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 states the tool fetches info but doesn't describe key behaviors like whether it's a read-only operation, error handling for invalid IDs, rate limits, or authentication needs. This is a significant gap 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 appropriately sized and front-loaded, with the main purpose stated first and parameter details following. It uses two sentences efficiently, with no wasted words, 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 (1 parameter) and the presence of an output schema, the description is somewhat complete but has gaps. It covers the basic purpose and parameter usage but lacks behavioral details and usage guidelines. With an output schema, it doesn't need to explain return values, but overall it's only minimally adequate.

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 semantics beyond the input schema. The schema has 0% description coverage, but the description explains that 'arxiv_ids' can be a list or string and provides an example (e.g., ["2503.01469", "2503.01470"]), clarifying usage. With only one parameter, this compensates well for the low 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: 'Get the Arxiv info for a list of papers.' It specifies the verb ('Get') and resource ('Arxiv info'), making it understandable. However, it doesn't explicitly differentiate from the sibling tool 'semantic_search_papers_on_huggingface', which appears to be a search tool rather than a direct fetch by ID, so it misses full sibling distinction.

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 the sibling tool or any other context for usage, such as prerequisites or scenarios where this tool is preferred over others. This leaves the agent without explicit direction on tool selection.

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 mentions that the query 'will automatically determine if it should use keywords or a natural language query,' which adds some context about the tool's behavior. However, it lacks details on rate limits, authentication needs, error handling, or what happens with invalid inputs, which are important for a search 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 appropriately sized and front-loaded, with the core purpose stated first. The Args and Returns sections are structured clearly, though the 'Returns' section could be more concise (e.g., listing fields without full sentences). Overall, it's efficient with minimal waste.

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, but with an output schema), the description is reasonably complete. It explains the parameters and return format, and the output schema likely covers the return structure in detail. However, it could benefit from more behavioral context (e.g., search scope, limitations) to be fully comprehensive.

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 significant meaning beyond the input schema, which has 0% description coverage. It explains that 'query' can be keywords or natural language and will be automatically interpreted, and it specifies the default and flexibility for 'top_n'. This compensates well for the schema's lack of descriptions, though it doesn't cover all possible edge cases (e.g., query length limits).

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 HuggingFace using semantic search.' This specifies the verb (search), resource (papers on HuggingFace), and method (semantic search). However, it doesn't explicitly differentiate from the sibling tool 'fetch_paper_details_from_arxiv' (which appears to fetch details rather than search), 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. While it mentions semantic search, it doesn't explain when to prefer this over keyword-based search or the sibling tool. There's no mention of prerequisites, limitations, or typical use cases, leaving the agent with minimal context for selection.

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