wikipedia

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

With no annotations provided, the description carries full burden but only states what it returns (list of sections) without covering behavioral aspects like error handling, rate limits, authentication needs, or whether it's read-only/destructive. This is a significant gap for a tool with zero 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 front-loaded and concise with two sentences that efficiently convey purpose and output without any wasted words, making it easy for an agent 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?

For a simple read operation with one parameter and no output schema, the description covers basic purpose and output but lacks behavioral context (e.g., error cases, limitations). It's minimally adequate but has clear gaps in completeness given the absence of annotations.

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 the single parameter 'title' with its description. The description adds no additional parameter semantics beyond what the schema provides, meeting the baseline of 3 for high 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 verb ('Get') and resource ('section structure of a Wikipedia article'), specifying it returns a table of contents with titles and heading levels. It distinguishes from siblings like get_article_summary (summary content) and search_wikipedia (search 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 by mentioning 'by title,' which suggests it's for retrieving structure of a known article, contrasting with search_wikipedia for unknown articles. However, it doesn't explicitly state when not to use it or name alternatives, leaving some ambiguity.

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. It discloses behavioral traits by stating what data is returned (introduction extract, description, thumbnail URL, content URLs), which helps the agent understand the output format. However, it doesn't mention potential errors (e.g., if the article doesn't exist), rate limits, or authentication needs, leaving gaps in behavioral 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 a single, efficient sentence that front-loads the core action and resource, then lists the returned data without unnecessary details. Every part earns its place by clarifying the tool's purpose and output, making it 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 the tool's low complexity (one parameter, no output schema, no annotations), the description is mostly complete. It covers the purpose and output format adequately. However, it lacks error handling or edge case information (e.g., handling non-existent titles), which would enhance completeness for a read operation.

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%, with the parameter 'title' fully documented in the schema as 'Wikipedia article title (e.g., "Albert Einstein")'. The description adds no additional parameter semantics beyond what the schema provides, such as formatting constraints or examples. 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 specific action ('Get a summary'), target resource ('Wikipedia article by title'), and distinguishes from siblings by focusing on summary extraction rather than sections, random articles, or search. It explicitly mentions what information is returned, making the purpose unambiguous.

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 by specifying 'by title' and listing returned data, which suggests it's for retrieving structured summaries. However, it doesn't explicitly state when to use this tool versus alternatives like get_article_sections (for detailed structure) or search_wikipedia (for finding articles). No exclusions or prerequisites are mentioned.

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 mentions the return format ('title, extract, and page ID for each article'), which adds value beyond the input schema. However, it lacks details on potential limitations (e.g., rate limits, data freshness, or error conditions), which is a significant gap for a tool with zero 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 a single, efficient sentence that front-loads the purpose and key details (return format) with zero waste. It is appropriately sized for the tool's simplicity, making every word count without unnecessary elaboration.

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 low complexity (one optional parameter, no output schema, no annotations), the description is adequate but has clear gaps. It covers the basic purpose and return format, but lacks usage guidelines and full behavioral context (e.g., error handling or constraints), making it minimally viable but not 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?

The input schema has 100% description coverage, fully documenting the 'count' parameter with its type, range, and default. The description does not add any parameter-specific information beyond what the schema provides, so it meets the baseline score of 3 for high schema coverage without compensating value.

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 action ('Get random Wikipedia articles') and resource ('Wikipedia articles'), specifying what the tool does. It distinguishes from siblings like 'get_article_sections' or 'search_wikipedia' by focusing on random retrieval rather than specific articles or searches. However, it doesn't explicitly contrast with siblings in the text, keeping it from a perfect score.

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 'search_wikipedia' or 'get_article_summary'. It implies usage for fetching random articles but lacks explicit context, prerequisites, or exclusions, leaving the agent to infer based on tool names 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?

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the return format (title, snippet, page ID, word count) but lacks details on rate limits, authentication needs, error handling, or pagination. For a search tool, this leaves gaps in understanding operational constraints.

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 highly concise and front-loaded, consisting of two sentences that directly state the action and return values without unnecessary details. Every sentence earns its place by providing essential information efficiently.

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 (search operation with 2 parameters) and no annotations or output schema, the description is minimally adequate. It covers the purpose and return format but lacks behavioral details like error handling or performance limits. Without an output schema, it should ideally explain return values more thoroughly, but it does specify key fields.

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 (query and limit). The description adds no additional meaning beyond what the schema provides, such as examples or contextual usage for parameters. Baseline 3 is appropriate as the schema handles parameter documentation effectively.

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 searching Wikipedia articles by keyword, which is a specific verb (search) and resource (Wikipedia articles). It distinguishes from siblings like get_article_summary or get_random_articles by focusing on keyword-based search rather than retrieving specific articles or random content. However, it doesn't explicitly contrast with get_article_sections, which might also involve article retrieval.

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 scenarios where search_wikipedia is preferred over siblings like get_article_summary for summaries or get_random_articles for random content, nor does it specify prerequisites or exclusions. Usage is implied by the purpose but not explicitly defined.

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