profiles_inspect

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

No annotations provided, so the description carries the full burden. It explains that the tool returns data (stats, summaries, full profile) with no indication of side effects, making its read-only nature clear. No destructive behavior mentioned, which is appropriate.

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 well-structured with clear sections, front-loading the overall purpose then detailing arguments. It is reasonably concise without being overly verbose.

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 5 parameters and no output schema, the description explains the return format (dict with stats/profiles/profile+evidence) and covers all arguments. It lacks details on pagination or sorting, but for a local inspection tool this is sufficient.

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 0%, but the description details all 5 parameters with their effects (partial name match, filter by institution, etc.), adding meaning beyond the bare schema types and defaults.

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: inspect the local professor profiles database. It distinguishes three modes (stats, filtered summaries, full profile with evidence) which differentiates it from sibling tools like find_professors or get_professor_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 clear guidance on when to use each parameter: no arguments for stats, filters for summaries, openalex_id for full profile. It does not explicitly contrast with siblings, but the context of alternatives is present.

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