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

Annotations only provide hints (readOnly=false, destructive=true, idempotent=false), so the description carries the burden and adds significant context: billing behavior (0.5 credit per returned post, free misses, 1-credit base for author/company scope), deterministic literal-v1 relevance filtering, and per-platform status. This goes well beyond the annotations, though it does not explain the 'destructive' hint or output details.

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 two sentences with the core purpose front-loaded. Billing details are relevant but include jargon like 'deterministic literal-v1 relevance' and 'when enabled' that could be tightened. Still, no wasted sentences.

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 tool with 7 parameters and no output schema, the description covers search scope and cost but leaves gaps: no return value shape beyond 'per-platform status', no guidance on limit/within_days/platforms, and vague platform enablement. Functional but not fully complete.

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 only 29% schema description coverage, the description must compensate. It explains the high-level query modes (query, author, company_domain) and cost implications, but does not clarify limit, platforms, within_days, or the author sub-fields beyond what the schema already provides. Partial compensation, not complete.

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 states a specific verb and resource: 'Search relevant public social posts' by three distinct modes (keyword, author profile/handle, LinkedIn company domain). This clearly differentiates find_posts from sibling lead/company/intent tools, even without naming them, since the resource and action are unambiguous.

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 gives clear usage contexts: keyword search, known author profile/handle, or LinkedIn company domain, and lists supported platforms. It does not explicitly name alternative tools or state when not to use this tool, but the context is strong enough that an agent can infer when find_posts is appropriate.

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