hf_papers_daily

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

No annotations are provided, so the description carries the full burden. It discloses that the tool is a read-only fetch operation, but it does not mention any authentication requirements, rate limits, or details about what 'trending' means (e.g., based on likes, views). It is sufficient for a simple fetch tool but lacks deeper 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 two concise sentences, front-loaded with the primary action and resource. Every word adds value, with no redundancy or filler.

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 tool with only two parameters and no output schema, the description is adequately complete. It clearly explains the purpose and context. It could be slightly improved by explicitly stating that it returns a list of papers, but that is implied by 'Fetch papers.'

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% for both parameters (date and limit), so the schema already documents them. The description adds no additional parameter-specific meaning beyond the schema, so the baseline of 3 applies.

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 fetches daily curated papers from Hugging Face and is used to check AI research trends. The verb 'Fetch' plus the specific resource 'daily curated papers' distinguishes it from sibling tools like hf_papers_search, which handles search queries.

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 for when to use the tool—when you want daily trending papers—but it does not explicitly mention alternatives or exclusions. It implies a specific use case without naming sibling tools for different needs.

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