WHEN: checking server status, loaded D365 version, or custom model path. Triggers: 'status', 'statut', 'is the server ready', 'how many chunks', 'index loaded'. Returns JSON with: status, indexed chunk count, loaded version, custom model path.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "result": {
+ "type": "string"
+ }
+ },
+ "required": [
+ "result"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover read-only, idempotent, and non-destructive behavior, so the description's main contribution is the return contract: JSON with status, chunk count, version, and model path. This adds useful behavioral context without contradicting the annotations.
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 compact and front-loaded with the most important 'WHEN' information, followed by triggers and return fields. Every sentence earns its place with no filler or redundancy.
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?
With zero parameters, an output schema present, and annotations declaring the tool safe and idempotent, the description provides everything an agent needs to invoke it correctly. It even lists the expected JSON response fields.
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?
The tool has zero parameters, so the description is not required to explain parameter semantics. The baseline of 4 applies because there are no parameter gaps for an agent to resolve.
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 clearly states the tool checks server status, loaded D365 version, and custom model path, which is a specific purpose. It does not explicitly differentiate itself from sibling tools, but the healthcheck intent is unambiguous.
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 provides explicit when-to-use conditions and concrete trigger phrases like 'status', 'statut', and 'is the server ready'. It does not mention when not to use it or name alternatives, but the usage context is clearly communicated.
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.