cuemap_intent_classify

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

With no annotations, the description carries the burden of behavioral disclosure. It adds a useful caveat that 'scores are ranking signals, not calibrated probabilities,' which prevents misinterpretation of the output, but it does not disclose side effects, local-processing implications, or any limits that might affect invocation.

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 concise sentences, with the core action front-loaded and the important score-interpretation caveat placed second. Every word earns its place and there is no redundant filler.

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?

There is no output schema and no annotation, so the description is the only source of return-value information. It mentions 'recall/memory eligibility signals' but does not explain the shape of the response, how scores map to eligibility, or how the 'target' parameter changes the behavior, leaving an agent under-informed for a classification tool.

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 67%, so two of three parameters already have descriptions. The tool description adds context around 'recall/memory eligibility signals' which helps clarify the 'target' enum, but it does not describe the text, target, or project parameters directly or add format-level meaning beyond the schema.

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 description states a specific action ('Classify text with CueMap's local intent model') and a clear deliverable ('return recall/memory eligibility signals'). It distinguishes the tool as an intent-classification step rather than a storage or retrieval operation, though it does not explicitly name any sibling it is not.

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 or when-not-to-use guidance is provided. The description does not compare this tool to sibling tools such as cuemap_recall, cuemap_memory_get, or the ingest tools, leaving the agent to infer when classification is the appropriate step.

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