academic_search

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

Annotations already declare readOnlyHint=true and destructiveHint=false; the description adds substantial behavioral context beyond this: natural language input, result composition, recovery hints on no matches, 1-hour cache freshness, provider selection nuances (especially scholarapi being paid/full-text and only explicitly requested), and the response-time impact of full_text. No contradiction with annotations.

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?

The description is compact yet information-dense, front-loaded with the core purpose, then flows into result details, usage guidance, and behavioral notes. Every sentence adds distinct value, with no redundancy or 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?

Given output schema exists and annotations cover safety, the description provides enough context for effective invocation: result fields, pairing with scrape_page, recovery hints, freshness, provider nuances, and filtering. It addresses both what to expect and operational caveats, making it complete for a search tool of this complexity.

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 baseline is 3. The description adds value above the schema by explaining provider selection behavior (automatic vs forced, scholarapi paid/full-text only when explicit), the no-syntax-needed aspect, and general narrowing capabilities (year, source, access type) that map to parameters. This extra context elevates it to a 4.

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 clearly states the verb ('Search') and resource ('peer-reviewed papers and scholarly literature'), and differentiates from siblings by explicitly naming web_search for non-academic content and news_search for current events. The mention of pairing with scrape_page for full text distinguishes its role in the tool ecosystem.

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?

Explicitly provides use cases ('literature reviews, prior-art research, and finding citations') and exclusions ('use web_search for non-academic content or news_search for current events'). Also notes filtering options and provider caveats, giving clear guidance on when to use rather than alternatives.

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