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MicrosoftKnown publishermicrosoft/skills-for-copilot-studio/skills/create-eval-set/SKILL.md

create-eval-set

Skill486 starsChanged 8 months agoMITView on GitHub

Create a test set CSV file for import into Copilot Studio's in-product Evaluate tab. Reads the agent's topics, instructions, and knowledge sources to generate meaningful test cases with appropriate graders (General quality, Compare meaning, Exact match, etc.). Use when the user asks to create, prepare, or generate evaluation test cases for their agent.

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We split this skill into the rules it gives an agent

13 rules. About 0 are common, 10 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈10

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Create a test set CSV file that can be imported into Copilot Studio's Evaluate tab for in-product agent evaluation.

    line 15
  2. Distinctive:

    Read the agent's YAML files to understand what it does:

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  3. Very specific:

    Read agent.mcs.yml — get the agent's instructions, description, and capabilities

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  4. Very specific:

    Read settings.mcs.yml — check orchestration mode (generative vs classic)

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  5. Distinctive:

    Read key topics (especially non-system ones) — understand trigger phrases, conversation flows, expected behaviors

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  6. Distinctive:

    Check for knowledge sources, actions, and connected tools

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  7. Distinctive:

    Create test cases that cover:

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  8. Distinctive:

    Write expected responses with this in mind:

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  9. Very specific:

    Leave expectedResponse empty for questions that only need General quality (it works without expected responses)

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  10. Distinctive:

    Write the CSV file using the Write tool.

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  11. Distinctive:

    Use double quotes around all values

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  12. Distinctive:

    After writing the CSV, tell the user:

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  13. Distinctive:

    After import, some things can only be configured in the UI:

    line 120

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Create Evaluation Test Set

Create a test set CSV file that can be imported into Copilot Studio's Evaluate tab for in-product agent evaluation.

Phase 1: Understand the Agent

Read the agent's YAML files to understand what it does:

  1. Glob: **/agent.mcs.yml — find the agent
  2. Read agent.mcs.yml — get the agent's instructions, description, and capabilities
  3. Read settings.mcs.yml — check orchestration mode (generative vs classic)
  4. Glob: **/topics/*.mcs.yml — list all topics
  5. Read key topics (especially non-system ones) — understand trigger phrases, conversation flows, expected behaviors
  6. Check for knowledge sources, actions, and connected tools

Phase 2: Design Test Cases

Create test cases that cover:

CategoryWhat to testExample
Core functionalityMain topics and capabilitiesQuestions matching trigger phrases
Knowledge/generativeKnowledge source responsesQuestions the agent should answer from its knowledge
System topicsGreeting, Escalation, Goodbye, Thank You, Fallback"Hi", "I want to speak to a person", "Goodbye"
Edge casesOut-of-scope, ambiguous, off-topic"Tell me a joke", "Book a flight for me"
Boundary testingThings the agent should NOT doActions beyond its capabilities

Aim for 10–25 test cases with good coverage across categories.

Phase 3: Write the Expected Responses

The CSV import only supports two columns: question and expectedResponse. Test methods cannot be set via CSV import — they are configured in the UI after import. The default test method (General quality) is applied to all imported test cases.

Write expected responses with this in mind:

  • For questions where you want General quality grading: write behavioral descriptions ("The response should recommend hotels in Paris with relevant details")
  • For questions where you'll later switch to Compare meaning or Exact match in the UI: write realistic agent replies that the grader can compare against
  • Leave expectedResponse empty for questions that only need General quality (it works without expected responses)

Available test methods (configured in UI after import)

Test methodWhat it measuresRequires expected response?
General quality (default)AI-graded quality: relevance, completeness, groundedness, abstentionNo (but recommended as a rubric)
Compare meaningSemantic similarity — compares meaning/intentYes
Text similarityCosine similarity of textYes, configurable pass threshold
Exact matchCharacter-for-character matchYes
Keyword matchResponse contains expected keywords/phrasesYes (keywords added in UI)
Capability useAgent called expected tools/topicsConfigured in UI
CustomCustom grader with your own instructions and labelsConfigured in UI

Phase 4: Write the CSV

Write the CSV file using the Write tool. The format must be:

"question","expectedResponse"
"User question here","Expected agent response or behavioral rubric"
"Question without expected response",

Column specification

ColumnRequiredDescription
questionYesThe user message to send to the agent. Max 1,000 characters.
expectedResponseNoThe expected response or behavioral rubric. Leave empty if not needed.

Important: The Testing method column is not supported on import — it is ignored. All imported test cases get the default test method (General quality). Configure other test methods in the UI after import.

Rules

  • Max 100 questions per test set
  • Max 1,000 characters per question (including spaces)
  • File must be .csv format
  • Use double quotes around all values
  • For questions that will use General quality: write expected responses as behavioral descriptions
  • For questions that will use Compare meaning or Exact match: write expected responses as realistic agent replies

Expected response examples

Behavioral rubric (for General quality):

"Find me a hotel in Paris","The response should include hotel recommendations in Paris with relevant details like names, locations, or prices."

Realistic reply (for Compare meaning — set method in UI after import):

"Hi there","Hello! How can I help you today?"

Exact expected text (for Exact match — set method in UI after import):

"What is 2+2?","4"

Phase 5: Instruct the User

After writing the CSV, tell the user:

To import into Copilot Studio:

  1. Open your agent in Copilot Studio
  2. Go to the Evaluate tab
  3. Click New evaluation > Single response
  4. Drag or browse for the CSV file
  5. Review the imported test cases and adjust if needed
  6. Optionally add more test methods (Capability use, Custom) in the UI
  7. Click Evaluate to run, or Save to run later

After import, some things can only be configured in the UI:

  • Pass thresholds for Compare meaning and Text similarity
  • Keywords for Keyword match test cases
  • Expected capabilities for Capability use test cases
  • Custom grader instructions and labels

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