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get_commands

Analyze which Cursor commands are used and how often. Filter by date range and specific users to get detailed usage analytics.

Instructions

Get command usage analytics: which Cursor commands are being used and how often.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
usersNoComma-separated emails to filter by specific users
endDateNoEnd date. Formats: "YYYY-MM-DD", "today", "yesterday". Default: "today"
startDateNoStart date. Formats: "YYYY-MM-DD", "7d", "30d", "today", "yesterday". Default: "30d"
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It only states 'Get', implying a read operation, but does not explicitly confirm non-destructiveness, mention authentication needs, or describe any side effects. The agent cannot infer safety or behavior beyond the vague verb.

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?

The description is a single concise sentence that immediately conveys the tool's purpose. Every word earns its place; there is no redundancy or irrelevant information.

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

Completeness2/5

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

With no output schema, the description should explain the response format. It vaguely mentions 'which commands are used and how often' but lacks specifics like data structure, aggregation level, or default behavior (e.g., date range defaults). The tool has optional parameters requiring default behavior clarification, which is missing.

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

Parameters3/5

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

The input schema provides 100% description coverage for all three parameters, so the schema itself is informative. The description adds no further meaning; it does not explain how filtering works or what the 'usage analytics' include. Given high schema coverage, a baseline score of 3 is appropriate.

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?

The description clearly states it retrieves command usage analytics, specifying the resource ('command usage') and the metrics ('which Cursor commands are being used and how often'). It distinguishes itself from more general analytics tools like get_daily_usage, but could be more explicit about its unique scope.

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

Usage Guidelines2/5

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 like get_daily_usage or get_mcp_usage. There is no mention of prerequisites, typical use cases, or when not to use it. This leaves the agent without context to choose correctly among sibling tools.

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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