search_lectures

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

The annotations already establish read-only, idempotent, non-destructive behavior, so the final “Read-only” is redundant. The description nevertheless adds useful context beyond those annotations: the concrete backend service and an authorization requirement, though it gives no further detail about search or failure 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?

The purpose is front-loaded, followed immediately by the alternative tool and access prerequisite in four very short statements. There is almost no waste; only the final read-only statement repeats structured information, without creating meaningful bloat.

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?

For a one-parameter read-only search, the description adequately covers tool selection and the main access prerequisite. However, the undocumented query and absence of an output schema leave searchable fields, result scope, and result shape unclear, so the definition is usable but not fully self-contained.

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?

With 0% schema description coverage, the description needed to explain query, but it never says whether the text matches lecture titles, identifiers, instructors, or other fields. Its general role as lecture-search text is inferable, yet no syntax, matching behavior, or example is supplied.

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?

“Search lectures” gives a specific verb and resource, while the token-service name clarifies the intended backend. The explicit contrast with search_courses for the public catalogue distinguishes it from the most relevant sibling.

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 explicitly routes public-catalogue searches to search_courses rather than leaving that choice to inference. It also states the “lectures right” prerequisite, helping the agent avoid an unauthorized invocation.

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