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

With no annotations, the description carries the full burden and largely succeeds: it discloses the underlying data source and population (active remote-job corpus, Indonesia-reachable), and explains tiered access behavior — unprivileged keys get top rows plus `free_layer: true` and a `paid_depth_url`. Rate limits and auth mechanics are not covered, keeping it below a 5.

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?

Three short sentences, front-loaded with the purpose before the endpoint mapping and tier behavior. No filler, though the endpoint reference and the tier sentence could be tighter.

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 single optional-parameter read tool with no output schema or annotations, the description covers the data population and the paid/free response variation, which are the main things an agent needs. It stops short of describing the row fields (skill name, mention count) beyond the two flags.

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% and `top_n` is documented there with its 1–100 range and default of 25, so the schema does the heavy lifting. The description adds no meaning about how top_n interacts with the free-layer truncation, which would have been the valuable addition.

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 specifically that this returns top in-demand skills by mention count, scoped to an active remote-job corpus filtered for Indonesia-reachable postings. That is enough to distinguish it from job-search siblings like search_jobs or talent_search, though it never uses an explicit verb like 'list' or 'returns'.

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 conveys the domain of use (market demand statistics) and cross-references the equivalent REST endpoint, which helps an agent recognize the data shape. But it never says when to prefer this over the sibling market/recruiting tools, nor any exclusions or prerequisites.

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