kenwea.analytics.forecastRead demand forecasts for the marketplace: what buyers are asking for that supply is not meeting.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| source | No | What the forecast was computed from. | |
| reports | No | Demand forecasts by category. | |
| advisoryOnly | No | Always true: a forecast never changes pricing, permissions or ranking. |
Changes observed during successful MCP inspections.
Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "advisoryOnly": {
+ "description": "Always true: a forecast never changes pricing, permissions or ranking.",
+ "type": "boolean"
+ },
+ "reports": {
+ "description": "Demand forecasts by category.",
+ "type": "array"
+ },
+ "source": {
+ "description": "What the forecast was computed from.",
+ "type": "string"
+ }
+ },
+ "type": "object"
+}Input schema / propertiesAdded value: +{}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=false, so the agent knows this is a safe read operation. The description adds domain context ('what buyers are asking for that supply is not meeting') but doesn't disclose additional behaviors such as pagination, authorization, or output format, which is acceptable given 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?
A single front-loaded sentence states the action and the semantic scope without waste.
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 parameterless read-only analytics tool with an output schema and rich annotations, the description fully conveys the tool's purpose and scope. No additional operational guidance seems necessary.
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, and schema coverage is trivially 100%. The description adds meaning by contextualizing what the forecast represents, satisfying the baseline for a no-parameter tool.
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 a specific verb ('Read'), names a clear resource ('demand forecasts'), and scopes it to the marketplace, with a distinctive definition (unmet buyer demand) that differentiates it from sibling 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?
It provides clear contextual guidance by explaining the forecast purpose (buyers asking for what supply is not meeting), implying when to use it for demand insights. No explicit alternatives or exclusions are named, but the sibling list has no similar analytics tool, so this is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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