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search_scihub

Search Sci-Hub for academic papers using DOI, title, or keywords to access research articles and check availability.

Instructions

Search Sci-Hub for papers by DOI, title, or keyword. Use search_type='doi', 'title', or 'keyword'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
search_typeNodoi
limitNo
check_availabilityNo
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the search functionality but doesn't describe what the tool returns (e.g., list of papers, metadata, links), whether it's read-only or has side effects, any rate limits, authentication needs, or error handling. For a search tool with zero annotation coverage, this leaves significant behavioral gaps.

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 extremely concise and front-loaded: one sentence states the purpose, and a second provides key usage guidance. Every word earns its place with no redundancy or fluff, making it easy to scan and understand quickly.

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

Completeness2/5

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

Given the tool's moderate complexity (4 parameters, no annotations, no output schema), the description is incomplete. It covers the basic purpose and search types but lacks details on return values, error conditions, behavioral traits, and full parameter semantics. Without an output schema, the description should explain what results to expect, but it doesn't, leaving the agent uncertain about the tool's output.

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

Parameters2/5

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 for undocumented parameters. It explains 'search_type' with its three values, adding meaning beyond the schema. However, it doesn't address 'query' (what format for each type?), 'limit' (what it controls), or 'check_availability' (what this means). With 4 parameters total, this partial coverage is insufficient to compensate for the low schema coverage.

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Search Sci-Hub for papers by DOI, title, or keyword.' This specifies the action (search), target resource (papers on Sci-Hub), and search methods. It distinguishes from obvious siblings like 'download_scihub_paper' (which retrieves content) but doesn't explicitly differentiate from 'search_libgen' or 'search_literature' which might have overlapping domains.

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

Usage Guidelines3/5

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

The description provides some usage guidance by listing the three search types ('doi', 'title', 'keyword') and suggesting to 'Use search_type='doi', 'title', or 'keyword'.' However, it doesn't explain when to choose one type over another, when to use this tool versus alternatives like 'search_libgen' or 'search_literature', or any prerequisites. This implies usage but lacks explicit context or exclusions.

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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