analyze-evals
Analyze exported evaluation results from Copilot Studio's Evaluate tab.
Skill by microsoftOfficial
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/microsoft-analyze-evals
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: spreadsheets, design, backend, agent-building
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/analyze-evals
Tools it pre-approves 4
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Read,Glob,Grep,Edit
What's inside
- Skill name
analyze-evals- Description
- Analyze exported evaluation results from Copilot Studio's Evaluate tab. The user provides a CSV file exported from the Copilot Studio UI; this skill parses it, identifies failures, and proposes YAML fixes. No API access or published agent required — just the exported CSV.
- License
- MIT
- Allowed tools
- Read,, Glob,, Grep,, Edit
- Instructions
- 52 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: missing
Files (1)
- SKILL.md
SKILL.md (first lines)
# 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 <agent name> <date>.csv` in their Downloads folder. 2. **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`). 2. 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 2. **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) 3. **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 4. **Apply accepted changes** using the Edit tool. After applying, remind the user to push and publish again before re-running evaluations.
From microsoft/skills-for-copilot-studio, MIT.
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Signals
- Stars
- 482
- Forks
- 103
- Open issues
- 29
- Last commit (this folder)
- Apr 6, 2026 (6 months ago)
- Last release
- May 13, 2026 (5 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
analyze-evals skill. Agent Mart. https://agentmart.dev/skills/microsoft-analyze-evals (last updated 2026-10-24)