Map Fields Ai

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the mechanism (reads target bundle fields, then calls the AI provider) and implies a read-only suggestion operation, but it does not state permissions, whether results are persisted, cost/rate implications of an AI call, or any failure 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?

Two tight sentences, front-loaded with the purpose and followed by the mechanism. No filler; every clause earns its place.

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 explained, and the description adequately covers the input meaning and the two-step mechanism. It is only slightly short of complete given the missing sibling differentiation and lack of any annotation coverage for a tool that invokes an external AI provider.

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 100%, so the schema already documents both parameters (source_fields as D7-style field names, target_bundle). The description restates the same inputs without adding format, ordering, or constraint details, so baseline 3 is appropriate.

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 ('Suggest') and resource ('AI-powered field mappings') plus the scope (source field list to target bundle), and adds mechanism detail ('reads the target bundle's available fields'). However, it does not differentiate itself from the near-identical sibling ai_suggest_field_mappings, leaving the agent to guess which to pick.

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?

No when-to-use, when-not-to-use, or alternatives are given. The presence of a highly similar sibling (ai_suggest_field_mappings) makes the absence of routing guidance a real gap, leaving usage only weakly implied by the purpose.

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