list_available_fields

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

No annotations exist, so the description carries the full burden. It does disclose the result shape ('fields' nested name list plus an additive 'units' dict) and that the change is backward-compatible, which is real behavioral context. However, it says nothing about read-only safety, rate limits, or caching, and a large share of its behavioral text is version-scoped changelog material rather than invocation-relevant behavior.

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 first two sentences are tight, front-loaded, and exactly what an agent needs. The following paragraph is over half the definition and is largely internal engineering notes ('v1.7.1.6', 'mcp_context.py's _resolve_context_bundle()', 'FIELD_UNITS in mcp_field_registry.py') that consume space without helping selection or invocation.

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 output schema, the description takes on the job of explaining the return shape and does so (nested {domain:{source:[...]}} plus a flat {field:unit} map). Purpose, usage trigger, and the lone parameter are all covered, so an agent can call this correctly; only the exhaustive domain list is missing.

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 0% and the single 'domain' param is undocumented in the schema, so the description must compensate. It does: null/omitted yields a full overview, and it supplies three concrete narrowing values ('health', 'context', 'fit'). It stops short of enumerating the complete valid domain set, so the agent must still infer whether other values are legal.

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 states a specific verb+resource ('List all queryable fields') plus its organization ('grouped by domain and source'). It implicitly distinguishes itself from the query_* siblings by being the metadata/introspection call, but it never names an alternative, so it stops short of a clean 5.

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?

'Use this first if the set of available fields is unknown' gives an explicit triggering condition, and the follow-up tells the agent how to call it (omit domain for a full overview, pass health/context/fit to narrow). There is no statement of when NOT to use it or which sibling to prefer once fields are known.

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