fetch_paper_text

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

With no annotations provided, the description carries the full behavioral burden. It discloses 'best-effort' semantics (implying possible partial/failed text retrieval), the arXiv-only constraint for the html preference, and the section normalization behavior. However, it does not disclose what happens when html is requested for non-arXiv papers (fallback behavior) or how failures surface to the caller.

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?

Roughly 60 words with the core purpose front-loaded in the first sentence. Each subsequent sentence explains the prefer values and the canonical section names without waste. It is appropriately tight, though slightly terse.

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?

An output schema exists, so return values are partially covered there. The description discloses section-normalization output behavior. But the undefined 'input_str' format is a critical gap: an agent cannot reliably invoke the tool without knowing what identifier to pass. The failure/fallback semantics of 'best-effort' and non-arXiv html requests are also unspecified. For a 2-param tool at 0% schema coverage, the description needed to compensate and did not.

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 define both parameters. 'prefer' is explained thoroughly (auto/html/pdf values, default, and the html constraint), but 'input_str' — the single required parameter — is never explained. An agent has no idea whether it expects an arXiv ID, DOI, or URL. This is the most critical parameter for calling the tool and is left undefined.

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 opens with a specific verb+resource: 'Return best-effort full text + section split for a paper.' This clearly distinguishes it from siblings like get_paper_metadata (metadata only) and summarize_paper (summary), making it easy for an agent to know this tool retrieves the raw full text with section boundaries.

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 purpose implicitly signals when to use this tool (need full text + sections, not metadata or analysis), but there is no explicit when-to-use or when-not-to-use guidance, and no alternative tools are named. The agent must infer the selection logic from the name and description alone.

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