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SKILL verified MIT Self-run

Analyze Evals

skill-microsoft-skills-for-copilot-studio-analyze-evals · by microsoft

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Install

$ agentstack add skill-microsoft-skills-for-copilot-studio-analyze-evals

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

Verified badge

Passed review? Show it. Paste this badge into your README, it links to the public security report.

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[![AgentStack Verified](https://agentstack.voostack.com/badges/verified.svg)](https://agentstack.voostack.com/security/report/skill-microsoft-skills-for-copilot-studio-analyze-evals)

Reliability & compatibility

Security review passed
0 installs to date
no reviews yet
1mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.

How agent discovery & health will work →
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About

Analyze Copilot Studio Evaluation Results

Analyze evaluation results exported from the Copilot Studio UI as CSV.

Phase 1: Get Results

  1. Ask the user for the CSV file path if not already provided. The file is typically exported from Copilot Studio's Evaluate tab and named Evaluate .csv in their Downloads folder.
  1. Read the CSV file. The in-product evaluation CSV has these columns:

| Column | Meaning | |--------|---------| | question | The test utterance | | expectedResponse | Expected response (may be empty) | | actualResponse | What the agent responded | | testMethodType_1 | Eval method (e.g., GeneralQuality) | | result_1 | Pass or Fail | | passingScore_1 | Score threshold (may be empty) | | explanation_1 | Why it passed/failed (e.g., "Seems relevant; Seems incomplete; Knowledge sources not cited") |

The _1 suffix indicates the first eval method. There may be additional methods (_2, _3, etc.) with the same column pattern.

Phase 2: Analyze Results

  1. Focus on failed evaluations (result_1 = Fail, or any result_N = Fail).
  1. For each failure, use the explanation column to understand the issue:
  • "Question not answered" — The agent couldn't handle the question. Check if there's a matching topic or knowledge source.
  • "Knowledge sources not cited" — The agent responded but didn't cite sources. Check knowledge source configuration and SearchAndSummarizeContent nodes.
  • "Seems incomplete" — The response was partial. Check topic flow for early exits, missing branches, or incomplete SendActivity messages.
  • Error messages in actualResponse (e.g., GenAIToolPlannerRateLimitReached) — These are runtime errors, not authoring issues. Flag them to the user as transient failures to retry.

Phase 3: Propose Fixes

  1. For each failure, identify the relevant YAML file(s):
  • Auto-discover the agent: Glob: **/agent.mcs.yml
  • Find the relevant topic by matching the test utterance against trigger phrases and model descriptions
  • Read the topic file to understand the current flow
  1. Propose specific YAML changes to fix each failure. Present them to the user as a summary:
  • Which test(s) failed and why
  • Which file(s) need changes
  • What the proposed change is (show the diff)
  1. Wait for user decision. The user can:
  • Accept all — apply all proposed changes
  • Accept partially — apply only some changes (ask which ones)
  • Reject — discard proposed changes and discuss alternative approaches
  1. Apply accepted changes using the Edit tool. After applying, remind the user to push and publish again before re-running evaluations.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

Reviews

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Versions

  • v0.1.0 Imported from the upstream source.