context-intelligence-evaluation-methodology Skill
Use when deciding how to measure a context-intelligence tool signal — metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor measurement, A/B and statistical-N discipline, and test-data fidelity. Published by microsoft in amplifier-bundle-context-intelligence.
What is context-intelligence-evaluation-methodology Skill?
Use when deciding how to measure a context-intelligence tool signal — metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor measurement, A/B and statistical-N discipline, and test-data fidelity. Published by microsoft in amplifier-bundle-context-intelligence. 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
- Testing
- Data analysis
- Design and media
- Testing use cases
- Data analysis use cases
Technical details
- Install or run with Copy skill directory
When to use context-intelligence-evaluation-methodology Skill
- Use it for testing.
- Use it for data analysis.
- Use it for design and media.
Built with
Editorial notes
Source
- Creator: microsoft
- Repository: microsoft/amplifier-bundle-context-intelligence
- Skill file: skills/context-intelligence-evaluation-methodology/SKILL.md
What it does
Use when deciding how to measure a context-intelligence tool signal — metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor measurement, A/B and statistical-N discipline, and test-data fidelity.
Skill instructions
Context Intelligence Evaluation Methodology Mode-only skill for how to measure. It complements — and never restates — context-intelligence-eval-design (which owns scenario mechanics and the two-layer structural/behavioral structure) and digital-twin-universe (which owns the DTU machinery). Scope In scope - Metric design. Choose metrics across three axes: quality (did it detect what the user means?), efficiency (token/tool cost to detect), efficacy (does detection drive the right outcome?). - Measure the precursor, not only the failure. Prefer leading indicators (e.g. bounded vs climbing context growth) over lagging ones (e.g. a final timeout). The precursor is testable in a short window; the full failure often is not. - A/B + statistical-N discipline. A single green run is not proof of a behavioral change. Compare a control arm against a treatment arm; require N independent trials and report the pass rate, not a single anecdote. - Test data fidelity. Validate on real sessions where ava
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Frequently asked questions
What is context-intelligence-evaluation-methodology?
context-intelligence-evaluation-methodology is a open-source AI agent skill with Copy skill directory. Use when deciding how to measure a context-intelligence tool signal — metric design across quality/efficiency/efficacy axes, artifact-metric avoidance via precursor.
Who is context-intelligence-evaluation-methodology best for?
context-intelligence-evaluation-methodology is best for reusing agent instructions, scripts, and references, testing workflows, data analysis workflows, design and media workflows.
How do I install context-intelligence-evaluation-methodology?
Install or run context-intelligence-evaluation-methodology using Copy skill directory. Check context-intelligence-evaluation-methodology for the latest setup command.
Is context-intelligence-evaluation-methodology actively maintained?
context-intelligence-evaluation-methodology may need a closer maintenance check before production use.
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