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

With no annotations, the description carries the full burden, and it does disclose one meaningful trait: results are computed over only the latest 200 'visible' leads, so the agent knows the sample is bounded and permission-filtered. It omits auth requirements, whether the window is time-based, and what the aggregate response actually contains.

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?

A single front-loaded sentence with no filler. It is efficient, though so terse that there is no structure beyond the one clause to hang scope or parameter behavior on.

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 annotations, no output schema, and an undocumented parameter, the description leaves key gaps: default behavior when `type` is omitted, whether the 200-lead window is fixed or time-bounded, and the shape of the returned analytics. For a schema-less-output tool this is under-specified.

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 description coverage is 0%, and the description never mentions the single `type` parameter or its job/gig enum. The enum values are fairly self-explanatory, but the description adds no semantics — crucially, it does not say what happens when `type` is omitted (both categories? a default?).

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 names the concrete outputs — top requested skills and median budget — over a defined dataset (latest 200 visible leads), which is far more specific than the tool name alone. It implicitly distinguishes itself from get_lead_details and search_leads by being an aggregate view, though it never names those siblings explicitly.

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?

There is no explicit statement of when to use this versus search_leads or get_lead_details, nor any prerequisites. Usage is only implied by the aggregate nature of the output (market-level stats rather than per-lead data).

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