list_reference

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

With no annotations, the description carries the burden and largely does: it discloses that every entry's id and name are returned, that custom_field lookups are project scoped with project_id defaulting to TESTOPS_PROJECT_ID, and that tag is a flat un-paginated list where query applies. It omits pagination behavior for the paginated kinds (page/size semantics, page-size limits, ordering) and does not explicitly say the call is read-only.

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 front-loaded with purpose, then per-kind scoping notes, with no filler. Some phrasing is slightly compressed/ambiguous ('they are what create_test_case wants in ...', 'so query is applied here'), costing clarity a little, but nothing is extraneous.

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 five-parameter read tool with an output schema (so return structure need not be described) and no annotations, the description covers discoverability, cross-tool usage, project scoping, and query behavior. The remaining gap is pagination for page/size, which an agent would have to guess at for non-tag kinds.

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 description coverage is 0%, so the description must supply parameter meaning. It does for kind (four enumerated values), query (applied for custom_field and tag), and project_id (defaults to TESTOPS_PROJECT_ID) — but page and size are never mentioned, leaving two of five parameters with no documented meaning anywhere.

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 first sentence names a specific verb and resource ('List a reference dictionary') and enumerates the four valid kinds, so the agent knows exactly what domain of data comes back. It also ties the output back to concrete consumers ('what create_test_case wants in workflow_id, test_layer_id and custom_fields_json'), which distinguishes it from generic listers like list_projects or list_statuses.

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 gives a clear use case — fetch ids/names to feed create_test_case — and explains per-kind behavior differences (custom_field is project scoped, tag has no pagination so query is applied). It does not state when this tool is the wrong choice, e.g. use list_statuses/list_projects instead, so it stops short of full when/when-not guidance.

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