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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description adds useful context beyond that by disclosing the return contents (ids, link, snippet, code languages, citation), which matters because there is no output schema. It does not describe ranking or scoring behavior.

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?

Two sentences, front-loaded with the purpose followed by the return shape. The long parenthetical topic list is dense but earns its place by telling the agent what content is matchable; nothing else is wasteful.

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?

With no output schema, the description compensates by stating what a result contains, and it covers the searchable corpus. Combined with the fully documented schema, an agent has what it needs; only the ranking behavior and the absence of sibling routing leave minor gaps.

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 100%, so all four parameters (query, source, language, limit) are already documented in the schema. The description adds no syntax, format, or behavior detail for them, so the baseline 3 applies.

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 gives a specific verb (search) and resource (sections of textbooks and an R package on research methods), and enumerates the covered domains so an agent knows the corpus scope. It does not explicitly contrast with siblings like get_code or fetch, but the retrieval-of-sections scope is unambiguous.

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?

Usage is implied rather than stated: it reads as the discovery entry point for the library, but there is no explicit when-to-use/when-not guidance or routing to alternatives such as choose_method, cite, get_code, or list_sources. An agent can infer its role but must decide on its own when a direct fetch or code lookup is preferable.

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