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

No annotations are provided, so the description carries the full burden and does so well: it explains the no-keyword-filter design, that zero drafts is a valid outcome not an error, that unresolved_companies should be surfaced, that n is capped by the user's daily cap, and that the model judges topical relevance. It also specifies the required post-call behavior of displaying every draft in full.

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?

Front-loaded with purpose then a clear USE/DO NOT USE structure. The long output-format template and follow-up instructions are useful but make it longer than a typical tool description; still, nearly every sentence serves a distinct behavioral or routing purpose.

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?

Complete for a multi-parameter pipeline tool with no annotations and no output schema. It covers routing, parameter semantics, failure modes, empty-result handling, caps, and required post-call display behavior, leaving little an agent would need to infer.

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 Args section documents all three parameters: companies with a max of 5, n with default 3 and daily-cap behavior, and date_posted with the allowed values and default. This adds essential meaning beyond the bare schema, which has no descriptions or enums.

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: generate LinkedIn comment drafts on recent posts by employees of named companies. It explicitly distinguishes from the sibling run_commenting_pipeline by explaining this tool searches by AUTHOR COMPANY and recency, not keywords.

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?

Gives explicit trigger examples ('comment on posts from people at Stripe') and an explicit DO NOT USE case with examples, naming run_commenting_pipeline as the alternative for topic/keyword commenting. Also states not to approve or schedule unless asked.

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