Cc Sdd New Agent
gotalab/cc-sdd
Add or extend coding-agent support in cc-sdd by executing the SOP in docs/cc-sdd/sop-new-agent.md end-to-end.
指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 qwenpaw-data 命令完成数据任务、选择 run 或 plan/execute、传入 --datasource-id、处理长任务输出或排查 CLI 失败的场景。
Install Qwenpaw Data CLI
$ npx skills add agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data qwenpaw-data-cli --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/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/qwenpaw-data-cli .claude/skills/qwenpaw-data-cli && 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 "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .claude/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cliType 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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data qwenpaw-data-cli --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/qwenpaw-data-cli .agents/skills/qwenpaw-data-cli && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .agents/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data qwenpaw-data-cli --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/qwenpaw-data-cli .cursor/skills/qwenpaw-data-cli && 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 "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .cursor/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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/agentscope-ai/QwenPaw-Data.git --path skills/qwenpaw-data-cli--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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data qwenpaw-data-cli --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/qwenpaw-data-cli .gemini/skills/qwenpaw-data-cli && 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 "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .gemini/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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 agentscope-ai/QwenPaw-Data qwenpaw-data-cliInstalls 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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/qwenpaw-data-cli .github/skills/qwenpaw-data-cli && 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 "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .github/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data qwenpaw-data-cli --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/agentscope-ai/QwenPaw-Data.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/qwenpaw-data-cli .opencode/skills/qwenpaw-data-cli && 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 "qwenpaw-data-cli" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/skills/qwenpaw-data-cli into .opencode/skills/qwenpaw-data-cli/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "qwenpaw-data-cli", 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.
Facts
- Skill name
qwenpaw-data-cli- GitHub stars
- 124
- Token cost
- ~961 tokens
- SKILL.md length
- 228 words
- Files
- 1
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 qwenpaw-data 命令完成数据任务、选择 run 或 plan/execute、传入 --datasource-id、处理长任务输出或排查 CLI 失败的场景。
- Works in 5 steps: 运行 qwenpaw-data --help，确认命令存在且公开子命令为… → CLI 会自动加载项目根目录 .env 或… → 使用 QWENPAW_DATA_CM_BASE_URL 指定 Data… → …
- Tasks that involve Operations and SOPs
- SKILL.md covers 执行前检查, 选择命令, 选择输出模式 and 验收结果, plus 2 more sections
- Needs OPENAI_API_KEY
What it does
Qwenpaw Data CLI is an agent skill from agentscope-ai/QwenPaw-Data. 指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 qwenpaw-data 命令完成数据任务、选择 run 或 plan/execute、传入 --datasource-id、处理长任务输出或排查 CLI 失败的场景。
Its SKILL.md is about 960 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Business, Finance & HR, covering Operations and SOPs. The repository describes itself as: Agentic enterprise data analytics: governed facts (DataBridge), reusable methodology (Skill-Hub), and controllable execution (Host). The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Operations and SOPs
Example prompts
- “/qwenpaw-data-cli”
Requirements
- A credential in OPENAI_API_KEY
Workflow steps
5 steps, taken from the first numbered list in SKILL.md.
- 运行 qwenpaw-data --help，确认命令存在且公开子命令为 plan、execute、run、chat 和 datasource。若命令不可用，报告需要先运行项目的 scripts/init_local.sh；不要搜索或直接调用…
- CLI 会自动加载项目根目录 .env 或 QWENPAW_DATA_ENV_FILE 指定的文件。不要读取、打印或手动 source dotenv 文件。模型命令会优先使用 QWENPAW_DATA_MODEL_*，未配置时回退到…
- 使用 QWENPAW_DATA_CM_BASE_URL 指定 Data Bridge 地址；未配置时默认使用 http://127.0.0.1:8765。
- 需要访问数据源时，先运行
- 假定模型凭据和 MCP 配置已由运行环境提供。不要写入凭据或自行创建、覆盖 MCP 配置。
What it can do on your machine
Read from SKILL.md and the folder at commit e0bae36. 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
No scripts in the folder and no shell commands in SKILL.md (its code samples are bash).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
OPENAI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Qwenpaw Data CLI loads about 961 tokens when it runs. Until then it costs about 56 tokens; SKILL.md has 228 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.
Safety
Auto-check: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:13
2. CLI 会自动加载项目根目录 `.env` 或 `QWENPAW_DATA_ENV_FILE` 指定的文件。不要读取、打印或手动 `source` dotenv 文件。模型命令会优先使用 `QWENPAW_DATA_MODEL_*`，
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from agentscope-ai/QwenPaw-Data at commit e0bae36, republished under its Apache-2.0 licence (© agentscope-ai). 228 words, ~961 tokens.
Download SKILL.mdSave it as
.claude/skills/qwenpaw-data-cli/SKILL.md (or your agent's skills folder).- name
- qwenpaw-data-cli
- description
- 指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 `qwenpaw-data` 命令完成数据任务、选择 `run` 或 `plan`/`execute`、传入 `--datasource-id`、处理长任务输出或排查 CLI 失败的场景。
QwenPaw Data CLI
将 qwenpaw-data 作为外部任务执行入口。若当前 agent 已经运行在 QwenPaw Data 任务内部，不要递归启动另一个 qwenpaw-data 进程。
执行前检查
运行
qwenpaw-data --help，确认命令存在且公开子命令为plan、execute、run、chat和datasource。若命令不可用，报告需要先运行项目的scripts/init_local.sh；不要搜索或直接调用.venv/bin/qwenpaw-data，也不要自行安装或改写项目环境。CLI 会自动加载项目根目录
.env或QWENPAW_DATA_ENV_FILE指定的文件。不要读取、打印或手动sourcedotenv 文件。模型命令会优先使用QWENPAW_DATA_MODEL_*，未配置时回退到LLM_MODEL、OPENAI_API_KEY和OPENAI_BASE_URL。使用
QWENPAW_DATA_CM_BASE_URL指定 Data Bridge 地址；未配置时默认使用http://127.0.0.1:8765。需要访问数据源时，先运行：
bash qwenpaw-data datasource list从返回 JSON 的
items中选择精确的datasource_id。优先使用用户明确指定的 ID；名称或类型只有一个明确匹配时才自动选择；存在多个合理候选时向用户确认。不要从已掩码的凭据推断数据源。假定模型凭据和 MCP 配置已由运行环境提供。不要写入凭据或自行创建、覆盖 MCP 配置。
选择命令
直接完成普通任务
对不需要预先审阅或复用计划的一次性任务使用 run：
qwenpaw-data run --datasource-id "sales-prod" "分析最近 30 天销售额趋势"需要传递较长、包含多行或容易被 shell 错误解释的请求时，将请求保存到文件并使用 --file：
qwenpaw-data run --file request.md --datasource-id "sales-prod"位置 prompt 与 --file 互斥，不要同时传递。
审阅或复用计划
当用户要求先看计划、任务需要人工审阅，或 SOP 需要重复执行时，先生成 YAML：
qwenpaw-data plan --file request.md --datasource-id "sales-prod" --output plan.yaml确认命令成功、plan.yaml 存在且内容符合任务目标后再执行：
qwenpaw-data execute plan.yaml --datasource-id "sales-prod"在 plan 和 execute 中重复传入同一个 --datasource-id；该参数属于每次 CLI 请求的上下文，不要假定它已写入 SOP。
交互式对话
只在有人值守且终端支持标准输入时使用：
qwenpaw-data chat --datasource-id "sales-prod"不要在无人值守的自动化流程中使用 chat，因为它会持续等待输入，直至收到 exit、quit 或 EOF。
选择输出模式
run 和 execute 默认启用流式输出。保留默认模式，持续读取文本增量、工具调用和工具结果，直至进程退出：
qwenpaw-data run --file request.md --datasource-id "sales-prod"
qwenpaw-data execute plan.yaml --datasource-id "sales-prod"不要仅因短时间没有新输出就判定任务失败；使用支持长超时或会话轮询的命令执行工具，并确认进程是否仍在运行。
仅在同时满足以下条件时使用 --no-stream：
- 需要干净的最终回复以及
Execution summary； - 调用方允许任务期间没有 stdout；
- 调用方提供足够长的超时或能够轮询进程状态。
qwenpaw-data run --no-stream --file request.md --datasource-id "sales-prod"
qwenpaw-data execute plan.yaml --no-stream --datasource-id "sales-prod"plan 不支持 stream 选项。运行 plan 时预留长超时并轮询进程；不要添加 --stream 或 --no-stream。
当前流式路径在结束后不会追加 Execution summary。若任务必须严格检查节点状态和产物列表，应在执行前选择 --no-stream，不要为获取汇总而重复执行已经完成的任务。
验收结果
始终等待 CLI 进程结束并检查退出码：
0：CLI 正常结束；仍需检查任务内容是否完整。1：运行时异常；读取 stderr 并按错误类型排查。2：命令或参数无效；使用对应子命令的--help修正调用。130：任务被中断；不要当作成功交付。
流式模式下，检查最终回复、工具结果和任何显式失败信息。由于该模式没有 execution summary，不能仅凭退出码 0 声称所有 DAG 节点成功；需要严格节点级验收时应预先选择非流式模式。
非流式模式下，额外检查 Execution summary：
- 确认存在
graph_id。 - 确认
completed: true。 - 逐一检查节点状态。只有全部节点为
done才视为完整成功；任何failed或abandoned都应标记为部分失败，即使completed: true。 - 检查
artifacts中的路径，并在可访问时确认文件存在且可读。引用 CLI 返回的实际路径，不要虚构产物。
向用户交付时，说明使用的数据源、完成状态、失败或跳过的节点、核心结论和产物路径。
排查失败
- 参数错误：运行
qwenpaw-data <subcommand> --help，根据公开参数修正；不要猜测参数名。 - 模型未配置：报告错误中列出的缺少变量名称，不要读取 dotenv 文件，也不要输出、记录或构造 API Key。
- Data Bridge 不可用：检查
QWENPAW_DATA_CM_BASE_URL指向的服务是否可达，再重试qwenpaw-data datasource list。 - 数据源不存在或不明确：重新读取
datasource list，使用精确 ID；多个候选无法消歧时请求用户选择。 - MCP 不可用：说明运行环境需要预配置 MCP。公开 CLI 不提供 MCP 管理命令，不要调用
qwenpaw-data mcp或自行覆盖配置文件。 - 节点执行失败：保留已有回复和产物，说明失败节点及影响。修正明确的暂时性问题后再重试，不要无条件重复整个任务。
禁止事项
- 不要调用不存在的
qwenpaw-data serve、qwenpaw-data mcp或qwenpaw-data data-source。 - 不要绕过公开命令去搜索或调用
.venv/bin/qwenpaw-data。 - 不要向
datasource list传递不存在的--base-url；通过QWENPAW_DATA_CM_BASE_URL配置地址。 - 不要打印模型密钥、数据库密码、AccessKey 或 STS Token。
- 不要为了获得 execution summary 重复执行一个已经通过流式模式完成的有副作用任务。
© agentscope-ai, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/qwenpaw-data-cli of agentscope-ai/QwenPaw-Data.
Open the folder on GitHubat commit e0bae36
Compare with similar skills
Qwenpaw Data CLI 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 |
|---|---|---|---|---|---|---|
| Qwenpaw Data CLI this skillagentscope-ai/QwenPaw-Data | 124 | — | ~961 | Automated safety check: Notes | Apache-2.0 | |
| Cc Sdd New Agentgotalab/cc-sdd | 3.7k | — | ~1.1k | Automated safety check: Pass | MIT | |
| DBS Business Toolkit Entrydontbesilent2025/dbskill | 11k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Agent Sop Authorstrands-agents/agent-sop | 1.2k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | |
| Diffusion Narrative Denouncingcanwhite/Krebs | 1k | — | ~831 | Automated safety check: Pass | MIT | |
| Polanyi Perspective0xenzyme/polanyi-skill | 137 | — | ~1.3k | Automated safety check: Pass | MIT |
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Fetch Data
agentscope-ai/QwenPaw-Data
取数 / 查数据 / 拉数据 / 跑 SQL。把自然语言取数需求转为 SQL，经数据湖仓执行后返回查询结果供下游分析。任何需要业务数据的任务在工作区缺少对应文件时都必须先调用此技能——覆盖 BI 业务分析、留存 / 转化 / 同期群分析、数据探索 EDA、统计建模、定量计算、元数据查询、数据查询。命中任一即触发：(1) 直接索要指标或记录，如「DAU 多少」「上月销售额」「3…
Bi Adaptive Threshold
agentscope-ai/QwenPaw-Data
通过量化历史数据的自然波动幅度，自适应计算判定阈值。当需要从数据本身确定阈值（如波动阈值、影响度阈值等）、而非使用固定值时调用。仅适用于日/周粒度阈值确定。
Bi Anomaly Detection
agentscope-ai/QwenPaw-Data
基于阈值检测时间序列中的显著异常波动点。当需要找出指标异常波动日期、识别数据异动时调用. An agent skill from agentscope-ai/QwenPaw-Data.
Bi Attribution Analysis
agentscope-ai/QwenPaw-Data
计算各维度（组）值对指标变动的贡献度，支持可加型量值指标和加权平均型/率值指标。当需要计算贡献度、解释指标"为什么涨/跌"时调用。
Bi Causal Attribution
agentscope-ai/QwenPaw-Data
从运营周报、活动文档、对话输入或文档工具 API 中提取业务事件，与指标异常时间窗口对齐，生成有证据支撑的因果归因假设并排序。当已知指标存在异常波动、需要从外部文档证据中解释"为什么"时调用。
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Questions about Qwenpaw Data CLI
What does Qwenpaw Data CLI do?
指导外部自动化 agent 使用 QwenPaw Data CLI 发现 Data Bridge 数据源、通过自然语言规划与执行数据分析任务、复用 SOP YAML，并根据流式输出、执行摘要和错误信息验收结果。用于需要调用本地 qwenpaw-data 命令完成数据任务、选择 run 或 plan/execute、传入 --datasource-id、处理长任务输出或排查 CLI 失败的场景。. Qwenpaw Data CLI is an agent skill from agentscope-ai/QwenPaw-Data.
When should I use Qwenpaw Data CLI?
Qwenpaw Data CLI fits situations like: tasks that involve Operations and SOPs.
How do I install Qwenpaw Data CLI in Claude Code?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a claude-code`. Or copy the skill folder (skills/qwenpaw-data-cli in agentscope-ai/QwenPaw-Data) into .claude/skills/qwenpaw-data-cli in your project. Claude Code loads it when a task matches its description.
How do I install Qwenpaw Data CLI in Codex?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a codex`. Or copy the skill folder (skills/qwenpaw-data-cli in agentscope-ai/QwenPaw-Data) into .agents/skills/qwenpaw-data-cli in your project. Codex loads it when a task matches its description.
Can I use Qwenpaw Data CLI 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 agentscope-ai/QwenPaw-Data --skill qwenpaw-data-cli -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/qwenpaw-data-cli, .gemini/skills/qwenpaw-data-cli, .github/skills/qwenpaw-data-cli and .opencode/skills/qwenpaw-data-cli in your project.
What does Qwenpaw Data CLI need to run?
Going by SKILL.md and its folder, Qwenpaw Data CLI needs credentials named OPENAI_API_KEY. Our summary lists: A credential in OPENAI_API_KEY.
Does Qwenpaw Data CLI access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Qwenpaw Data CLI safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Qwenpaw Data CLI use?
Qwenpaw Data CLI is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Qwenpaw Data CLI use?
About 961 tokens (SKILL.md is roughly 3.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Qwenpaw Data CLI?
Skills that share tags, products or a category with Qwenpaw Data CLI: Cc Sdd New Agent (gotalab/cc-sdd, 3.7k stars), DBS Business Toolkit Entry (dontbesilent2025/dbskill, 11k stars), Agent Sop Author (strands-agents/agent-sop, 1.2k stars) and Diffusion Narrative Denouncing (canwhite/Krebs, 1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Qwenpaw Data CLI?
agentscope-ai (a GitHub organization) maintains it in agentscope-ai/QwenPaw-Data, which has 124 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on October 5, 2026.
Source: agentscope-ai/QwenPaw-Data on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.