rpys

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

With no annotations, the description carries the full burden and does well: it discloses side effects (writes a CSV and PNG), the cost model (one reference request per paper), caching behavior, cache sharing with citation_network, and OpenAlex batching of 50. It omits permission/error behavior, but the resource and mutation profile is unusually well covered.

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?

It is a single dense paragraph, but it is front-loaded with the method and purpose before cost/side-effect details, and every sentence carries information. Slightly run-on, but no 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 9-parameter analytical tool with no output schema and no annotations, the description covers method, inputs, outputs (CSV/PNG), cost, and source handling adequately. It could say more about failure modes or what the returned job/report object contains, but nothing essential to calling it correctly is missing.

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 baseline is 3; the description still adds value by clarifying what ids should be (a set of papers, e.g. confirmed citers) and by noting the OpenAlex batch-of-50 fetch behavior tied to source. Most other parameter meaning is already in the schema.

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 names a specific technique (Reference Publication Year Spectroscopy), states the exact algorithm (count cited references by year, subtract five-year median, report peak years with top cited works), and frames the output as the set's historical roots. This is clearly distinguishable from siblings like citation_lineage or bibliographic_coupling.

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 tells the agent what to feed it (ids, a query, or a corpus) and gives a concrete sourcing example ('the confirmed citers from resolve_citers'). However, it never explicitly states when to prefer rpys over alternatives such as historiograph or citation_network, so routing is left partly to inference.

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