Observe Metrics
ruvnet/ruflo
Aggregate and display system metrics with anomaly detection for a time period
获取并计算指标的基础观测数据，包括时间周期确定、指标聚合、衍生指标计算和维度交叉展示表构建。当需要对指标进行基础数据观测、获取当期值与变动幅度时调用。
Apache-2.0Auto-check passed
Install Bi Metric Observation
$ npx skills add agentscope-ai/QwenPaw-Data --skill bi-metric-observation -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-metric-observation --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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .claude/skills/bi-metric-observation && 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 "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .claude/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observationType 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 bi-metric-observation -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-metric-observation --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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .agents/skills/bi-metric-observation && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .agents/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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 bi-metric-observation -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-metric-observation --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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .cursor/skills/bi-metric-observation && 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 "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .cursor/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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 packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation--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 bi-metric-observation -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install agentscope-ai/QwenPaw-Data bi-metric-observation --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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .gemini/skills/bi-metric-observation && 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 "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .gemini/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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 bi-metric-observationInstalls 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 bi-metric-observation -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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .github/skills/bi-metric-observation && 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 "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .github/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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 bi-metric-observation -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 bi-metric-observation --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/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation .opencode/skills/bi-metric-observation && 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 "bi-metric-observation" agent skill from https://github.com/agentscope-ai/QwenPaw-Data/tree/main/packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation into .opencode/skills/bi-metric-observation/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "bi-metric-observation", 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
bi-metric-observation- GitHub stars
- 127
- Token cost
- ~847 tokens
- SKILL.md length
- 139 words
- Files
- 1
- Skills in repo
- 29
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
获取并计算指标的基础观测数据，包括时间周期确定、指标聚合、衍生指标计算和维度交叉展示表构建。当需要对指标进行基础数据观测、获取当期值与变动幅度时调用。
- SKILL.md covers 前置检查 and 执行步骤
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Bi Metric Observation is an agent skill from agentscope-ai/QwenPaw-Data. 获取并计算指标的基础观测数据，包括时间周期确定、指标聚合、衍生指标计算和维度交叉展示表构建。当需要对指标进行基础数据观测、获取当期值与变动幅度时调用。
Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
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.
Example prompts
- “/bi-metric-observation”
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.
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 no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Bi Metric Observation loads about 847 tokens when it runs. Until then it costs about 24 tokens; SKILL.md has 139 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 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); 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). 139 words, ~847 tokens.
Download SKILL.mdSave it as
.claude/skills/bi-metric-observation/SKILL.md (or your agent's skills folder).- name
- bi-metric-observation
- description
- 获取并计算指标的基础观测数据，包括时间周期确定、指标聚合、衍生指标计算和维度交叉展示表构建。当需要对指标进行基础数据观测、获取当期值与变动幅度时调用。
bi-metric-observation
获取指标的原始数据并完成基础计算，构建指标的当期值、变动幅度和维度交叉展示表，为后续分析提供数据基础。常见场景：
- 指标分析：在分析流程中，对指标进行基础数据获取和计算
- 数据概览：快速了解指标当前水平与变动趋势
前置检查
开始前确认以下信息已明确：
- 分析条目明确，清楚本次要观测哪些指标
- 指标与角色已确定，知道每个指标是北极星、展示还是分布角色
- 关联维度已确定，知道北极星指标的归因拆解维度、展示指标的展示拆解维度
- 数据获取能力可用，有可以获取数据的工具或 API
若以上信息不完整，需先回到规划阶段补充，或向用户确认后再开始。
执行步骤
1：数据准备
根据分析目标获取指标的原始数据。数据文件至少包含以下列：
| 列 | 说明 | 示例 |
|---|---|---|
| 日期列 | 时间标识 | 日期 |
| 指标列 | 各指标值，每个指标一列 | 访问用户数 |
| 维度列 | 各维度值，每个维度一列 | 端类型 |
若上游步骤已产出可用数据文件则直接使用，否则自行取数。
2：确定分析时间周期
根据分析目标选择合适的分析时间区间：
| 分析目标 | 时间区间 |
|---|---|
| 日数据波动 | 当日 vs 上日 |
| 日数据波动（消除周末效应） | 当日 vs 上周同日 |
| 周数据波动 | 本周 vs 上周 |
| 月数据波动 | 本月 vs 上月 |
| 年度趋势 | 当期 vs 上年同期 |
| 特定日期分析 | 指定日期前后日/周 |
确定时间区间后，获取该区间内所有指标的原始数据。
3：确定指标计算方式
根据指标类型和时间周期，判断该指标在对应周期下的聚合方式。通用规则：
- 累加型指标（如收入、订单量、新增用户数）：使用周期内聚合值（求和）
- 水平型指标（如日活跃用户数 DAU、活跃率、转化率）：使用周期内均值
- 用户规模型指标（如月活跃用户数 MAU、累计用户数）：使用周期末快照值（去重值或最后一天值）
4：计算衍生指标
根据分析场景计算合适的衍生指标，不需要全部计算：
| 衍生指标 | 适用场景 |
|---|---|
| 日环比 | 日数据，对比日数据波动 |
| 周同比 | 日数据，对比日数据波动，消除周末效应 |
| 周环比 | 周数据，对比周波动 |
| 月环比 | 月数据，对比月波动 |
| 年同比（日） | 日数据，长期业务且有年度周期性波动时关注 |
| 年同比（月） | 月数据，需要年度比较的业务（如 B 端收入） |
| 年环比 | 年/财年数据，对比财年累计值，适用可累加指标（如年收入） |
| 分布占比 | 量值指标在各维度下的分布拆解，展示核心观测指标时需加上分布占比 |
注意：计算衍生指标时，根据指标类型选择正确的变动表达方式，避免产生"百分比的百分比"等歧义：
| 指标类型 | 识别特征 | 变动表达 | 示例 |
|---|---|---|---|
| 量值指标 | 绝对数值，可直接累加 | 百分比增幅 | DAU 增长 10% |
| 率值指标 | 有分子/分母，数值为百分比 | 绝对值增幅 (pt) | 留存率从 40% 到 42%，+2pt |
| 加工指标 | 由其他指标计算得到，数量级小按率值，否则按量值 | 视业务场景而定 | 人均对话次数、客单价 |
5：构建维度交叉展示表
按展示维度聚合指标，构建"维度值 × 指标"交叉表。
构建规则：
- 每个展示维度构建一张交叉表
- 行：该维度的各维度值（含"全部"汇总行）
- 列：关联该维度的所有指标，每个指标包含当期值和衍生指标；分布角色的指标额外附加占比列
示例：展示维度为"端类型"，关联指标为访问用户数（分布）、对话渗透率（展示）、人均对话次数（展示），衍生指标为月环比：
| 端 | 访问用户数 | 月环比 | 访问用户数占比 | 对话渗透率 | 月环比 | 人均对话次数 | 月环比 |
|---|---|---|---|---|---|---|---|
| 全部 | ... | ... | 100% | ... | ... | ... | ... |
| web | ... | ... | ... | ... | ... | ... | ... |
6：汇总观测结果
将基础观测结果汇总输出，包含：
| 输出项 | 说明 |
|---|---|
| 分析时间周期 | 确定的当期和往期区间 |
| 指标当期值 | 各指标的当期聚合值 |
| 衍生指标 | 各指标的变动幅度（环比/同比/占比等） |
| 维度交叉展示表 | 各展示维度的"维度值 × 指标"交叉表 |
© 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 packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation of agentscope-ai/QwenPaw-Data.
Open the folder on GitHubat commit e0bae36
Compare with similar skills
Bi Metric Observation 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 |
|---|---|---|---|---|---|---|
| Bi Metric Observation this skillagentscope-ai/QwenPaw-Data | 127 | — | ~847 | Automated safety check: Pass | Apache-2.0 | |
| Observe Metricsruvnet/ruflo | 74k | — | ~592 | Automated safety check: Notes | MIT | |
| Python Observabilitywshobson/agents | 40k | — | ~1.8k | Automated safety check: Pass | MIT | |
| Observability Designeralirezarezvani/claude-skills | 28k | — | ~3.5k | Automated safety check: Pass | MIT | |
| Langsmith ObservabilityOrchestra-Research/AI-Research-SKILLs | 13k | 2 repos | ~2.4k | Automated safety check: Pass | MIT | |
| ObservabilityBuilderIO/agent-native | 7.1k | — | ~7.3k | Automated safety check: Pass | None |
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Questions about Bi Metric Observation
What does Bi Metric Observation do?
获取并计算指标的基础观测数据，包括时间周期确定、指标聚合、衍生指标计算和维度交叉展示表构建。当需要对指标进行基础数据观测、获取当期值与变动幅度时调用。. Bi Metric Observation is an agent skill from agentscope-ai/QwenPaw-Data.
How do I install Bi Metric Observation in Claude Code?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-metric-observation -a claude-code`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation in agentscope-ai/QwenPaw-Data) into .claude/skills/bi-metric-observation in your project. Claude Code loads it when a task matches its description.
How do I install Bi Metric Observation in Codex?
Run `npx skills add agentscope-ai/QwenPaw-Data --skill bi-metric-observation -a codex`. Or copy the skill folder (packages/qwenpaw-data-skills/skills/atomic/bi-metric-observation in agentscope-ai/QwenPaw-Data) into .agents/skills/bi-metric-observation in your project. Codex loads it when a task matches its description.
Can I use Bi Metric Observation 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 bi-metric-observation -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bi-metric-observation, .gemini/skills/bi-metric-observation, .github/skills/bi-metric-observation and .opencode/skills/bi-metric-observation in your project.
What does Bi Metric Observation need to run?
SKILL.md names no scripts, command-line tools or credentials: Bi Metric Observation is instructions for the agent only.
Does Bi Metric Observation 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 Bi Metric Observation 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. Review the folder before installing.
What licence does Bi Metric Observation use?
Bi Metric Observation 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 Bi Metric Observation use?
About 847 tokens (SKILL.md is roughly 3.4k 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 Bi Metric Observation?
Skills that share tags, products or a category with Bi Metric Observation: Observe Metrics (ruvnet/ruflo, 74k stars), Python Observability (wshobson/agents, 40k stars), Observability Designer (alirezarezvani/claude-skills, 28k stars) and Langsmith Observability (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Bi Metric Observation?
agentscope-ai (a GitHub organization) maintains it in agentscope-ai/QwenPaw-Data, which has 127 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.