list_insightsDetected week-over-week changes and anomalies that are still going on, most impactful first, each with the two weeks it compares. Use when asked what changed, or why something moved — and check each change's window against the period you are describing before connecting them. For how long a change has lasted use list_insight_episodes; for what to do about it, list_recommendations.
| 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, idempotentHint, and destructiveHint=false, so safety is covered and the bar is lower. The description still adds real behavioral value the annotations don't: scoping to changes 'still going on', the 'most impactful first' ordering, and that each entry carries its own two-week comparison window. It stops short of describing pagination or limits, which keeps it out of 5 territory.
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 sentences, front-loaded with what is returned, then when to use it, then the routing alternatives. Every clause carries distinct information; the window-caution clause is the only slightly dense part and it is genuinely actionable.
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 has to carry the return shape itself, and it does: a most-impactful-first list of ongoing changes, each with its comparison weeks. It also covers both the call-time routing decision and the interpretation caveat about windows, so nothing an agent needs is missing.
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 per the rubric the baseline is 4. There is no parameter surface for the description to enrich, and it correctly spends no words on one.
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 states a specific resource and scope: week-over-week changes and anomalies that are still ongoing, ordered by impact, each carrying its comparison window. It also differentiates itself from siblings by naming list_insight_episodes and list_recommendations, so an agent can route correctly without opening any schema.
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?
Explicit trigger ('Use when asked what changed, or why something moved'), plus a concrete precondition ('check each change's window against the period you are describing before connecting them'), plus named alternatives for the two adjacent intents (duration -> list_insight_episodes, action -> list_recommendations). This is about as complete a routing statement as a list tool can carry.
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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