Co-Author Graph

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

Annotations already indicate readOnlyHint and destructiveHint, but the description adds important behavioral details: returns specific edge fields, default window_years=10, result capped at 500 edges sorted by papers_count DESC. There is 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 concise (two sentences), front-loads the purpose before details, and contains no unnecessary words. Every sentence adds value.

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 that the output schema exists (covering return fields), the description adequately explains the purpose, parameters, behavioral constraints, and use cases. No gaps are present.

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 baseline is 3. The description goes beyond schema by advising to 'Get author IDs via the find_author tool' for author_ids, and clarifying the window_years' default and maximum values, which adds practical context.

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 purpose: 'Find the co-authorship neighborhood of one or more authors.' It specifies the action ('find') and resource ('co-authorship neighborhood'), and distinguishes from sibling tools like 'find_author' and 'search_papers' by focusing on relationships between authors.

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 use cases: 'AC reviewer triage, disambiguating researchers, expanding an author seed.' While it doesn't explicitly state when not to use the tool, the given contexts are clear and helpful for an AI agent to decide when to invoke this tool.

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