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scitex-ai

crossref-local

by scitex-ai

search_by_doi

Fetch full metadata for a scholarly work by DOI. Generate formatted citations or save results as JSON, BibTeX, or text file.

Instructions

Get detailed information about a work by DOI.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
doiYesDigital Object Identifier (e.g., "10.1038/nature12373")
save_pathNoOptional file path to save result (e.g., "paper.json", "paper.bib")
as_citationNoReturn formatted citation instead of full metadata
save_formatNoOutput format for save_path: "text", "json", or "bibtex" (default: "json")json

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states only that the tool 'Get detailed information' but does not disclose what 'detailed information' includes, whether the operation is read-only, any rate limits, or what happens with non-existent DOIs. The description is too minimal to set expectations about side effects or response characteristics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that conveys the core purpose without any waste. It is front-loaded and easy to parse, which is ideal for an AI agent scanning tool descriptions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 4 parameters and an output schema, and the description is a minimal one-liner. While it clearly states the core function, it does not explain the optional parameters' purpose or the relationship to sibling tools. However, because the schema covers parameters and the output schema exists, the description is minimally viable for a simple lookup tool. More context about caveats or alternatives would elevate completeness.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema provides detailed descriptions for all four parameters (doi, save_path, as_citation, save_format), with 100% coverage. The description itself adds no parameter-level detail, but since the schema already documents each parameter clearly, the baseline of 3 is appropriate. The description does not need to repeat schema information.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: 'Get detailed information about a work by DOI.' It uses a specific verb ('Get') and a resource ('a work by DOI'), distinguishing it from sibling tools like search_works (which likely searches by query) and enrich_dois (which likely enriches a list of DOIs). This is a clear, non-tautological statement of purpose.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or scenarios where another sibling tool would be preferred. Given the sibling tools include search_works, enrich_dois, and cache-related tools, the lack of usage context leaves the agent to infer when this tool is appropriate.

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

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