Spelling Bee Hive

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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds useful context beyond that: the catalogue is internal and exceeds a hundred thousand words, and results include links and audio recordings. Return-field detail is partly redundant given an output schema exists.

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?

Purpose and resource are front-loaded in the opening clause, and the trailing sentence gives usage. The middle enumeration of every returned field is fairly long, though it does help the agent judge whether the tool fits the query.

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?

For a one-parameter read-only lookup with a full output schema, the description covers what it does, what the source data is, and when to reach for it. No auth, pagination, or side-effect caveats are needed for a public catalogue read.

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?

There is a single parameter with 100% schema description coverage, including example words, so the schema fully carries parameter meaning. The description's mention of 'an English word' reinforces the expected input domain, but adds little beyond the schema.

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 (look up an English word) and names the exact source catalogue with its scale. It is clearly distinguishable from the list-style siblings (trending_words, words_of_the_year, etc.), which browse collections rather than resolve a single word.

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?

The final sentence gives concrete usage contexts: checking a spelling and retrieving the clue types a speller may ask for in a bee. It does not explicitly name an alternative sibling or state when not to use it, so it stops short of a 5.

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 readOnlyHint/not-destructive and idempotentHint=false; the description usefully confirms non-determinism ('picked at random') and details the payload contents (pronunciation, part of speech, definition, origin, example sentence, recording). It stops short of stating rate limits or whether different calls with the same level can overlap.

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?

The purpose and level banding are front-loaded in a single efficient sentence, and the quiz-conduct guidance is supportive rather than filler. The trailing 'Run it like a bee' sentence is somewhat verbose but still earns its place as usage guidance.

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 structure need not be spelled out; nonetheless the description names the fields returned. Difficulty semantics, randomness, and invocation context are all covered, leaving nothing an agent needs missing.

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 real meaning the schema lacks: the banding of levels (1-3 School, 4-6 Advanced, 7-9 Champion) and the calibration of 1 as easiest to 9 as national-final difficulty. The count parameter is left entirely to the schema.

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 (get) and resource (practice words) with the distinctive scoping detail that words are picked at random from free practice sets at a chosen difficulty. This clearly separates it from siblings like look_up_word or trending_words, which retrieve established word data rather than quizzing material.

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 context for use — quizzing a speller — plus a step-by-step usage pattern ('say the word, give those clues when asked, reveal the spelling after'). It does not name or exclude any alternative sibling tool, so the routing guidance is implied rather than explicit.

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 readOnlyHint, idempotentHint, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered. The description adds useful context about returned content (grouped by topic, spelling tip, page link) but says nothing about how 'recently' is defined or how results are ordered.

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?

A single front-loaded sentence with no filler; every clause describes returned content. It is appropriately sized for a one-parameter read tool.

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 an output schema present, return values need not be explained, and annotations carry the safety profile. The remaining gap is the undefined 'recently' window and lack of any routing versus sibling tools, but for a simple read tool this is close to complete.

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%, so the sole 'limit' parameter is already fully documented in the schema (range 1-100, default 30). The description adds nothing about the parameter, so 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?

The description names a specific resource — words recently searched for spelling/pronunciation/definition — plus its shape (grouped by topic, with a tip and link). It is clear what the tool returns, though it never explicitly contrasts itself with siblings like words_of_the_year, which could superficially sound similar.

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?

There is no when-to-use guidance. Nothing says whether this is the right choice versus look_up_word (single word lookup) or words_of_the_year (annual list), and no prerequisites, freshness window, or exclusions are given.

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, idempotent, non-destructive, and closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: ordering is newest-first, coverage spans back to 1925, scope includes regional and international bees, and each result links to the word's page.

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, both earning their place: the first covers what is returned and in what order, the second covers filtering and the default. No redundancy or filler, and the most important framing (scope + ordering) is front-loaded.

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 an output schema present, return-value detail is not required, and all three optional parameters are covered elsewhere. The description supplies everything an agent needs to call this correctly: default behavior, filter semantics, ordering, and result scope.

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 parameter definitions are already well documented and the baseline would be 3. The description still adds meaning by explaining the interaction of the filters and what happens when none are supplied (defaults to recent national championship winners), which the schema does not state.

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+resource (returns winning words of past spelling bees) and scopes it clearly: newest first, national championship back to 1925 plus national and regional bees worldwide. This is easily distinguished from siblings like look_up_word, practice_words, trending_words, and words_of_the_year, none of which deal with historical competition winners.

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 clear context for filtering ('by part of a competition's name... or by year') and spells out the no-filter default behavior ('returns the most recent national championship winners'). It doesn't name or defer to a sibling tool, so it stops short of explicit when-not/alternatives guidance.

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, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds a genuinely useful behavioral detail beyond them: a not-yet-announced pick reports when it is expected, which tells the agent how to interpret an incomplete result.

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 tight sentences with no filler; the payload description is front-loaded, followed by the edge-case note. Efficient, though the second sentence would read better attached to a clearer statement of scope.

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 an output schema present, the description need not explain return formatting, and its summary of contents plus the unannounced-pick caveat is enough for correct invocation. Only the absence of sibling routing keeps it from being fully complete.

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% on the single optional year parameter, and the schema already explains the format (e.g. 2025) and the default. The description adds nothing further about the parameter, so the 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?

The description names a specific resource (each major dictionary's Word of the Year for a given year) and enumerates the fields returned (pronunciation, meaning, spelling tip), so the agent knows exactly what it gets. It does not distinguish itself from siblings like winning_words or trending_words, which could plausibly overlap, so it stops short of a 5.

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?

There is no statement of when to use this tool versus look_up_word, practice_words, trending_words, or winning_words, and no exclusions or prerequisites. The only hint is the year parameter defaulting to the most recent year, which is usage-implied at best.

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