GridSmith Puzzle Maker

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

Annotations only declare readOnly/idempotent/openWorld, but the description discloses the real output shape: interlocking grid, standard numbering, Across/Down lists, a report of unplaceable answers, a playable rendering, and a printable PDF with answer key. It also flags the normalization behavior on answers, which affects what the caller should pass in.

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?

Four sentences, each doing distinct work: trigger, behavior/output, input requirement, and exclusions. The trigger and the most surprising behavior (unplaced-answer reporting) are front-loaded, with no filler.

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 annotations and an output schema already present, the description covers everything an agent needs to decide and call: intake requirements, preprocessing, output forms, and the negative boundary. Only minor gap is that seed reproducibility is left entirely to the schema.

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 description coverage is 100% and the schema already documents seed, paper, title, and the entries structure with examples, so the schema carries the parameter burden. The description only restates the 4-40 entry-count constraint and the A-Z letter normalization, adding little that the schema does not already say. Baseline 3 applies.

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 resource ('builds a valid interlocking grid', 'crossword puzzle') and immediately lists the user intents it serves (crossword maker, class puzzle, vocabulary list). It is trivially distinguishable from generate_sudoku and generate_word_search by naming the artifact type explicitly.

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 the triggering condition ('Use this when the user wants a crossword puzzle'), a preprocessing instruction ('if the user gives only words, write a short clue for each first'), and explicit exclusions ('does not solve existing crosswords or answer single clues... does not make symmetric newspaper-style grids'). This is close to a complete decision procedure.

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

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

Annotations already declare readOnly, non-destructive, non-open-world, so the safety profile is covered. The description still adds real behavioral value beyond them: uniqueness is verified by a solver, the puzzle is playable in-chat with pencil notes, and a PDF with answer key is produced. It stops short of stating latency, size limits, or how the two output forms are returned, which keeps it off a 5.

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?

Two sentences, front-loaded with the usage trigger before the capability list and the exclusions last. The parenthetical keyword string ('sudoku generator, printable sudoku with answers, easy sudoku for kids, hard sudoku') is slightly redundant padding, but it is the only real waste in an otherwise tight definition.

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?

An output schema exists, yet the description still tells the agent what the user actually receives: an in-chat playable grid and a printable PDF with answer key. Combined with the scope limits (9x9 classic only) and all-defaults parameters, an agent has everything needed to call this correctly on the first try.

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% and each parameter already carries an example plus enum semantics, so the schema is doing the heavy lifting. The description reinforces the difficulty axis ('easy, medium or hard') and the existence of a printable PDF, but adds nothing about seed reproducibility, paper size, or title beyond what the schema states. Baseline 3 is appropriate.

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?

The description opens with a concrete verb and artifact ('Generates a classic 9x9 sudoku') and enumerates the delivered outputs (chat-playable puzzle, printable PDF with answer key). The resource is unambiguously a sudoku, which separates it cleanly from the crossword and word-search siblings without needing to name them.

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?

It states the triggering intent ('when the user wants a new sudoku puzzle to play or print') and then explicitly excludes adjacent requests: solving an existing puzzle, explaining strategies, and 4x4/6x6/variant grids. That is an explicit when/when-not pair, so an agent has no inference left to do.

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

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

Annotations already declare read-only, idempotent, non-destructive, closed-world, so the description correctly focuses on value-add: word-count validation (5-40), the exact direction rules behind each difficulty tier, duplicate-word detection, and reporting of words that could not be placed. It also discloses the two outputs — an on-screen playable puzzle and a printable PDF with answer key.

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?

Three sentences, front-loaded with the trigger, then mechanics, then exclusions — no filler. Every clause carries either routing or behavioral information.

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?

An output schema exists, so return format needn't be detailed, yet the description still tells the agent a playable puzzle plus PDF/answer key come back. Input validation, difficulty semantics, and sibling exclusions are all covered for a 6-parameter tool.

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 behavioral meaning beyond the schema: it explains that the word list is validated for duplicates and that unplaceable words are reported back. The difficulty tier descriptions largely restate the enum documentation already in the schema, which keeps it from a 5.

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 resource (generate a word search puzzle) and enumerates the user intents it serves (word find, word search maker, printable for kids/class). It also explicitly distinguishes itself from generate_crossword and from grid-scanning tools, so an agent can route correctly without opening the schema.

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?

Opens with an explicit trigger ('Use this when the user wants a word search puzzle ... from a list of words') and closes with two exclusions: not crosswords (use generate_crossword) and not finding words in a grid the user already has. Both when-to-use and when-not-to-use are covered.

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