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Generate an AI insight

generate_ai_insight
Read-only

Generate a short, factual AI insight from the signed-in account's real website traffic over the last 30 days (pageview trend, top source, unique visitors).

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered; the description adds substantive context beyond that — the fixed 30-day lookback, that it draws on real account traffic (not synthetic data), and that the output is short and factual rather than a full report. It does not mention generation latency, cost, or non-determinism, which would be the remaining useful disclosures.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that front-loads the action, the output character (short, factual), the data source and window, and the three topics covered. Nothing is wasted and nothing relevant is buried.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a no-parameter, read-only tool this covers source, scope, and content of the insight. With no output schema present, a brief note on the return shape (e.g., a prose string vs. structured fields) would have closed the last gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool takes zero parameters, so the baseline is 4. The description usefully explains why there are none: the window is fixed at 30 days and the account is implicit ("signed-in account"), pre-empting an agent from hunting for filter arguments.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and artifact ("Generate a short, factual AI insight") plus the exact data basis: the signed-in account's real website traffic over the last 30 days, listing the three things covered (pageview trend, top source, unique visitors). It is clearly distinguishable from siblings like get_website_overview or investigate_traffic_day, though it never names a sibling explicitly to sharpen that contrast.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The implied usage is clear enough — call this when you want a narrative summary rather than raw traffic data — and the 30-day window is stated. But there is no explicit "use this instead of get_website_overview when..." routing, and no note about whether it should be called repeatedly or cached.

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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