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Puzzletide Agent Evals

skill-caravaca-labs-puzzletide-cli-puzzletide-agent-evals · by Caravaca-Labs

Use this skill when the user wants verifiable reasoning tasks to benchmark or test an LLM or agent — reproducible puzzle task sets (sudoku, word search) with objective, by-construction grading. No answer key to trust: answers are verified against the rules and the grid.

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Install

$ agentstack add skill-caravaca-labs-puzzletide-cli-puzzletide-agent-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.

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About

PuzzleTide Agent Evals

Generate reproducible, objectively gradable puzzle tasks for testing models and agents with the local PuzzleTide CLI.

Why puzzles: they are verifiable by construction. A sudoku answer either satisfies the rules and preserves the givens or it doesn't; a word search answer either spells the word along a straight line in the grid or it doesn't. Grading needs no LLM judge and no trusted answer key.

Prefer the local CLI. Check availability in this order:

ptide --version
puzzletide --version
npx puzzletide --version

If none of those work, ask the user before installing (npm install -g puzzletide).

Generate a task set

ptide eval generate --type sudoku --n 20 --difficulty hard --seed 1 --out tasks.json
ptide eval generate --type wordsearch --n 10 --difficulty medium --seed 1 --out tasks.json

The tuple (type, difficulty, n, seed) fully determines the task set, so it names a reproducible benchmark — same command, same tasks, on any machine.

Each task has id, instructions, and the puzzle payload:

  • sudoku: puzzle (81 chars, . = empty). Expected answer: completed 81-char string.
  • wordsearch: grid (array of row strings) and words. Expected answer: JSON array

of {word, startRow, startCol, endRow, endCol} (0-indexed).

Run the subject model

Send each task's instructions + payload to the model under test and collect answers as a JSON array of {id, answer}.

Grade

ptide eval check --tasks tasks.json --answers answers.json --json

Returns per-task pass/fail with reasons and a summary score. Grading is deterministic and local.

Links

Safety

  • Everything runs locally; no account, API key, or network access.
  • Do not install packages without asking the user first.

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.