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

Annotations indicate readOnlyHint and openWorldHint, and the description adds context by mentioning it aggregates from job boards and wraps a specific model. It does not contradict annotations, and explains the transformation (aggregation, keyword detection). While not exhaustive about rate limits or errors, it is sufficient given the annotations.

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 front-loaded with the main purpose, then provides use cases and parameter details. Each sentence adds value with no wasted words.

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 read-only tool with one parameter and no output schema, the description explains the inputs, behavior, and high-level output (aggregated signals, keywords). It could be more precise about the output structure, but it is largely 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?

The description fully covers the single parameter company_slugs with an explanation and example, compensating for the schema's lack of descriptions (0% coverage). It adds meaning beyond the type definition.

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 clearly states the tool detects hiring-momentum signals for a list of companies, specifying what it aggregates (open-role counts, growth keywords, trend indicators). This verb-resource combination is specific and distinguishes it from siblings like search_linkedin_jobs or track_startup_funding.

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?

It provides concrete use cases (sales prospecting, funding signals) but does not explicitly state when not to use this tool or recommend alternatives among siblings. However, the use cases are clear enough to guide selection.

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