metric-diagnostics Skill
Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy. Published by openai in role-specific-plugins.
What is metric-diagnostics Skill?
Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy. Published by openai in role-specific-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.
Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.
Key capabilities
- Includes SKILL.md support
- Reusable instructions support
- Data analysis
- Research
- Data analysis use cases
- Research use cases
Technical details
- Install or run with Copy skill directory
When to use metric-diagnostics Skill
- Use it for data analysis.
- Use it for research.
Built with
Editorial notes
Source
- Creator: openai
- Repository: openai/role-specific-plugins
- Skill file: plugins/data-analytics/skills/metric-diagnostics/SKILL.md
What it does
Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy.
Skill instructions
Related Skills Use $gather-business-context when business context is needed to understand the metric, analysis period, ownership, or plausible explanations. Use $product-business-analysis when the task asks for a recommendation or tradeoff decision after diagnosing the movement. Use $analyze-data-quality when dashboard trust, grain, freshness, or source disagreement could affect the metric. Metric Diagnostics Use this skill to diagnose why a metric changed or differs from expectation. Reproduce the metric, define the comparison, quantify the movement, validate likely drivers, and state what is verified, likely, unresolved, and useful to do next. Clarify with the user when a missing input would materially change the analytical frame or recommendation. Otherwise make a reasonable assumption, state it, and proceed. Skill Configuration Source Discovery And Verification Use the relevant semantic layer as a starting map, not a boundary. 1. Explore all possible sources. Search every connected
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Frequently asked questions
What is metric-diagnostics?
metric-diagnostics is a open-source AI agent skill with Copy skill directory. Diagnose why a metric changed or differs from expectation. Use when the task is to identify likely drivers of a metric movement, anomaly, gap, or discrepancy.
Who is metric-diagnostics best for?
metric-diagnostics is best for reusing agent instructions, scripts, and references, data analysis workflows, research workflows.
How do I install metric-diagnostics?
Install or run metric-diagnostics using Copy skill directory. Check metric-diagnostics for the latest setup command.
Is metric-diagnostics actively maintained?
metric-diagnostics may need a closer maintenance check before production use.
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