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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds valuable behavioral context beyond annotations: it warns that draft editorialStatus entries are unreviewed model drafts and instructs the agent to disclose this when quoting. This is meaningful additional transparency.

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 compact and front-loaded: it states the purpose first, then describes output contents, then flags draft-status behavior and downstream usage. Every sentence earns its place with no 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 read-only listing tool with one fully documented parameter and an output schema, the description is complete. It covers what is returned, important quality caveats, and how to proceed with a result, leaving no critical gap for an agent to call it correctly.

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 the schema already defines 'subject' as a subject head concept id with an example. The description repeats the 'subject head' concept but does not add new parameter semantics beyond the schema, so the baseline of 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?

The description clearly states a specific verb (list) and resource (curated obligation topics under a subject head), and distinguishes itself from the related get_topic by noting that results should be fed into get_topic. This is more than a restatement of the title and gives an agent a precise idea of what the tool 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?

It gives clear context for when to use the tool: to get curated topics under a subject head with orientation and anchor counts. It also implies the follow-up action (feed conceptId to get_topic), though it does not explicitly list when-not-to-use scenarios or alternative listing tools.

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