list_insights
The workspace's AI insights (e.g. at-risk jobs, next actions): name, kind, schedule and when each last ran.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
The workspace's AI insights (e.g. at-risk jobs, next actions): name, kind, schedule and when each last ran.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=false, so safety and scope are covered without the description. The description adds useful context about the domain (insights represent at-risk jobs and next actions) but says nothing about ordering, pagination, or whether the list is exhaustive or per-user.
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 with no filler; the resource is named first and details follow. The trailing field enumeration is slightly packed but each item earns its place in the absence of a schema.
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 no parameters and no output schema, the description correctly carries the return-value burden by naming the fields (name, kind, schedule, last ran). It stops short of describing scope (whole workspace vs. current user) or ordering, which keeps it from being fully complete.
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 takes zero parameters, so the baseline of 4 applies; there is nothing for the description to disambiguate. The field list it provides describes output, not input, so it neither helps nor hurts this dimension.
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 and resource ('The workspace's AI insights') and concretizes it with examples (at-risk jobs, next actions) plus the fields each insight carries. It is clear on its own, but it never contrasts itself with the closely-named siblings run_insight and get_insight_result, so an agent must infer which one lists vs. executes.
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?
There is no explicit when-to-use or when-not-to-use guidance. Given siblings like run_insight and get_insight_result, the description should say this returns the catalog of insights rather than generating one, but that routing information is absent.
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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