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

Annotations already declare readOnly, idempotent, closed-world and non-destructive, so the safety profile is covered. The description adds one genuinely useful disclosure beyond that: the payload is names only with no SEO HTML, which implies sibling tools do return such markup. It says nothing else about behavior such as ordering or payload size, so the added value is real but thin.

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 what the tool returns, then scope, then the alternative. The fragment "Names only; no SEO HTML." is terse but each clause carries information.

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 parameters, an output schema present, and full annotation coverage, the description only needs to say what the list contains and how it differs from list_taxonomies — both of which it does. An agent can call it correctly from this definition alone.

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 tool takes zero parameters, so the baseline is 4. The description still earns its keep by naming the parameter it feeds (function_id) and giving example values, which helps the agent interpret results correctly.

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 ("List LexGO job function names") with concrete example values, and marks the output scope ("Names only"). It also distinguishes itself from list_taxonomies, so an agent can tell the two list tools apart without opening either schema.

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 a clear use case — "for use as function_id filters" — which tells the agent when to reach for this tool. It also redirects to list_taxonomies for the full vocabulary, though it never states an explicit exclusion or precondition for this tool versus that one.

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