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context-intelligence-evaluation-methodology Skill

AI Agent SkillPythonOpen source

Use when deciding how to measure a context-intelligence tool signal. Covers 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.

Decision snapshot

Is this a fit?

Best for

Testing, Data analysis, Design and media, Includes SKILL.md

Works with

Compatibility not yet detected.

Access

Filesystem access

Setup

Copy skill directory

Project health

2 months ago · MIT license

Considerations

Access note: Local files.

What is context-intelligence-evaluation-methodology Skill?

Use when deciding how to measure a context-intelligence tool signal. Covers 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.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
11/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement. See how SkillIndex evaluates profiles.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Testing
  • Data analysis
  • Design and media
  • Testing use cases
  • Data analysis use cases

Declared skill metadata

  • Declared license: MIT
  • Source file: skills/context-intelligence-evaluation-methodology/SKILL.md

Allowed tools declared by source

read_fileglobgrepdelegateload_skilltodo

These fields retain source and confidence evidence from the indexed SKILL.md.

Compatibility and setup

Copy skill directory
  • Install or run with Copy skill directory
  • Local files

Requirements and access

Local files

Security and permissions

Review permissions before connecting any MCP server to an agent. Pay special attention to whether it can read local files, write data, call external services, or perform destructive actions.

Filesystem access

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

PythonCopy skill directory

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. Covers 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

Verified compatibility and discovery

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.

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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2
Forks
3
Last commit
2 months ago
Last verified
Sep 3, 2026
Metadata fetched
Sep 3, 2026
Repository age
6 months
License
MIT

Project health auto-fetched from the source repository.

Maintain this resource?

Review this source-backed profile, send a correction with evidence, or link to it from your documentation. Claims verify your relationship to the project; profile facts still require source evidence and editorial review.

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