Finishing a Development Branch
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
A skill your agent uses for anything related to Teambition tasks and projects.
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .claude/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-projectType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/dingtalk-teambition-project .agents/skills/dingtalk-teambition && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .agents/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/dingtalk-teambition-project .cursor/skills/dingtalk-teambition && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .cursor/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/dingtalk-teambition-project--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/dingtalk-teambition-project .gemini/skills/dingtalk-teambition && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .gemini/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambitionInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/dingtalk-teambition-project .github/skills/dingtalk-teambition && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .github/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill dingtalk-teambition -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills dingtalk-teambition --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/dingtalk-teambition-project .opencode/skills/dingtalk-teambition && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "dingtalk-teambition" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/dingtalk-teambition-project into .opencode/skills/dingtalk-teambition/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "dingtalk-teambition", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
dingtalk-teambitionA 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. 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.
12 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
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.
Ships 9 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
uvFrom the folder's file list and the shell code blocks in SKILL.md.
Hosts in commands or code, which the agent is likely to contact:
teambition.comxxx.comAlso links to:
open.teambition.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TEAMBITION_USER_TOKENFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 775 words, ~3,681 tokens.
.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.✅ 适合使用本技能:
❌ 不适用场景:
git获取 User Token:Teambition 开放平台
# 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 syncme():TQL 中查询"我的"任务/项目,必须用 executorId = me(),禁止硬编码用户 ID
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:
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:2026-03-14T16:00:00.000ZID→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。
| 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 |
query_members.py,项目/迭代/任务用各自的查询脚本)# 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"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。
projectIduv run scripts/query_project_detail.py <projectId> --extra-fields organizationId 获取 organizationIduv run scripts/get_priority_list.py <organizationId> 获取企业真实优先级列表priority(数值)和 name(企业自定义名称),以此覆盖默认 label 后再展示priority 数值调用更新接口归档 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
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
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
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
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
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
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:
https://www.teambition.com/task/{taskId}https://www.teambition.com/project/{projectId}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
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:
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:
# 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"}]}]'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:
uv run scripts/upload_file_to_customfield.py \
--task-id '<taskId>' \
--file-path '/path/to/file.pdf' \
--customfield-id '<字段ID>'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:
[文件名](downloadUrl)[材料.md](https://xxx.com/...)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。
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:
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:
# 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 | 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> |
| 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
| 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
| 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
| 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
# 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# 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# 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# 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'# 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'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 |
# 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
SKILL.md and 33 other files (scripts, references) in skills/dingtalk-teambition-project of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Dingtalk Teambition this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.7k | Automated safety check: Pass | MIT | |
| Finishing a Development Branchobra/superpowers | 297k | 5 repos | ~1.9k | Automated safety check: Pass | MIT | |
| Code Review ChecklistshareAI-lab/learn-claude-code | 78k | 4 repos | ~1.1k | Automated safety check: Pass | MIT | |
| Code Design Rationale Investigatorcursor/plugins | 11k | 9 repos | ~2.6k | Automated safety check: Pass | None | |
| Contributor-First PR MergeHKUDS/OpenHarness | 16k | 1 repos | ~847 | Automated safety check: Pass | MIT | |
| Finishing A Development Branchfarm-fe/farm | 5.6k | 34 repos | ~1.8k | Automated safety check: Pass | MIT |
obra/superpowers
Walks the last step of a branch: confirm tests pass, detect the git environment, ask how to integrate, carry out your choice and clean up the worktree.
shareAI-lab/learn-claude-code
Reviews code against a five-part checklist covering security, correctness, performance, maintainability and testing, and reports findings in a fixed format.
cursor/plugins
Digs into why code is shaped the way it is by checking git history, pull requests and connected tools in parallel, then reporting a cited read on the tradeoffs.
HKUDS/OpenHarness
Merges external GitHub pull requests while keeping the original author credited, and fixes conflicts after the merge instead of rewriting the contribution.
farm-fe/farm
A skill your agent uses when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for…
TryGhost/Ghost
Moves a package from another TryGhost repository into Ghost as an internal workspace package while keeping its Git history, with checkpoints for the steps that need an administrator.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
Works with
Categories
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.
Dingtalk Teambition fits situations like: anything related to Teambition tasks and projects; : checking my todos; what tasks are due today; update task status.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.