所属任务列任务详情中通常包含 stageName,否则需查项目工作流
      projectId所属项目项目名通常已在上下文中,或用 query_project_detail.py 查询
      parentTaskId父任务query_task_detail.py <parentTaskId> 获取父任务标题
    • 展示任务列表/详情时的必要步骤:
      1. 收集所有任务中出现的各类 ID(去重)
      2. 批量查询对应的名称(人员用 query_members.py,项目/迭代/任务用各自的查询脚本)
      3. 将 ID 替换为名称后再向用户展示
    • 如果无法确定某个 ID 对应的名称,可展示为"未知"或保留该字段不展示,不要直接展示原始 ID
    bash
    # 按姓名搜索成员,获取 userId
    uv run scripts/query_members.py --keyword "张三"
    # 返回结果中匹配 userId,确认后用于展示或操作
    
    # 批量按用户ID查询成员(推荐用于ID转换)
    uv run scripts/query_members.py --user-ids "id1,id2,id3"
  4. 优先级:数值含义为 0=紧急 1=高 2=中 3=低,但企业通常会自定义优先级名称,脚本输出的 priorityLabel 仅为系统默认值,不代表该企业的真实配置。

    • 展示优先级名称前必须先查询企业配置,查询链路:
      1. 从任务详情获取 projectId
      2. uv run scripts/query_project_detail.py <projectId> --extra-fields organizationId 获取 organizationId
      3. uv run scripts/get_priority_list.py <organizationId> 获取企业真实优先级列表
    • 返回结果中每条优先级包含 priority(数值)和 name(企业自定义名称),以此覆盖默认 label 后再展示
    • 更新优先级前同样需要先查询,将用户描述的优先级名称与企业配置匹配后,再用对应的 priority 数值调用更新接口
  5. 归档 vs 删除:归档任务会移入回收站,不在正常列表显示,可通过 --restore 恢复;归档不等于删除

  6. 动态 vs 进展:动态(activity)是系统自动记录的操作历史(状态变更、字段修改等);进展(trace)是用户手动填写的阶段性状态更新

  7. 迭代操作顺序:先用 --action create --project-id <id> --name <名> 创建迭代获取 sprint-id,再用 --action start --project-id <id> --sprint-id <id> 开始,完成后用 --action complete --project-id <id> --sprint-id <id>;start/complete 都需要同时传 --project-id 和 --sprint-id

  8. 状态查询优先:更新任务状态时,优先使用 get_task_statuses.py <taskId> 直接查询该任务的工作流状态列表,无需先获取 projectId;只有创建任务需要初始状态时才用 get_taskflow_statuses.py

  9. 按需读文档:TQL 语法 → references/tql.md;进展/评论/动态/归档 → references/task-ops.md;错误处理 → references/error-handling.md

  10. 文件上传流程:先用 upload_file.py 上传文件获取 fileToken,再用 create_comment.py --file-tokens <token> 将文件附加到评论;两步均走脚本,无需直接调 API

  11. ID 链接渲染:当回复中涉及任务 ID 或项目 ID 时,必须将其渲染为可点击的链接,格式如下:

    • 任务链接:https://www.teambition.com/task/{taskId}
    • 项目链接:https://www.teambition.com/project/{projectId}
  12. 任务的 content = 标题:API 返回的 content 字段就是任务的标题,向用户展示时统一使用"标题"而非"内容",避免混淆;create_task.py 和 update_task.py 都统一使用 --title 参数

  13. 空字段隐藏:展示任务或项目信息时,值为空、null、0、false 或空数组的字段应当隐藏,不向用户展示,只展示有实际值的字段。例如:

    • 进度为 0 → 不展示进度
    • 截止时间为 null → 不展示截止时间
    • 备注为空字符串 → 不展示备注
    • 迭代为 null → 不展示迭代
    • 标签为空数组 → 不展示标签
    • 此规则适用于所有可选字段,保持信息展示简洁
  14. 自定义字段更新格式:使用 --customfields 更新任务自定义字段时,不同类型有不同格式:

    bash
    # 日期类型(date):value 是数组,包含带 title 的对象,日期格式为 ISO 8601
    uv run scripts/update_task.py --task-id 'xxx' \
      --customfields '[{"customfieldId": "字段ID", "value": [{"title": "2026-03-16T00:00:00.000Z"}]}]'
    # 文本类型(text):value 是数组,包含带 title 的对象
    uv run scripts/update_task.py --task-id 'xxx' \
      --customfields '[{"customfieldId": "字段ID", "value": [{"title": "文本内容"}]}]'
    # 单选类型(select):value 是数组,包含带 id 的选项对象
    uv run scripts/update_task.py --task-id 'xxx' \
      --customfields '[{"customfieldId": "字段ID", "value": [{"id": "选项ID"}]}]'
  15. 文件类型自定义字段上传:使用 upload_file_to_customfield.py 一站式上传文件到自定义字段:

    bash
    uv run scripts/upload_file_to_customfield.py \
      --task-id '<taskId>' \
      --file-path '/path/to/file.pdf' \
      --customfield-id '<字段ID>'
  16. 自定义字段文件类型展示:自定义字段中类型为 work(文件附件)的字段,展示时必须将文件名渲染为可点击的下载链接,使用字段值中的 downloadUrl 字段作为链接地址,格式如下:

    • 展示格式:[文件名](downloadUrl)
    • 示例:[材料.md](https://xxx.com/...)
    • 若一个字段包含多个文件,每个文件单独渲染为一个链接
    • 禁止只展示文件名而不附带链接
  17. 批量任务表格输出:当查询返回多个任务(2个及以上)时,默认使用表格形式展示,表格列应包含:标题、状态、优先级、执行人、截止时间。单行任务仍使用文本段落形式展示,保持信息清晰易读。

  18. 破坏性操作需确认:执行归档任务(archive_task.py)、删除等不可逆或影响较大的操作前,必须先向用户确认,展示操作对象(任务标题/ID)和操作类型,获得明确同意后再执行。例如:

    • "确认归档任务「完成需求文档」(ID: xxx)吗?归档后可从回收站恢复。"
    • "确认删除该评论吗?删除后无法恢复。"
  19. 空字段不返回:API 查询任务详情时,值为空的自定义字段不会被返回。如果一个文件类型字段从未被赋值过,customfields 数组中不会包含该字段。要查看任务可填写的所有自定义字段,需要:

    bash
    # 1. 从任务详情获取 sfcId(任务类型ID)和 projectId
    uv run scripts/query_task_detail.py <taskId> --detail-level detailed
    
    # 2. 查询该任务类型可用的所有自定义字段
    uv run scripts/get_custom_fields.py <projectId> --sfc-id <sfcId>

    返回结果中 type 为 work 的字段就是文件类型字段


脚本速查

脚本用途关键参数
query_tasks.py查询任务列表(TQL),默认返回:标题、状态、优先级、执行人ID、截止时间、备注、迭代、任务列、开始时间、进度、父任务ID--tql <TQL> --page-size N --page-token T --no-details --extra-fields f1,f2
query_task_detail.py <id1,id2>查询任务详情(支持批量)--detail-level simple|detailed --extra-fields f1,f2
create_task.py创建任务--title <标题>(必需)--project-id --executor-id --due-date --priority
update_task.py更新任务(多字段并行)--task-id <id>(必需)--title --executor-id --due-date --note --priority --taskflowstatus-id
update_task_priority.py单独更新优先级(更新前必须先用 get_priority_list.py 查企业配置)--task-id <id> --priority <0-3>
create_comment.py创建评论--task-id <id> --content <内容> --mention <姓名> --mention-id <userId> --file-tokens <token>
query_projects.py查询项目列表(TQL)--tql <TQL> --page-size N --page-token T --no-details --include-template
query_project_detail.py <id>查询项目详情(支持批量)--detail-level simple|detailed --extra-fields f1,f2
query_members.py搜索成员(支持批量ID查询)--keyword <姓名> --user-ids <ID1,ID2,...>
get_task_statuses.py <taskId>查询任务工作流状态列表(推荐)--q <关键词>
get_taskflow_statuses.py <projectId>获取项目工作流状态(创建任务时用)--only-start --q <关键词>
get_custom_fields.py <projectId>获取项目自定义字段配置--cf-ids <IDs> --sfc-id <ID>
get_scenario_types.py <projectId>获取项目任务类型列表--q <关键词> --sfc-ids <IDs>
get_priority_list.py <organizationId>获取企业优先级配置—
get_current_user.py获取当前登录用户信息(userId、name、email 等)—
create_trace.py添加任务进展--task-id <id> --title <标题> --status <1-3>
upload_file.py上传文件,返回 fileToken--file-path <路径> --scope task:<id> --category attachment
archive_task.py归档/恢复任务--task-id <id> [--restore]
query_task_activity.py查询任务动态--task-id <id> --actions comment
manage_sprint.py迭代管理--action list|create|start|complete --project-id <id> --sprint-id <id> --name <名>
Show full SKILL.md (273 more words)Show less
query_task_detail.py 参数说明
参数类型必需说明
任务ID字符串是任务 ID,逗号分隔支持批量
--detail-level字符串否simple(默认)或 detailed
--extra-fields字符串否simple 模式下额外包含的字段,逗号分隔

simple(默认) 包含字段:

字段说明
id任务 ID
content任务标题
isDone是否完成
executorId执行人 ID
projectId项目 ID
dueDate截止时间
priority优先级(0=紧急,1=高,2=中,3=低)
created创建时间
updated更新时间
note备注

detailed 额外包含:sprintId(迭代 ID)stageId(任务列 ID)startDate(开始时间)progress(进度)parentTaskId(父任务 ID)及自定义字段等 30+ 字段

query_project_detail.py 参数说明
参数类型必需说明
项目ID字符串是项目 ID,逗号分隔支持批量
--detail-level字符串否simple(默认)或 detailed
--extra-fields字符串否simple 模式下额外包含的字段,逗号分隔

simple(默认) 包含字段:

字段说明
id项目 ID
name项目名称
description项目描述
visibility可见性(public/private)
isTemplate是否是模板项目
creatorId创建人 ID
isArchived是否在回收站
isSuspended是否已归档
created创建时间
updated更新时间

detailed 额外包含:logo(项目 LOGO)organizationId(企业 ID)uniqueIdPrefix(任务 ID 前缀)startDate(开始时间)endDate(结束时间)等 20+ 字段


TQL 快速参考

任务 TQL 常用场景
场景TQL
我的待办任务executorId = me() AND isDone = false
我的逾期任务executorId = me() AND isDone = false AND dueDate < startOf(d)
今天截止的任务executorId = me() AND dueDate >= startOf(d) AND dueDate <= endOf(d)
本周截止的任务executorId = me() AND dueDate >= startOf(w) AND dueDate <= endOf(w)
即将逾期(未来3天)executorId = me() AND isDone = false AND dueDate >= startOf(d) AND dueDate <= endOf(d, 3d)
过去7天更新的任务executorId = me() AND updated >= startOf(d, -7d)
高优先级未完成priority = 0 AND isDone = false
标题模糊搜索title ~ '关键词'
全文搜索(标题+备注)text ~ '关键词'
指定项目的任务projectId = 'xxx'

完整 TQL 语法(字段、运算符、时间函数)→ references/tql.md

项目 TQL 常用场景
场景TQL
我参与的项目involveMembers = me()
我创建的项目creatorId = me()
按名称搜索nameText ~ '关键词'
已归档的项目isSuspended = true
今天更新的项目updated >= startOf(d) AND updated <= endOf(d)
今天创建的项目created >= startOf(d) AND created <= endOf(d)
本周创建的项目created >= startOf(w) AND created <= endOf(w)
本月创建的项目created >= startOf(M) AND created <= endOf(M)
过去7天创建的项目created >= startOf(d, -7d)
指定日期范围创建created >= '2026-03-01T00:00:00.000Z' AND created <= '2026-03-31T23:59:59.999Z'

⚠️ 项目没有截止时间(dueDate)字段,只有 created 和 updated。

完整项目 TQL → references/project-tql.md


常用命令示例

查询任务
bash
# 我的待办任务
uv run scripts/query_tasks.py --tql "executorId = me() AND isDone = false"
# 注意:返回的 executorId 是原始 ID,需批量调用 query_members.py --user-ids 转换为姓名后展示

# 我的逾期任务,按截止时间升序
uv run scripts/query_tasks.py --tql "executorId = me() AND isDone = false AND dueDate < startOf(d) ORDER BY dueDate ASC"
# 返回的 executorId 需批量转换为姓名:uv run scripts/query_members.py --user-ids "<id1,id2,...>"

# 本周截止的任务
uv run scripts/query_tasks.py --tql "executorId = me() AND dueDate >= startOf(w) AND dueDate <= endOf(w)"

# 标题搜索
uv run scripts/query_tasks.py --tql "title ~ '需求'"

# 查询任务详情(simple 默认,含 note)
uv run scripts/query_task_detail.py <taskId>

# 查询详细信息(含自定义字段等)
uv run scripts/query_task_detail.py <taskId> --detail-level detailed

# 批量查询多个任务
uv run scripts/query_task_detail.py id1,id2,id3
创建任务
bash
# 基本创建
uv run scripts/create_task.py --project-id 'xxx' --title '完成需求文档'

# 完整参数创建
uv run scripts/create_task.py \
  --project-id 'xxx' \
  --title '实现登录模块' \
  --executor-id 'uid' \
  --due-date '2026-04-01' \
  --priority 1 \
  --note '参考设计稿'
更新任务
bash
# 更新标题和优先级(多字段并行执行)
uv run scripts/update_task.py --task-id 'xxx' --title '新标题' --priority 0

# 更新截止日期和执行人
uv run scripts/update_task.py --task-id 'xxx' --due-date '2026-04-01' --executor-id 'uid'

# 更新任务状态(先查询状态 ID)
uv run scripts/get_task_statuses.py <taskId>
uv run scripts/update_task.py --task-id 'xxx' --taskflowstatus-id '状态ID'

# 单独更新优先级
uv run scripts/update_task_priority.py --task-id 'xxx' --priority 0
查询项目
bash
# 我参与的项目
uv run scripts/query_projects.py --tql "involveMembers = me()"

# 按名称搜索
uv run scripts/query_projects.py --tql "nameText ~ '产品开发'"

# 查询项目详情
uv run scripts/query_project_detail.py <projectId>

# 获取 organizationId(用于查询优先级配置)
uv run scripts/query_project_detail.py <projectId> --extra-fields organizationId
查询成员和当前用户
bash
# 按姓名搜索成员
uv run scripts/query_members.py --keyword '张三'

# 批量按用户ID查询成员(推荐用于ID转换)
uv run scripts/query_members.py --user-ids "id1,id2,id3"

# 获取当前登录用户信息(userId、name、email 等)
uv run scripts/get_current_user.py
创建评论(含 @提及)
bash
# 创建评论并 @张三(--mention 接受姓名,脚本自动查询 userId)
uv run scripts/create_comment.py \
  --task-id 'xxx' \
  --content '请张三确认一下' \
  --mention '张三'

# @多人(逗号分隔)
uv run scripts/create_comment.py \
  --task-id 'xxx' \
  --content '请张三和李四评审' \
  --mention '张三,李四'

# 已知 userId 时可直接用 --mention-id
uv run scripts/create_comment.py \
  --task-id 'xxx' \
  --content '已更新' \
  --mention-id '61cad8021deea2ac89a4cbf3'
文件上传
bash
# 第一步:上传文件,获取 fileToken
uv run scripts/upload_file.py \
  --file-path '/path/to/doc.pdf' \
  --scope 'task:<taskId>' \
  --category attachment

# 第二步:将 fileToken 附加到评论
uv run scripts/create_comment.py \
  --task-id 'xxx' \
  --content '附件已上传,请查收' \
  --file-tokens 'token1'

分页查询

query_tasks.py 和 query_projects.py 均支持分页:

参数说明
--page-size <N>每页记录数(默认由 API 决定)
--page-token <T>传入上次返回的 nextPageToken 获取下一页
bash
# 第一页
uv run scripts/query_tasks.py --tql "executorId = me()" --page-size 50

# 下一页(使用上次输出中的 nextPageToken)
uv run scripts/query_tasks.py --tql "executorId = me()" --page-size 50 --page-token "上次返回的TOKEN"

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 33 other files (scripts, references) in skills/dingtalk-teambition-project of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • README.md
  • _meta.json
  • package.json
  • pyproject.toml
  • references/error-handling.md
  • references/project-ops.md
  • references/project-tql.md
  • references/task-ops.md
  • references/tql.md
  • scripts/__init__.py
  • scripts/archive_task.py
  • scripts/call_api.py
  • scripts/create_comment.py
  • scripts/create_task.py
  • scripts/create_trace.py
  • scripts/get_current_user.py
  • scripts/get_custom_fields.py
  • scripts/get_priority_list.py
  • … and 15 more

Open the folder on GitHubat commit e5199b5

Compare with similar skills

Dingtalk Teambition next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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Contributor-First PR MergeHKUDS/OpenHarness16k1 repos~847Automated safety check: PassMIT
Finishing A Development Branchfarm-fe/farm5.6k34 repos~1.8kAutomated safety check: PassMIT

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Works with

Categories

Questions about Dingtalk Teambition

What does Dingtalk Teambition do?

A skill your agent uses for anything related to Teambition tasks and projects. Dingtalk Teambition is an agent skill from LeoYeAI/openclaw-master-skills. Use for anything related to Teambition tasks and projects.

When should I use Dingtalk Teambition?

Dingtalk Teambition fits situations like: anything related to Teambition tasks and projects; : checking my todos; what tasks are due today; update task status.

How do I install Dingtalk Teambition in Claude Code?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a claude-code`. Or copy the skill folder (skills/dingtalk-teambition-project in LeoYeAI/openclaw-master-skills) into .claude/skills/dingtalk-teambition in your project. Claude Code loads it when a task matches its description.

How do I install Dingtalk Teambition in Codex?

Run `npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a codex`. Or copy the skill folder (skills/dingtalk-teambition-project in LeoYeAI/openclaw-master-skills) into .agents/skills/dingtalk-teambition in your project. Codex loads it when a task matches its description.

Can I use Dingtalk Teambition in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dingtalk-teambition, .gemini/skills/dingtalk-teambition, .github/skills/dingtalk-teambition and .opencode/skills/dingtalk-teambition in your project.

What does Dingtalk Teambition need to run?

Going by SKILL.md and its folder, Dingtalk Teambition needs Python for the scripts in its folder, the command-line tools its instructions call (uv) and credentials named TEAMBITION_USER_TOKEN. Our summary lists: Python 3; A credential in TEAMBITION_USER_TOKEN.

Does Dingtalk Teambition access the network?

SKILL.md names 3 domains. In commands or code: teambition.com and xxx.com; the agent is likely to contact these when it follows the instructions. As links in the text: open.teambition.com. This is read from the text; nothing was executed.

Is Dingtalk Teambition safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Dingtalk Teambition use?

Dingtalk Teambition is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dingtalk Teambition use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.

What are the alternatives to Dingtalk Teambition?

Skills that share tags, products or a category with Dingtalk Teambition: Finishing a Development Branch (obra/superpowers, 297k stars), Code Review Checklist (shareAI-lab/learn-claude-code, 78k stars), Code Design Rationale Investigator (cursor/plugins, 11k stars) and Contributor-First PR Merge (HKUDS/OpenHarness, 16k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dingtalk Teambition?

LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.

Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.