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, yet the description adds genuine behavioral detail: corpus size, AI-generated transcripts, and that transcript-only hits are flagged via matched_in:'transcript' with a transcript_snippet. That return-shape disclosure is useful in the absence of an output schema; it only lacks pagination/ordering semantics.

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?

Three sentences, front-loaded with the verb+resource and scope before the alternative-tool routing. Dense but each clause carries information; the parenthetical example of the series title is slightly decorative but harmless.

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 explaining the matched_in/transcript_snippet hit annotation and how hits are surfaced; all seven parameters are optional and mostly self-documented. What is left unspecified (ordering, pagination behavior beyond limit/offset) is minor for a search tool.

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 86%, so the baseline is 3, and the description adds the cross-parameter semantics the schema cannot express: filters are optional and AND-combined, and the keyword parameter reaches into the transcript rather than just title/abstract. That last point is a meaningful clarification of keyword behavior.

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?

States a specific verb and resource ('Search the cluster's podcast episodes') and goes further by explaining the scope of the search (reaching into AI-generated transcripts) and the size of the corpus (~43 episodes). It also names the sibling get_podcast and its distinct purpose, so the agent can separate the two without opening a schema.

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?

Explicitly routes single-episode use to get_podcast ('Use get_podcast for one episode's detail and the transcript itself'), which is a clear alternative-and-condition pairing. It also notes filters are optional and AND-combined. It stops short of distinguishing itself from the generic `search` sibling, leaving one inference gap.

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