Run Eval

Organization

microsoft

run-eval

Run evaluations against a Copilot Studio agent via the Power Platform Evaluation API. Works on DRAFT agents — no publish step required. Lists test sets, starts a run, polls until complete, fetches results, and proposes YAML fixes for failures. Use when the user wants to test agent changes without publishing.

Overview

Publisher	microsoft
Repository	`skills-for-copilot-studio`
Skill name	`run-eval`
Stars	478
Forks	101
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Run Eval AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/microsoft/skills-for-copilot-studio/tree/main/skills/run-eval
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/microsoft/skills-for-copilot-studio.git /tmp/skills-for-copilot-studio
mkdir -p .claude/skills
cp -r /tmp/skills-for-copilot-studio/skills/run-eval .claude/skills/run-eval

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Run Eval in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Run Eval on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Run Eval is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Run Evaluation (PPAPI)

Run evaluations against a Copilot Studio agent's draft — no publish needed.

The caller (test agent) must provide --client-id and --workspace. If you don't have the client ID, return immediately and tell the caller to run test-auth first.

All eval-api commands run in the foreground. NEVER use run_in_background.

Step 1: List test sets and let the user choose

bash
node ${CLAUDE_SKILL_DIR}/../../scripts/eval-api.bundle.js list-testsets --workspace <path> --client-id <id>

No test sets found: Tell the user to create one in Copilot Studio (Evaluate tab > New evaluation). Stop.
One test set: Tell the user which one you're using and proceed.
Multiple test sets: Show them all and ask the user to pick. Do not proceed until they answer.

Step 2: Ask about authenticated execution — MANDATORY, do not skip

You MUST ask this question and wait for the user's answer before starting the run.

Ask the user:

Does your agent use authenticated knowledge sources or connector actions (tools) that require user identity? If so, you'll need to provide a connection ID — without it, the eval runs anonymously and tools and knowledge sources will not be used.

How to obtain the connection ID:

Go to https://make.powerautomate.com

Open Connections from the side menu

Select the relevant Microsoft Copilot Studio connection

Copy the connection ID from the URL (the GUID segment after /connections/)

If your agent doesn't use authenticated knowledge or tools, you can skip this.

Do not proceed to Step 3 until the user responds.

Step 3: Start the run

bash
node ${CLAUDE_SKILL_DIR}/../../scripts/eval-api.bundle.js start-run --workspace <path> --client-id <id> --testset-id <id> --run-name "Draft eval <date>"

Add --connection-id <id> if the user provided a connection ID in Step 2.

Add --published only if the user explicitly asked for published-bot testing.

Step 4: Poll until complete

bash
node ${CLAUDE_SKILL_DIR}/../../scripts/eval-api.bundle.js get-run --workspace <path> --client-id <id> --run-id <runId>

Poll every 15-30 seconds. Report progress: "Processing: 3/10 test cases..."

Stop when state is Completed, Failed, Abandoned, or Cancelled.

Step 5: Fetch and analyze results

bash
node ${CLAUDE_SKILL_DIR}/../../scripts/eval-api.bundle.js get-results --workspace <path> --client-id <id> --run-id <runId>

Present a summary table (total, passed, failed, errors). For failures:

Metric	What to check
`GeneralQuality` Fail	Which of relevance/completeness/groundedness/abstention failed
`ExactMatch` Fail	Score 0.0–1.0
`CapabilityUse` Fail	`missingInvocationSteps`
`Error` status	`errorReason` — often a test set config issue, not a YAML issue

Step 6: Propose fixes (if failures found)

For YAML authoring failures: find the relevant topic, read it, propose specific edits. Wait for user approval before applying.

After applying: offer to push and re-run (go back to Step 3).

Frequently asked questions

What does the Run Eval AI skill do?

Why use Run Eval on TypingMind?

Because you install it once and use it with any model. Run Eval is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Run Eval in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/skills-for-copilot-studio/tree/main/skills/run-eval. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Run Eval?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Run Eval?

As many as you like. As long as a model supports skills, you can use Run Eval with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Run Eval AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Instructions

View

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Run Evaluation (PPAPI)

Step 1: List test sets and let the user choose

Step 2: Ask about authenticated execution — MANDATORY, do not skip

Step 3: Start the run

Step 4: Poll until complete

Step 5: Fetch and analyze results

Step 6: Propose fixes (if failures found)

Frequently asked questions

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