get_bookingRead a booking using its private manage-link token. Includes meeting-link synchronization status. Treat this token as a password; do not share it publicly.
| Name | Required | Description | Default |
|---|---|---|---|
| token | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| ok | Yes | ||
| code | No | ||
| message | No | ||
| nextCursor | No | ||
| nextOffset | No | ||
| syncStatus | No |
Changes observed during successful MCP inspections.
Input schema / $schemaPrevious value: -"http://json-schema.org/draft-07/schema#"New value: +"https://json-schema.org/draft/2020-12/schema"Input schema / properties / token / minLengthRemoved value: -8Input schema / properties / token / patternAdded value: +"^[a-f0-9]{64}$"Output schema / (root)Previous value: -nullNew value: +{
+ "$schema": "https://json-schema.org/draft/2020-12/schema",
+ "additionalProperties": {},
+ "properties": {
+ "code": {
+ "type": "string"
+ },
+ "message": {
+ "type": "string"
+ },
+ "nextCursor": {
+ "type": [
+ "string",
+ "null"
+ ]
+ },
+ "nextOffset": {
+ "anyOf": [
+ {
+ "maximum": 9007199254740991,
+ "minimum": 0,
+ "type": "integer"
+ },
+ {
+ "type": "null"
+ }
+ ]
+ },
+ "ok": {
+ "type": "boolean"
+ },
+ "syncStatus": {
+ "enum": [
+ "pending",
+ "ready",
+ "attention"
+ ],
+ "type": "string"
+ }
+ },
+ "required": [
+ "ok"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already cover safety (readOnly, idempotent, non-destructive). The description adds meaningful context beyond that: the token acts as a credential ('treat as a password, do not share publicly') and that the response includes meeting-link sync status. This is useful behavioral disclosure the annotations don't provide.
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?
Three short sentences, front-loaded with what the tool does, then the return content, then the security caveat. No wasted text.
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?
An output schema exists so return values needn't be detailed; the description notes one return aspect (meeting-link sync status) and covers the security-relevant behavior of the token. Minor gap: no explicit when-to-use guidance, but the tool is simple enough that this is acceptable.
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 0% for the one required parameter, but the description compensates by explaining the token's meaning and sensitivity (a password-like manage link). The regex format (64 hex chars) is only in the schema. Baseline 3 is appropriate given the description partially covers the single param.
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 (read) and resource (booking) with the scoping mechanism (private manage-link token). Distinguishes from siblings like get_booking_page or list_available_times by being the token-based single-booking fetch.
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?
Implies the retrieval context via 'using its private manage-link token' but never states when to use this vs. get_booking_page or preview_booking, nor any prerequisites. Usage is inferable but not explicit.
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.