get_paperswithcode_trending

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

With no annotations provided, the description bears full responsibility for behavioral disclosure. It only mentions the data source and does not disclose key behaviors such as whether results are cached, rate limits, sorting order, or what fields are returned. This is insufficient for an agent to understand side effects or 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 very concise with only two sentences, front-loading the purpose and data source. It earns its place with no wasted words, though it could benefit from additional structure (e.g., bullet points for usage notes).

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 has 2 optional parameters, no output schema, and low complexity, the description provides a minimal but adequate overview. However, it lacks details on response format (e.g., paper titles, URLs, scores), which would be helpful for an agent to interpret results. It is complete enough for a simple fetch but not 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?

Schema coverage is 100%, so the baseline is 3. The description adds value by providing usage guidance for the 'limit' parameter ('Use 10-20 for quick overview, 50+ for comprehensive research'), which goes beyond the schema's description. This enriches parameter semantics.

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 it retrieves trending ML/AI research papers with code, using a specific verb and resource. It distinguishes from siblings by specifying 'trending' and naming the data source (HuggingFace Daily Papers), differentiating it from get_paperswithcode_latest and others.

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 suggests using it for 'latest AI research, machine learning papers, deep learning advances,' but does not explicitly state when to avoid this tool or mention alternatives among the many sibling tools. The guidance is implied but lacks exclusion criteria.

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