list_papers

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

With no annotations, the description carries the burden. It discloses a key behavioral detail – pagination via `offset` defined as 'the last paper_uuid from the previous batch' – which goes beyond the schema. It does not mention ordering, result shape, or read-only nature, but those are either obvious or covered by the output schema.

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 three sentences, front-loaded with purpose, then usage, then parameter/pagination details. Every sentence adds distinct value with no fluff.

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?

The description explains the core listing functionality and pagination sufficiently, and an output schema exists for return values. However, it leaves out some filter parameters (e.g., year_min/year_max) which are non-obvious from names alone, making it slightly incomplete for a 12-parameter 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 description coverage is 0%, so the description must compensate. It lists 'year/venue/acronym/field_of_study/author' and 'offset', covering 5 of 12 properties. It omits range filters (year_gt/lt/min/max), limit, collection_id, and doesn't clarify whether 'acronym' maps to collection_acronym. The offset semantics are well explained, but the partial coverage leaves gaps.

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 'Browse ACL conference NLP papers using structured filters only (no semantic query)' – a specific verb+resource+constraint. It distinguishes from siblings by explicitly excluding semantic queries and by giving concrete examples like 'all ACL 2024 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?

It gives an explicit when-to-use: 'USE THIS to list papers when you know the filters but have no search text' and provides examples. The 'no semantic query' phrase implies that for search text, one should use a different tool (search_papers). This is nearly as clear as naming the alternative.

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