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 searches across directories and returns JSON or an error, but lacks details on permissions, rate limits, side effects, or error handling. For a search tool with zero annotation coverage, this is insufficient.

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 appropriately sized and front-loaded, with the purpose stated first, followed by parameter and return details. It uses clear sections ('Args:', 'Returns:') and avoids unnecessary words, though it could be slightly more concise by integrating the return statement into 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 (search operation with one parameter), no annotations, and no output schema, the description is minimally adequate. It covers the purpose and basic I/O but lacks details on behavior, error cases, and differentiation from siblings, making it incomplete for optimal agent use.

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 description adds meaning for the single parameter 'paper_id' by explaining it's 'The ID of the paper to look for,' which clarifies its role. However, schema description coverage is 0%, and the description doesn't specify format, constraints, or examples, leaving gaps in parameter understanding.

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: 'Search for information about a specific paper across all topic directories.' It specifies the verb ('search'), resource ('paper'), and scope ('across all topic directories'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_papers'.

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 'search_papers' or specify use cases, prerequisites, or exclusions. The agent must infer usage from the purpose 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, and the description does not disclose behavioral traits such as data source freshness, authentication requirements, rate limits, or error handling for invalid states. The agent is left uninformed about important runtime behaviors.

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 (two lines) with the purpose front-loaded. Every sentence adds value: the first states the action, the second clarifies the parameter. No 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?

For a simple one-parameter tool with no output schema, the description is largely complete. It explains what the tool does and how to specify the input. However, it does not mention what the return value contains (e.g., alert details, count), which could be useful for an agent.

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?

With 0% schema description coverage, the description adds crucial meaning by specifying the parameter format ('Two-letter US state code') and providing examples (CA, NY). This adequately compensates for the missing schema descriptions.

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') and resource ('weather alerts') with a specific scope ('for a US state'). It is unambiguous and distinguishes the tool's function even without sibling tools present.

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 when to use the tool (when needing weather alerts for a US state) but does not provide explicit exclusions or alternatives. Since there are no sibling tools, this is acceptable but could be more prescriptive about valid state codes.

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 full burden for behavioral disclosure. It states what the tool does but doesn't describe any behavioral traits - no information about rate limits, authentication needs, whether this is a read-only operation, what format the forecast returns, or any side effects. This is inadequate 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 appropriately sized with a clear purpose statement followed by parameter documentation. The two-sentence structure is efficient, though the parameter documentation could be integrated more seamlessly rather than as a separate 'Args:' section. Every sentence serves a 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 no annotations, no output schema, and a simple 2-parameter tool, the description is incomplete. It doesn't explain what the forecast returns (format, time range, metrics), any limitations (e.g., historical vs. future forecasts), or behavioral constraints. For a weather API tool, users need to know what data they'll receive.

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?

With 0% schema description coverage and 2 parameters, the description compensates well by explicitly listing both parameters ('latitude' and 'longitude') and providing basic semantic context ('Latitude of the location', 'Longitude of the location'). This adds meaningful information beyond the bare schema, though it doesn't specify format constraints or valid ranges.

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 with 'Get weather forecast for a location' - a specific verb ('Get') and resource ('weather forecast') with scope ('for a location'). However, it doesn't differentiate from sibling tools like 'get_alerts' which might also relate to weather, so it doesn't reach the highest 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. There's no mention of when-not scenarios, prerequisites, or comparison with sibling tools like 'get_alerts' (which might provide weather alerts instead of forecasts). The agent must infer usage from the name 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 storing information, which implies a write operation, but doesn't specify where or how storage occurs, potential side effects, or any constraints like rate limits or authentication needs. This leaves significant gaps in understanding the tool's behavior beyond the basic search 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 well-structured and concise, with a clear purpose statement followed by bullet points for arguments and returns. Every sentence adds value: the first defines the tool's action, and the subsequent sections efficiently document parameters and output without redundancy. It's front-loaded and wastes no 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 the tool's moderate complexity (2 parameters, no annotations, no output schema), the description is minimally adequate. It covers the basic purpose and parameters but lacks details on behavioral traits, usage context, and output specifics (e.g., what 'store their information' entails or the format of returned IDs). This leaves room for improvement in completeness.

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 description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'topic' is for searching and 'max_results' sets a retrieval limit with a default of 5, clarifying their roles. However, it doesn't detail format constraints (e.g., topic string requirements) or the implications of the default value, leaving some ambiguity.

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: 'Search for papers on arXiv based on a topic and store their information.' It includes a specific verb ('search') and resource ('papers on arXiv'), and distinguishes itself from sibling tools like 'extract_info' or 'get_forecast' by focusing on paper retrieval. However, it doesn't explicitly differentiate from potential similar search tools beyond the arXiv context.

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 mentions storing information but doesn't clarify if this is for archival, analysis, or other purposes, nor does it reference sibling tools like 'extract_info' which might handle related tasks. Usage is implied through the action described, but no explicit context or exclusions are provided.

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