pubmed_extract_info

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

Annotations already declare readOnlyHint, openWorldHint, and idempotentHint, covering safety and side-effect expectations. The description adds context about token efficiency and the targeted nature of extraction, but does not disclose return format or further behavioral details. This is adequate but not rich beyond 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?

Two sentences, front-loaded with purpose, then usage guidance. No filler or redundancy. Every sentence contributes meaning.

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 the moderate complexity (2 params, no output schema, read-only), the description provides enough context: what it extracts, when to use, and how it compares to a sibling. It does not explain return values, but the annotations cover safety and the description conveys the core use case well.

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%: both 'pmid' and 'sections' have descriptive text in the schema. The description mentions examples of sections (authors, abstract, keywords, DOI) which echo the schema enums, adding no new meaning. Baseline 3 is appropriate since the schema handles parameter semantics fully.

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 tool's function: 'Extract specific structured sections from a PubMed article.' It uses a specific verb ('extract') and resource ('sections from a PubMed article'), and differentiates from siblings by noting it is for partial data rather than the full record, explicitly contrasting with get_details.

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 provides explicit guidance on when to use: 'Use when you need only certain aspects… rather than the full record.' It also names the alternative (get_details) and highlights token efficiency. It does not explicitly state when not to use, but the 'when' scenario is clear enough.

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