Classifies car insurance claim severity into AUTO_PROCESS, REVIEW_NEEDED, or URGENT_ESCALATION using a two-model LLM judge for reliable triage.
Classifie la sévérité d'un sinistre automobile en AUTO_PROCESS, REVIEW_NEEDED ou URGENT_ESCALATION. Utilise un LLM-as-judge (Sonnet valide Haiku) pour garantir la fiabilité.
| Name | Required | Description | Default |
|---|---|---|---|
| claimData | Yes | Objet ClaimData retourné par analyze_claim_report |
Changes observed during successful MCP inspections.
v1.0.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions an LLM-as-judge validation process (Sonnet validates Haiku) for reliability, but it does not clarify whether the operation is read-only, whether it has side effects, what permissions are required, latency, cost, or 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?
The description is two concise sentences with no wasted wording. The primary purpose and output categories are front-loaded before the secondary reliability note.
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?
The input schema is rich and fully described, and the description lists the possible output labels. However, with no output schema and no annotations, it does not fully describe the return structure, side effects, or invocation context needed for a complex 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 description coverage is 100%, so the schema already documents the single claimData parameter and its nested fields thoroughly. The description adds no additional parameter semantics beyond the schema baseline, which is appropriate for a 3.
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 verb and resource: classifying the severity of an automobile claim. It also names the exact output categories, making the tool's purpose immediately clear. It does not explicitly distinguish itself from sibling tools such as analyze_claim_report, so it falls short of a 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?
The description explains what the tool does but gives no guidance on when to use it versus analyze_claim_report or generate_broker_notification. There are no prerequisites, exclusions, or contextual triggers for invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.