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

Annotations already mark the call as readOnly, idempotent, and non-destructive; the description adds meaningful behavioral detail beyond that: default include_superseded behavior, why merged rows are hidden to avoid duplicate ids, and the returned row shape plus cursor pagination. There is no contradiction with annotations.

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 front-loads the purpose and then uses short labeled sections for use conditions, exclusions, args, and returns. Every line earns its place with no filler or repetition.

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?

Even without an output schema, the RETURNS line supplies the full result field set and describes cursor pagination. Combined with explicit sibling routing and annotation-covered safety, there is no missing context needed to invoke this tool 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%, so the baseline is 3. The ARGS section adds non-redundant guidance by recommending core/proven maturity when building and explaining the duplicate-prevention rationale for include_superseded. It still largely mirrors schema descriptions, so it stops short of a 5.

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 opening sentence uses a specific verb 'List' and a precise object, the workspace Field Registry, and enumerates what each entry contains (stable id, maturity, data type, synonyms, occurrence count). It also distinguishes itself by naming siblings it is not (talonic_search, talonic_filter) and providing use cases for related get_field/field_values tools.

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 USE WHEN block gives concrete scenarios: knowing what data exists before querying it, picking a concept, or needing an exact field id for talonic_get_field / talonic_field_values. The NOT FOR section explicitly points to talonic_search and talonic_filter, so an agent can quickly route among siblings.

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