get_analytics_summaryDashboard-level overview: views, conversations, lead counts, conversion rate.
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| client | No | Agency only: target a managed client org by its id to query that client's data. Omit for your own. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / properties / clientAdded value: +{
+ "description": "Agency only: target a managed client org by its id to query that client's data. Omit for your own.",
+ "type": "string"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only behavior, but the description adds little beyond the list of metrics. It does not explain how the data is aggregated, whether the overview is limited to a date range, how the client parameter affects the result, or any other behavioral detail. The description is essentially a summary of contents, not behavior.
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?
The description is a single, front-loaded sentence that immediately states what the tool provides. There is no unnecessary wordiness, and the metrics are listed in a compact, scannable way.
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 simple tool with two optional parameters, the description gives basic metric names but omits return format, aggregation level, and parameter effects. The absence of an output schema places more burden on the description to explain what the agent will receive, which it does not do.
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?
With 50% schema description coverage, only the 'client' parameter has an explanation in the schema. The description does not clarify the 'days' parameter or how it interacts with the summary. Since the description adds no parameter-specific information, it fails to compensate for the missing schema description.
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 clearly states the tool provides a 'dashboard-level overview' of key metrics (views, conversations, leads, conversion rate), which distinguishes it from sibling tools that focus on specific details. However, it lacks an explicit verb and could be more precise about the exact scope, so it doesn't reach a 5.
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?
The description provides no guidance on when to use this tool versus alternatives. It does not mention any exclusions, prerequisites, or context for choosing this over siblings like get_conversations or get_hot_leads. The 'overview' label implies a general use case, but no explicit direction is given.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Most tools are clearly distinct, but get_conversations and search_by_intent both return conversations, and get_hot_leads vs get_lead_enrichment have some overlap. Descriptions clarify their specific purposes, so ambiguity is minimal.
The majority of tools follow the get_* pattern, but search_by_intent deviates. Otherwise, naming is consistent and readable.
With 8 tools, the count is well-scoped for the server's purpose. Each tool focuses on a distinct aspect of buyer intent, from summaries to specific searches, without unnecessary bloat.
The server covers core needs: overview, listing, detail, enrichment, MEDDIC summary, knowledge gaps, and search. Missing are non-read operations and a general lead list (only hot leads), but these are minor gaps for an analytics-focused server.