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

With no annotations, the description carries the burden. It adds useful provenance ('Computed directly from the database, not an estimate') and scope ('currently published'), but it does not disclose return shape, default behavior, or any edge cases. This is helpful but incomplete for a tool with zero annotation coverage.

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 dense sentence front-loads the resource and enumerates the exact statistics, followed by a short provenance qualifier. No filler or redundancy.

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-optional-parameter read-only stats tool, the description covers the data scope and the dimensions returned. The lack of an output schema and annotations means exact response format is unspecified, but the tool is simple enough that the description is largely sufficient.

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 100%: top_n is fully documented with min/max and default. The description's mention of 'most frequent tools and categories' aligns with top_n but adds no new parameter semantics. Baseline 3 applies.

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?

Description opens with 'Aggregated statistics over currently published Level listings,' a specific resource and operation. It enumerates the exact dimensions (AI level distribution, remote share, top tools/categories), making the tool's purpose unmistakable. It doesn't explicitly contrast with siblings like search_jobs or get_job, so it stops short of full differentiation.

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?

No explicit when-to-use or alternative routing is given. The aggregate scope implies it is for market-level overview rather than individual job lookup, but the description never names search_jobs/get_job as alternatives. This is implied usage, not stated guidance.

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