Investigate self-hosted product analytics by posing natural-language questions about metric changes, such as revenue dips, using evidence and coverage checks.
Ask a natural-language question about your analytics, e.g. 'why did revenue dip last Tuesday?'
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| question | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
v0.1.0Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds no behavioral context beyond that — nothing about cost, latency, scope, or how the answer is produced.
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 sentence with an inline example, front-loaded and free of waste. Nothing is extraneous and it is appropriately sized.
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 need not be explained, and annotations cover safety. However, the description leaves the 'days' parameter and the relationship to sibling query/investigation tools unaddressed, which matters given the crowded toolset.
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 description coverage is 0%, so the description must compensate but does not. The example question loosely maps to the 'question' parameter, but the 'days' parameter (default 30) is never explained, leaving a key scoping input undocumented.
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 gives a specific verb (Ask) and resource (natural-language question about analytics), plus a concrete example. It does not distinguish itself from siblings like investigate_change or query_metrics, so it falls short of the top score.
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 guidance on when to use this tool versus structured alternatives such as query_metrics or run_query, and no when-not conditions. The example implies a diagnostic use case but does not route the agent explicitly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.