Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world) and the description is consistent with them. It adds real behavior beyond the schema: a line solver validates uniqueness, and the fix setting controls whether ambiguous pictures get hint cells, altered cells, or an error listing unclear rows. Reproducibility via seed is also disclosed, though rate limits or output size limits are not mentioned.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the when-to-use case, then puzzle-source options, then ambiguity handling, then layout, then exclusions — a sensible order. It is dense but nearly every clause carries information; the long list of quoted trigger phrases is the only slightly padded part.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With 14 optional parameters and an output schema already documenting the return value, the description supplies what is missing: how to choose between puzzles[] and count, how grid input is encoded, the ambiguity-resolution policy, and the page-layout knobs. Nothing an agent needs to call it correctly is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine routing logic the schema does not: puzzles[] holds one object per puzzle when they differ (shape, text, grid, or difficulty/size), while count should be used for a set of uniform random puzzles. Layout parameters (per_page, paper, title, name line, answer pages) and the fix outcomes are also given operational meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and artifact: generates printable nonogram puzzles as a PDF with an answer key. It also enumerates synonyms (griddlers, hanjie, paint by numbers, pixel puzzles) and representative user phrasings, so an agent can match intent without ambiguity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit positive triggers ('make a nonogram', 'printable nonograms for my class', 'turn this pixel art into a nonogram') and explicit negatives: no colour nonograms, no reading photos or image files, no solving from a photo. There are no siblings, yet the when/when-not boundary is fully drawn.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.