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Open a case

case_open

Starts a complaint case in the local log with company, issue, and summary, plus optional account, amount, state, and desired outcome details for tracking escalation.

Instructions

Start a case in the local log. account_hint is at most the last 4 digits. Never store passwords, full card numbers or SSNs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "company": "<company>",
      "issue": "<issue>",
      "summary": "<summary>"
    },
    "name": "case_open"
  }
}

Input Schema

NameRequiredDescriptionDefault
issueYes
stateNo
amountNo
companyYes
summaryYes
account_hintNo
desired_outcomeNo

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

B3/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=false, destructiveHint=false and openWorldHint=false, so the write/scope profile is covered. The description still adds real value by stating that records go to the local log and by imposing a data-handling rule (never store passwords, full card numbers or SSNs), but says nothing about duplicate cases, required review, or what happens to the record afterward.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short clauses, front-loaded with the action and followed by a parameter constraint and a compliance rule; no filler sentences. The brevity is close to under-specification, but nothing written is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a non-destructive mutation tool with 7 undocumented parameters, the definition covers only purpose, one parameter rule and one data-safety policy. The existing output schema reduces the need to explain return values, but the gap on required-field semantics (especially summary versus issue) leaves the agent guessing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0% across 7 parameters, so the description carries the full burden and only compensates for one of them, account_hint ("at most the last 4 digits"). The required fields company, issue and summary plus state, amount and desired_outcome remain undefined in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

"Start a case in the local log" gives a specific verb plus resource and clarifies that storage is local rather than remote, which separates it from case_get, case_close and case_list. It stops short of explicitly naming any sibling for contrast, but the operation is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description never states when to open a case versus using case_log, bill_record or other record-creating siblings, nor what prerequisites exist. Usage is only implied by the verb "start", leaving the agent to infer the correct entry point.

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