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

The annotations already declare readOnlyHint=true and idempotentHint=true, and the closing sentence merely restates those facts, earning no extra credit. The description does add behavioral value by disclosing the taxonomy's style (IFRS/SASB) and that results are grouped by sector, which helps the agent anticipate the shape of the output. It stops short of richer context such as whether the list is complete or filtered.

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, each front-loaded with the key fact: what it lists, when to use it, and its safety profile. 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 zero-parameter, read-only listing tool with an output schema in place, the description covers everything an agent needs: identity of the taxonomy, intended use for discovery and tagging, and grouping structure. No return-value explanation is required since the output schema handles that.

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. There is no parameter syntax or format to document, and the description correctly adds nothing spurious on this front.

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 the ESG Hub industry taxonomy') and adds scope detail (IFRS/SASB-style, grouped by sector). This is clearly distinguishable from siblings like list_frameworks or list_esg_resources, which handle different taxonomies entirely.

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?

Explicitly states the use case: 'Use to discover valid industry values for tagging and filtering.' That gives the agent a clear trigger, but it names no alternatives or when-not-to-use conditions (e.g., when to use it vs. get_esg_metadata).

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