search_scihub

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

With no annotations, the description carries the full behavioral burden and does well: it discloses that the tool is disabled by default, requires opt-in, tries direct mirrors before a bounded ScrapingAnt fallback, and grants no access rights. It omits details like what happens when disabled or what the return payload is, but the key safety-relevant traits are present.

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?

One dense sentence carries the operation, constraints, fallback order, and a legal/access caveat with no filler. The most important facts (opt-in, disabled, DOI-only) are front-loaded.

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 tool with no output schema, the description explains input restrictions and behavioral fallback well. The main gaps are how someone enables the opt-in, what happens when disabled, and whether the tool returns a match or only a saved PDF.

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 schema already documents doiOrUrl, savePath, and downloadPdf. The description adds no parameter-level meaning beyond restating the DOI-only constraint, which 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 identifies this as a 'Sci-Hub DOI adapter' and sharply constrains its input to DOI/doi.org URLs, which distinguishes it from sibling search tools. However, it never states an explicit operation verb such as search, fetch, or download, relying on the tool name and schema to convey what it returns.

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 gives clear input constraints and hints at an opt-in workflow, but it does not compare this tool to siblings such as get_paper_by_doi or discover_paper_access, nor does it say when to choose it over them. Usage is mostly implied: use it when you have a DOI and want Sci-Hub access.

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