Parse unstructured insurance claim text into structured JSON: claim number, type, policy holder, incident, amounts, status, adjuster, next actions, risk flags.
Scored across 1 tool
There is only one tool, so there is no possibility of ambiguity or misselection among tools.
The single tool name 'parse_claim' follows a clear verb_noun pattern, which is consistent and readable.
With only one tool, the count is borderline thin for a server named 'Insurance Claim Parser'; while it matches the narrow purpose, additional tools for validation or enrichment could be expected.
The tool only parses claims into structured JSON, with no operations for creating, retrieving, updating, deleting, or otherwise managing claims, leaving significant gaps for a claims processing domain.
Parse unstructured insurance claim text (email, form, notes) into structured JSON: claim number, type, policy holder, incident, amounts, status, adjuster, next actions, risk flags. Useful for insurers, brokers, claims processing.
| Name | Required | Description | Default |
|---|---|---|---|
| claim_text | Yes | Raw claim text (email, form, notes) | |
| claim_type | No | Claim type hint: auto, home, life, health, property, liability, workers_comp |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It does disclose the output shape (claim number, type, policy holder, incident, amounts, status, adjuster, next actions, risk flags), which is real value given there is no output schema, but it says nothing about permissions/auth, rate limits, failure modes, or how malformed or non-claim text is handled.
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 sentences, front-loaded with the action and the output field inventory; nothing is buried. The trailing audience clause ('useful for insurers, brokers, claims processing') is filler that does not earn its place, keeping this short of a 5.
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?
For a low-complexity, two-parameter (one required), flat tool with no output schema and no annotations, the description covers the essential contract: input sources and the resulting structured fields. It stops short of covering edge-case behavior such as unparseable input, which leaves a modest gap.
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 both parameters are already documented; the baseline is 3. The description reinforces the sources of claim_text (email, form, notes) but never mentions the claim_type hint parameter or its allowed values, so it adds no 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?
States a specific verb (parse) plus the exact resource (unstructured insurance claim text from email/form/notes) and the target format (structured JSON) with an enumerated field list. An agent immediately knows what goes in and what comes out; there are no siblings to disambiguate against.
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 only usage signal is an audience list ('useful for insurers, brokers, claims processing'), which is marketing rather than guidance. There is no when-to-use, when-not-to-use, prerequisite, or alternative-tool advice, so the agent must infer the trigger condition itself.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
parse_claim
Add one secure layer between your agents and this server.