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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 the result limit ('up to 10 matches') and return fields (Q-id, label, description), which is helpful. However, it does not mention rate limits, authentication, or whether the operation is read-only (assumed from context, but not stated).

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 very concise: two sentences that cover what it does, what it returns, and a use case. No unnecessary words; every sentence adds value.

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 low complexity (single string parameter, no output schema, no annotations), the description is fairly complete. It states the purpose, result limit, and return fields. It could mention potential limitations (e.g., only matches by name) but overall covers the key aspects.

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 0%, so the description must compensate. It adds meaning by stating the query parameter is for searching 'by name,' but lacks details on matching behavior (e.g., partial matches, case sensitivity) or expected input format.

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 searches Wikidata entities by name and returns specific fields (Q-id, label, description). It also mentions a use case (entity disambiguation/canonicalization), distinguishing it from siblings like wiki_page_summary which focus on page summaries.

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 clear context with 'Use this for entity disambiguation / canonicalization,' indicating when to use it. It does not explicitly state when not to use it, but the purpose is distinct from sibling tools (summary, recent changes, trending).

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?

Lists outputs (extract, thumbnail, description, last modified) but does not disclose limitations, response format, or side effects. With no annotations, more detail on behavior would be beneficial.

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 purpose, no wasted words. Efficiently conveys key 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?

Describes outputs and use case, but lacks details on return structure (e.g., JSON format, thumbnail URL) given no output schema. Adequate for a simple tool 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?

Schema coverage is 0%, but the description implies the single parameter 'title' is a Wikipedia article title, adding meaning beyond the schema. Could specify case sensitivity or formatting.

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?

Clearly states it retrieves a clean summary of a Wikipedia article including extract, thumbnail, description, and last modified. Differentiates from siblings like wikidata_search (Wikidata queries) and wiki_trending (trending articles).

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?

Explicitly states use case: to verify an entity exists or pull a one-line description. Implicitly distinguishes from siblings, though could explicitly mention when not to 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?

No annotations are provided, so the description carries the burden. It describes the tool as 'live feed' but does not mention authentication, rate limits, or whether results are cached or streaming. Adequate but not detailed.

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, no filler. The first sentence states purpose and return fields. The second adds optional filtering and use case. Every sentence is informative and earns its place.

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 4 parameters, no output schema, and no annotations, the description provides a solid overview and key parameter hints. It lacks details on pagination, ordering, or limitations, but is fairly complete for a simple real-time feed 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 50% (topic and namespace have descriptions). The description adds meaning for 'topic' by specifying it does substring match against title and edit comment. It also mentions 'exclude_bots' but does not elaborate beyond the schema default. Overall, it adds value beyond 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?

The description clearly states the tool provides a 'live feed of recent edits to English Wikipedia' and lists the return fields (title, editor, timestamp, comment, size delta). This uniquely distinguishes it from sibling tools like wikidata_search, wiki_page_summary, and wiki_trending.

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 explicitly states usefulness for 'trend-monitoring or news-monitoring agents' and mentions that breaking news events appear in edits quickly. It does not explicitly exclude alternatives, but the use case is clear.

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 mentions the default date behavior but does not address rate limits, auth requirements, or whether the operation is read-only (though implied). The lack of explicit behavioral traits is a gap but acceptable for a simple tool.

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 two sentences, front-loaded with the core functionality, and contains no redundant or unnecessary words. Every sentence adds value.

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 simplicity (1 optional param, no output schema), the description covers the basic behavior. However, it does not mention the return format or structure of the results, which would be helpful for an agent without an output 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%, so the schema already documents the one parameter. The description adds no new information about the parameter beyond what the schema provides, meeting the baseline of 3.

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 returns the top 50 most-viewed English Wikipedia pages for a given date, with a specific verb (retrieve/list) and resource (trending pages). It distinguishes from siblings like wikidata_search, wiki_page_summary, and wiki_recent_changes by focusing on trending content.

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 a clear use case ('what's the world reading about?' signal) implying when to use it. However, it does not explicitly state when not to use it or provide alternatives, though the sibling tools cover other search/summary use cases.

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