mcpbeat

Analyze Eval

get-convex/analyze-eval

Investigate a single failing eval from the convex-evals system. Use when the user shares a visualizer URL pointing to a specific eval, asks about a specific failing eval, or references a specific eval ID.

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the whole folder, loaded on every use
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on the repository, not the skill itself

Install

one command, takes just this skill from the repository
npx skills add https://github.com/get-convex/convex-evals --skill analyze-eval

The instruction itself

6 sections, as written by the author

Analyze Eval

When to use

  • User shares a URL like https://convex-evals.netlify.app/experiment/.../run/$runId/$category/$evalId
  • User asks "why did this eval fail?" or "what went wrong with this eval?"
  • User references a specific eval ID

Step 1: Extract the eval ID from the URL

The visualizer URL pattern is:

/experiment/$experimentId/run/$runId/$category/$evalId?tab=steps
  • $runId — the Convex document ID for the run (e.g. jn7922j1w29pdxm76bj9ps0enx80mg9e)
  • $evalId — the Convex document ID for the specific eval (e.g. jh73jvjz2n00gfeve1dt5h963s80mbc6)

You need the evalId to query.

Step 2: Query the debug action

Run the internal action from the evalScores/ directory. Always use --prod to query the production database (where CI writes results):

npx convex run --prod debug:getEvalDebugInfo '{"evalId": "<evalId>"}'

This returns a JSON object with:

| Field | Contents |

|-------|----------|

| eval | Name, category, evalPath, status (pass/fail + failure reason), task text |

| run | Model name, provider, experiment name, run status |

| steps | Array of step results: filesystem, install, deploy, tsc, eslint, tests — each with pass/fail/skipped and failure reason |

| outputFiles | Map of file path -> file content from the model's generated output (unzipped) |

| evalSourceFiles | Map of file path -> file content from the eval source (answer dir, grader, TASK.txt, etc.) |

Step 3: Analyze the failure

With the data returned, compare:

  • Which step failed? — Check steps for the first entry with status.kind === "failed". The failureReason field has the error message.
  • What did the model generate? — Look at outputFiles for the model's code.
  • What was expected? — Look at evalSourceFiles for the answer directory and grader test files.
  • What was the task? — Check eval.task for the TASK.txt content.

Common failure patterns:

  • eslint fail — Check the failure reason for the specific lint rule violated. Compare the model output against the answer to spot the lint issue.
  • tsc fail — TypeScript compilation error. Check the failure reason for the specific type error.
  • convex dev fail — Schema or function definition issues that prevent Convex from deploying.
  • tests fail — The grader tests didn't pass. Compare outputFiles against evalSourceFiles (look for files like grader.test.ts or answer/) to understand what the tests expected.

Step 4: Classify and report findings

Classify the failure as one of:

  • MODEL_FAULT: The model genuinely got it wrong
  • OVERLY_STRICT: The eval/lint/test requirements are unreasonable for what was asked
  • AMBIGUOUS_TASK: The task description is unclear and the model's interpretation was reasonable
  • KNOWN_GAP: A known limitation of this eval that affects all models (e.g. the Convex API returns fields the model can't predict without being told)

Summarize:

  • The eval name, model, and experiment
  • Which step failed and the exact error
  • The classification and reasoning
  • The relevant code from the model output that caused the failure
  • What the correct code should look like (from the answer/eval source)
  • Whether any action is recommended (config change, task clarification, etc.)

How to use it

Copy the folder

Take get-convex/analyze-eval from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npx. Without those the skill loads but fails at the first command.