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

Beyond the annotations (readOnlyHint, destructiveHint=false, openWorldHint), the description usefully discloses the failure contract ('Returns null with transcriptNotAvailable') and that no AI transcription is involved. However, the cost statements conflict with one another — 'Returned native captions cost 1 credit' and '1 credit per request' versus 'Completed lookups cost at least 10 Nexscope credits' — leaving an agent unable to predict the actual charge for a paid, repeat-billed operation.

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 same paragraph appears twice verbatim, interleaved with pasted marketing boilerplate ('LinkedIn Post Transcript API View Pricing ... 1 credit per request'). The one genuinely useful fact, the transcriptNotAvailable null behavior, is buried mid-block, and the duplication makes the block roughly twice as long as needed.

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 tool with a clear safety annotation profile, the description covers the essentials: what is fetched, the empty-result sentinel, and the billing model. The missing pieces are a stated shape of the returned transcript (no output schema exists) and a resolved cost figure, but neither blocks a correct call.

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?

There is a single parameter with 100% schema description coverage, so the schema already tells the agent it is the URL of the LinkedIn post. The description adds no format, canonicalization, or accepted-URL-shape detail beyond that, which is the expected baseline 3 when the schema does the work.

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 gives a specific verb and resource ('Fetches the transcript from a LinkedIn post video'), which clearly separates it from social_linkedin_post and from other transcript tools for Facebook/TikTok/YouTube. It adds the scope qualifier 'when LinkedIn exposes one publicly', but never explicitly names a sibling to route between, so it stops short of a 5.

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?

Usage is only implied: an agent infers it should call this when it needs the spoken content of a LinkedIn video post. There is no explicit when-not guidance and no named alternative (e.g., social_linkedin_post for non-video posts), so the agent must infer the selection boundary from the tool name alone.

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