words

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the tool is 'useful for autocomplete and spelling suggestions,' which hints at read-only behavior, but doesn't explicitly state whether it's read-only, its performance characteristics, rate limits, or error handling. This leaves significant gaps for a tool with no annotation coverage.

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 description is concise and well-structured with two sentences: the first states the core purpose, and the second adds practical context. Every sentence earns its place without redundancy, making it efficient and 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?

Given the tool's moderate complexity (2 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and usage context but lacks details on behavioral traits, output format, or how it differs from siblings. This meets minimum viability but has clear gaps in providing a full understanding.

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 schema already documents both parameters ('prefix' and 'limit') with clear descriptions. The description adds no additional parameter semantics beyond what the schema provides, such as examples of prefix usage or details on result ordering. Baseline 3 is appropriate when the schema does the heavy lifting.

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 clearly states the tool's purpose: 'Get word completions from a prefix' specifies the verb ('Get') and resource ('word completions'), and 'Useful for autocomplete and spelling suggestions' provides context. However, it doesn't explicitly differentiate from sibling tools like 'find_words' or 'find_related', which might offer similar word-finding functionality.

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 description implies usage for autocomplete and spelling suggestions, giving some context for when to use it. However, it doesn't provide explicit guidance on when to choose this tool over alternatives like 'find_words' or 'find_synonyms', nor does it mention any exclusions or prerequisites for use.

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?

With no annotations, the description carries full burden but only covers basic functionality. It doesn't disclose behavioral traits like rate limits, error conditions, response format, or whether results are sorted/filtered. The description is functional but lacks operational context.

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 description is perfectly concise and front-loaded: a single sentence stating the core purpose followed by a comprehensive list of relation types. Every element serves a clear purpose with zero wasted words.

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?

Given no annotations, no output schema, and 3 parameters, the description is incomplete. It explains what the tool does but not how it behaves operationally—missing details on response format, error handling, or performance characteristics that would help an agent use it effectively.

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 baseline is 3. The description adds minimal value by listing relation types with codes, which the schema already documents clearly. No additional parameter semantics beyond what's in the schema are provided.

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 clearly states the specific action ('Find words related to') and resource ('a given word'), with explicit differentiation from sibling tools by listing all relation types. It distinguishes itself from find_rhymes and find_synonyms by being more comprehensive.

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 description implies usage through the detailed relation type list, suggesting when to use specific codes, but lacks explicit guidance on when to choose this tool over siblings like find_rhymes or find_synonyms. No clear when-not-to-use or alternative scenarios are provided.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool finds and ranks rhymes but doesn't describe what 'score' means, whether results are paginated, error handling, rate limits, or performance characteristics. This leaves significant gaps in understanding how the tool behaves beyond its basic function.

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 description is a single, efficient sentence that front-loads the core purpose ('find words that rhyme') and adds a key behavioral detail ('ranked by score'). There's zero wasted text, making it appropriately sized and easy to parse quickly.

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?

Given no annotations and no output schema, the description is incomplete for a tool with behavioral complexity. It doesn't explain what 'score' represents, the format of returned results, or any constraints on the input word. For a tool that ranks results, more context about the ranking mechanism and output structure is needed.

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 schema already fully documents both parameters ('word' and 'limit'). The description adds no additional parameter semantics beyond what's in the schema, such as explaining word format constraints or score calculation. Baseline 3 is appropriate when the schema does all the parameter documentation work.

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 clearly states the verb 'find' and the resource 'words that rhyme with a given word', specifying the exact function. It distinguishes from sibling tools like 'find_synonyms' or 'find_related' by focusing specifically on rhyming words, not synonyms or related concepts.

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 description provides no guidance on when to use this tool versus alternatives like 'find_synonyms' or 'find_related'. It mentions ranking by score but doesn't explain when rhyming is preferred over other word-finding methods, leaving the agent without contextual usage instructions.

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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It adds value by specifying that results are 'ranked by similarity score,' which isn't obvious from the name or schema. However, it lacks details on error handling, rate limits, data sources, or output format (e.g., whether it returns a list of strings or structured objects). For a tool with no annotations, this leaves gaps in understanding its behavior.

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 description is extremely concise—a single sentence that efficiently conveys the core functionality. Every word earns its place: 'Find synonyms' states the action, 'for a word' specifies the input, and 'ranked by similarity score' adds critical behavioral context. It's front-loaded with the main purpose.

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?

Given the tool's moderate complexity (2 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and ranking behavior but lacks details on output structure, error cases, or usage distinctions from siblings. Without an output schema, the agent doesn't know what the return values look like (e.g., list of strings vs. objects with scores).

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 schema fully documents both parameters ('word' and 'limit'). The description doesn't add any parameter-specific information beyond what's in the schema. According to the rules, when coverage is high (>80%), the baseline score is 3 even with no param info in the description.

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 clearly states the tool's purpose: 'Find synonyms for a word, ranked by similarity score.' It specifies the verb ('find'), resource ('synonyms'), and key behavioral aspect ('ranked by similarity score'). However, it doesn't explicitly differentiate from sibling tools like 'find_related' or 'find_words', which might also involve word relationships.

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 description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'find_related' or 'autocomplete', nor does it specify contexts where synonyms are preferred over other word-finding operations. The agent must infer usage from the name and description alone.

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?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool as an 'advanced word search' but doesn't mention critical behaviors like whether it's read-only, how results are ordered, if there are rate limits, or what the output format looks like. For a search tool with no annotation coverage, this leaves significant gaps in understanding its operation.

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 description is a single, efficient sentence that front-loads the core purpose ('Advanced word search') and lists the constraint types. It avoids redundancy and wastes no words, though it could be slightly more structured by explicitly separating the constraint categories for easier parsing.

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?

Given the complexity of a word search with multiple constraint types, no annotations, and no output schema, the description is incomplete. It doesn't explain how constraints combine (e.g., AND/OR logic), what the return values look like, or behavioral aspects like error handling. This leaves the agent with insufficient context for reliable tool invocation.

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?

The input schema has 100% description coverage, so the schema already documents all four parameters (limit, sounds_like, meaning_like, spelled_like) with clear descriptions. The tool description adds value by summarizing the constraint types (meaning, pronunciation, spelling) but doesn't provide additional syntax, examples, or interaction details beyond what the schema offers, meeting the baseline for high schema coverage.

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 clearly states the tool's purpose as an 'advanced word search' that finds words matching constraints on meaning, pronunciation, and spelling. It specifies the verb ('find') and resource ('words') with the scope of constraints, but doesn't explicitly differentiate from sibling tools like 'find_synonyms' or 'find_rhymes' which might overlap in word-finding functionality.

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 description provides no guidance on when to use this tool versus alternatives like 'find_synonyms' or 'find_rhymes'. It mentions a 'combination of constraints' but doesn't specify scenarios, exclusions, or prerequisites for choosing this over other word-finding tools, leaving the agent to infer usage based on the parameters alone.

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