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benchmark-qed-autoe Skill

AI Agent SkillPythonOpen source

Evaluate RAG system outputs using benchmark-qed scoring methods. Use when: running pairwise comparisons, reference-based scoring, assertion-based evaluation (flat or hierarchical), retrieval metrics, or statistical significance tests on RAG outputs. Also use when the user wants to score, compare, or evaluate RAG method Published by microsoft in benchmark-qed.

Decision snapshot

Is this a fit?

Best for

Testing, Includes SKILL.md, Reusable instructions

Works with

Compatibility not yet detected.

Access

API key required authentication, Credentials required

Setup

Copy skill directory

Project health

2 months ago · MIT license

Considerations

Access note: API key required.

What is benchmark-qed-autoe Skill?

Evaluate RAG system outputs using benchmark-qed scoring methods. Use when: running pairwise comparisons, reference-based scoring, assertion-based evaluation (flat or hierarchical), retrieval metrics, or statistical significance tests on RAG outputs. Also use when the user wants to score, compare, or evaluate RAG method Published by microsoft in benchmark-qed. 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
49/100

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
  • Testing use cases

Declared skill metadata

  • Source file: .apm/skills/benchmark-qed-autoe/SKILL.md

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
  • API key required

Requirements and access

API key required

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.

Credentials requiredAPI key required authentication

When to use benchmark-qed-autoe Skill

  • Use it for testing.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/benchmark-qed
  • Skill file: .apm/skills/benchmark-qed-autoe/SKILL.md

What it does

Evaluate RAG system outputs using benchmark-qed scoring methods. Use when: running pairwise comparisons, reference-based scoring, assertion-based evaluation (flat or hierarchical), retrieval metrics, or statistical significance tests on RAG outputs. Also use when the user wants to score, compare, or evaluate RAG method

Skill instructions

Benchmark-QED Evaluation (autoe) Evaluate and compare RAG system outputs using LLM-judged scoring, assertion-based evaluation, and retrieval metrics — all with built-in statistical significance testing. Prerequisites - Generated questions/assertions from the autoq pipeline (or your own) - RAG method answer files (JSON, one per method per question set) - A valid settings.yaml for the evaluation type - A configured workspace with valid settings.yaml (use the benchmark-qed-setup skill to initialize and configure) - LLM API key configured Run all commands with: bash uvx --from "git+https://github.com/microsoft/benchmark-qed" benchmark-qed <command Evaluation Methods Overview | Method | Command | Best for | |--------|---------|----------| | Pairwise comparison | autoe pairwise-scores | Comparing two RAG methods head-to-head | | Reference scoring | autoe reference-scores | Scoring against gold-standard answers | | Assertion scoring | autoe assertion-scores | Evaluating with ground-truth asse

Verified compatibility and discovery

Frequently asked questions

What is benchmark-qed-autoe?

benchmark-qed-autoe is a open-source AI agent skill with Copy skill directory. Evaluate RAG system outputs using benchmark-qed scoring methods. Use when: running pairwise comparisons, reference-based scoring, assertion-based evaluation (flat or hierarchical), retrieval metrics.

Who is benchmark-qed-autoe best for?

benchmark-qed-autoe is best for reusing agent instructions, scripts, and references, testing workflows.

How do I install benchmark-qed-autoe?

Install or run benchmark-qed-autoe using Copy skill directory. Check benchmark-qed-autoe for the latest setup command.

Is benchmark-qed-autoe actively maintained?

benchmark-qed-autoe may need a closer maintenance check before production use.

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Stars
91
Forks
18
Last commit
2 months ago
Last verified
Aug 30, 2026
Metadata fetched
Aug 30, 2026
Repository age
1 year
License
MIT

Project health auto-fetched from the source repository.

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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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