Ai Suggest Field Mappings

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

With no annotations, the description carries the full behavioral burden and fails: it does not disclose that the operation is read-only/advisory, that it is non-deterministic or incurs model cost/latency, or whether suggestions are persisted. 'Using AI' is the only behavioral hint and it is too thin.

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?

A single short sentence with no padding, so it is not verbose, but it is under-specified rather than genuinely concise. It is front-loaded with the action, which is the only structural merit.

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?

An output schema exists so return values need not be described, but the description omits any behavioral or parameter context for a 2-required-parameter AI tool with zero annotation coverage. An agent would be guessing at how 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?

Both parameters (source_fields, target_bundle) have 0% schema description coverage, and the description adds nothing about their format, expected values, or relationship. 'target_bundle' in particular is opaque without documentation.

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 verb+resource pair ('Suggest field mappings') states the basic action, but 'using AI' is filler rather than scope. It does not distinguish this tool from the sibling map_fields_ai, nor does it say what kind of mappings (Drupal field config? migration mappings?) are suggested.

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?

There is no when-to-use guidance, no prerequisite (e.g., a migration or content model must exist first), and no mention of alternatives such as map_fields_ai. The agent must infer everything about invocation context.

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