get_case_messagesRead the chat conversation on a case between you and the collection partner handling it. Each message includes: senderName, role (Creditor / Partner / Managed by partner), sentAt (UTC), message. See the debitura://glossary/chat-roles resource for what each role means.
| Name | Required | Description | Default |
|---|---|---|---|
| caseId | Yes | Debitura case ID (GUID) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds context about the conversation parties, message fields, and a glossary reference, enhancing transparency.
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, no wasted words. First sentence states purpose, second lists message fields and provides a helpful link to a glossary.
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 simple read tool with one parameter and no output schema, the description compensates by listing message fields and referencing roles, but could optionally mention pagination or limits.
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 100% with 'caseId' described adequately. The description does not add additional parameter-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 uses 'Read the chat conversation' as a specific verb+resource, clearly distinguishing it from write tools like 'send_case_message' and other case-related tools.
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 states when to use ('to read chat conversation') but does not explicitly mention when not to use or alternatives, though sibling tools make this clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a clearly distinct resource and action: case vs. tasks vs. files vs. messages vs. payments vs. account summary. The get_case_* family is broken out by specific sub-resource (activity, contract status, messages, payments, tasks), and preview_case is explicitly distinguished from create_case. list_tasks vs. get_case_tasks are scoped differently and the descriptions call out the difference.
All tool names follow a consistent lowercase verb_noun pattern: create_, get_, list_, send_, upload_, preview_, ping. Even the standalone 'ping' is a common health-check convention and does not break the pattern. No camelCase or mixed verb styles appear.
At 16 tools, the server is slightly above the typical 3-15 well-scoped range, but the breadth of the domain (case lifecycle, tasks, files, messages, payments, team management) justifies each tool. The count feels reasonable rather than bloated, earning a 4 rather than a 5.
The core workflow is well covered: preview, create, monitor (list/get, activity, payments, messages, contract status, files, tasks), communicate, and attach files. Missing operations like update_case, delete_case, or explicit task resolution are gaps, but they are often not needed in this domain since tasks auto-resolve and the partner drives legal processes. Overall, the surface is complete enough for typical agent workflows.