Building Streamlit Dashboards
iusztinpaul/designing-real-world-ai-agents-workshop
Building dashboards in Streamlit. An agent skill from iusztinpaul/designing-real-world-ai-agents-workshop.
运营指标分析技能。当用户询问网络运营指标、KPI、接通率、掉线率、时延、SLA 达标率、趋势对比、环比周报月报，或报告指标异常时使用。
Install Ops Metrics Analysis
$ npx skills add zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zj-unicom-ai/UniEmployee ops-metrics-analysis --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/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .claude/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .claude/skills/ops-metrics-analysis && 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 "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .claude/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysisType 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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zj-unicom-ai/UniEmployee ops-metrics-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .agents/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .agents/skills/ops-metrics-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .agents/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zj-unicom-ai/UniEmployee ops-metrics-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .cursor/skills/ops-metrics-analysis && 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 "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .cursor/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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/zj-unicom-ai/UniEmployee.git --path backend/skills/ops-metrics-analysis--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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zj-unicom-ai/UniEmployee ops-metrics-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .gemini/skills/ops-metrics-analysis && 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 "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .gemini/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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 zj-unicom-ai/UniEmployee ops-metrics-analysisInstalls 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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .github/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .github/skills/ops-metrics-analysis && 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 "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .github/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zj-unicom-ai/UniEmployee ops-metrics-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zj-unicom-ai/UniEmployee.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/backend/skills/ops-metrics-analysis .opencode/skills/ops-metrics-analysis && 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 "ops-metrics-analysis" agent skill from https://github.com/zj-unicom-ai/UniEmployee/tree/main/backend/skills/ops-metrics-analysis into .opencode/skills/ops-metrics-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ops-metrics-analysis", 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
ops-metrics-analysis- GitHub stars
- 360
- Token cost
- ~473 tokens
- SKILL.md length
- 133 words
- Files
- 1
- Skills in repo
- 22
- Repo updated
- First seen
- Licence
- MIT
At a glance
运营指标分析技能。当用户询问网络运营指标、KPI、接通率、掉线率、时延、SLA 达标率、趋势对比、环比周报月报，或报告指标异常时使用。
- Works in 3 steps: 按时间窗聚合：各片区… → 环比：本周期 vs 上一周期各指标变化（绝对差与百分比），标注升/降/持平； → 趋势：按周聚合画趋势方向（连续上行/下行/波动），找拐点日期。
- Tasks that involve OKRs and executive reporting
- SKILL.md covers 数据集, 执行步骤（用 execute 跑 pandas，工作目录…, 注意事项 and 最终输出铁律
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Ops Metrics Analysis is an agent skill from zj-unicom-ai/UniEmployee. 运营指标分析技能。当用户询问网络运营指标、KPI、接通率、掉线率、时延、SLA 达标率、趋势对比、环比周报月报，或报告指标异常时使用。
Its SKILL.md is about 470 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 OKRs and executive reporting. The repository describes itself as: 面向企业的数字员工构建与运行平台：把专业员工的经验、流程与判断标准，固化为可随时上岗、可配置、可审批、可观测的 AI 数字员工。 The licence is MIT.
When your agent uses it
- Tasks that involve OKRs and executive reporting
Example prompts
- “/ops-metrics-analysis”
Workflow steps
3 steps, taken from the first numbered list in SKILL.md.
- 按时间窗聚合：各片区 connection_rate/drop_rate/avg_latency_ms/sla_met_rate
- 环比：本周期 vs 上一周期各指标变化（绝对差与百分比），标注升/降/持平；
- 趋势：按周聚合画趋势方向（连续上行/下行/波动），找拐点日期。
What it can do on your machine
Read from SKILL.md and the folder at commit c38a00a. 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
Ops Metrics Analysis loads about 473 tokens when it runs. Until then it costs about 22 tokens; SKILL.md has 133 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 zj-unicom-ai/UniEmployee at commit c38a00a, republished under its MIT licence (© zj-unicom-ai). 133 words, ~473 tokens.
Download SKILL.mdSave it as
.claude/skills/ops-metrics-analysis/SKILL.md (or your agent's skills folder).- name
- ops-metrics-analysis
- description
- 运营指标分析技能。当用户询问网络运营指标、KPI、接通率、掉线率、时延、SLA 达标率、趋势对比、环比周报月报，或报告指标异常时使用。
运营指标分析
你是算网运营分析专家，回答指标问题必须基于运营指标数据集跑出的真实数据， 禁止估算或凭记忆给数。所有结论用中文结构化输出。
数据集
/datasets/netops_kpi.csv：180 天日粒度运营指标，列： date / station_group（城东片区/高新区片区/老城片区）/ connection_rate（接通率 %）/ drop_rate（掉线率 %）/ avg_latency_ms（平均时延）/ alert_count（当日告警数）/ ticket_count（当日工单数）/ sla_met_rate（SLA 达标率 %）/ satisfaction（满意度 5 分制）
业务口径（判定标准，写进结论）：
- 接通率达标线 99.0%，目标 99.5%；掉线率警戒线 0.5%
- SLA 达标率目标 ≥ 95%，低于即不合格
- 满意度目标 ≥ 4.5
执行步骤（用 execute 跑 pandas，工作目录 /data）
步骤1：明确分析口径
先确认用户的分析对象与时间窗（默认最近 30 天，对比上一周期）。 用户问"整体"时按全网三个片区汇总；点名片区时只看该片区分组。
步骤2：跑数（每步跑一次确认，禁止凭一次结果推断全局）
- 按时间窗聚合：各片区 connection_rate/drop_rate/avg_latency_ms/sla_met_rate 的均值与最差值；
- 环比：本周期 vs 上一周期各指标变化（绝对差与百分比），标注升/降/持平；
- 趋势：按周聚合画趋势方向（连续上行/下行/波动），找拐点日期。
步骤3：异常定位与归因
- 逐片区筛异常日：connection_rate < 99.0 或 drop_rate > 0.5 或 sla_met_rate < 95 的日期清单；
- 异常日关联告警：读 /datasets/netops_alerts.csv（列：alert_id/time/station/ station_code/alarm_type/severity P1~P4/status/duration_min/root_cause/ handler），取异常日前后 1 天对应基站（片区内）的 P1/P2 告警， 对照告警类型与根因，判定指标异常是否由故障引起；
- 区分两类异常：突发型（单日骤降，对应 P1/P2 告警）与劣化型 （连续下滑，对应 P2 频发或负载类根因），分别给结论。
步骤4：输出报告
结构：「总体结论 → 分片区指标对比表 → 异常清单与归因 → 建议动作」：
- 总体结论一句话（达标与否、最需关注的片区）；
- 指标对比用表格（均值/环比/趋势三列），数字必须与跑数结果一致；
- 每条异常给出日期、指标、疑似根因（关联到的告警编号）、责任装维；
- 建议：突发型 → 引用故障处置流程（提示可走 fault-impact-analysis 技能）； 劣化型 → 容量/整改方向（提示可走 resource-capacity-analysis 技能）。
结尾标注数据来源：「以上来自运营指标数据集（N 行 × M 天）+ 告警流水（X 条）」。
注意事项
- 环比必须两个窗口都真实跑数，不得用目测估算
- 异常归因只能说"疑似关联"，不得断言因果（除非告警时间与指标劣化严格对应）
- 用户要报表文件时用 matplotlib 出图并用 write_file 落到 /data/ 下
- 涉及 SLA 违约赔付的表述，先走 kb_search 查现行 SLA 制度再承诺
最终输出铁律
- 必须输出完整中文报告，格式固定为： 「总体结论 → 分片区指标对比表 → 异常清单与归因 → 建议动作」。
- 指标必须包含接通率、掉线率、平均时延、SLA 达标率中的至少两项。
- 必须给出本周期与上一周期的环比方向，例如上升、下降或持平。
- 必须给出至少一个异常日期，并说明疑似关联告警或根因。
- 不要只输出"现在跑数"或把工具执行过程当作最终报告。
© zj-unicom-ai, MIT. 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 backend/skills/ops-metrics-analysis of zj-unicom-ai/UniEmployee.
Open the folder on GitHubat commit c38a00a
Compare with similar skills
Ops Metrics Analysis 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 |
|---|---|---|---|---|---|---|
| Ops Metrics Analysis this skillzj-unicom-ai/UniEmployee | 360 | — | ~473 | Automated safety check: Pass | MIT | |
| Building Streamlit Dashboardsiusztinpaul/designing-real-world-ai-agents-workshop | 512 | — | ~1.1k | Automated safety check: Pass | Apache-2.0 | |
| Kpi Dashboard Designaiskillstore/marketplace | 433 | 10 repos | ~3.5k | Automated safety check: Pass | None | |
| SVG Visualsdata-goblin/power-bi-agentic-development | 1k | — | ~4.3k | Automated safety check: Pass | GPL-3.0 | |
| Large File Kpi AnalysisMichaelYang-lyx/AIDABench | 111 | 1 repos | ~502 | Automated safety check: Pass | None | |
| Consumer Goods Tpe Dashboard Configureforcedotcom/sf-skills | 1.1k | — | ~1.5k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Ops Metrics Analysis
What does Ops Metrics Analysis do?
运营指标分析技能。当用户询问网络运营指标、KPI、接通率、掉线率、时延、SLA 达标率、趋势对比、环比周报月报，或报告指标异常时使用。. Ops Metrics Analysis is an agent skill from zj-unicom-ai/UniEmployee.
When should I use Ops Metrics Analysis?
Ops Metrics Analysis fits situations like: tasks that involve OKRs and executive reporting.
How do I install Ops Metrics Analysis in Claude Code?
Run `npx skills add zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a claude-code`. Or copy the skill folder (backend/skills/ops-metrics-analysis in zj-unicom-ai/UniEmployee) into .claude/skills/ops-metrics-analysis in your project. Claude Code loads it when a task matches its description.
How do I install Ops Metrics Analysis in Codex?
Run `npx skills add zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a codex`. Or copy the skill folder (backend/skills/ops-metrics-analysis in zj-unicom-ai/UniEmployee) into .agents/skills/ops-metrics-analysis in your project. Codex loads it when a task matches its description.
Can I use Ops Metrics Analysis 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 zj-unicom-ai/UniEmployee --skill ops-metrics-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ops-metrics-analysis, .gemini/skills/ops-metrics-analysis, .github/skills/ops-metrics-analysis and .opencode/skills/ops-metrics-analysis in your project.
What does Ops Metrics Analysis need to run?
SKILL.md names no scripts, command-line tools or credentials: Ops Metrics Analysis is instructions for the agent only.
Does Ops Metrics Analysis 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 Ops Metrics Analysis 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 Ops Metrics Analysis use?
Ops Metrics Analysis 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 Ops Metrics Analysis use?
About 473 tokens (SKILL.md is roughly 1.9k 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 Ops Metrics Analysis?
Skills that share tags, products or a category with Ops Metrics Analysis: Building Streamlit Dashboards (iusztinpaul/designing-real-world-ai-agents-workshop, 512 stars), Kpi Dashboard Design (aiskillstore/marketplace, 433 stars), SVG Visuals (data-goblin/power-bi-agentic-development, 1k stars) and Large File Kpi Analysis (MichaelYang-lyx/AIDABench, 111 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ops Metrics Analysis?
zj-unicom-ai (a GitHub organization) maintains it in zj-unicom-ai/UniEmployee, which has 360 GitHub stars. The repository holds 22 skills in this directory. The repository was last updated on October 8, 2026.
Source: zj-unicom-ai/UniEmployee on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.