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CData Arc MCP Server

by ctslone

get_requests_count

Count request logs in CData Arc with optional OData filters. Retrieve the total number of matching requests for accurate monitoring and analysis.

Instructions

Get the total count of request logs with optional filtering

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
filterNoOData filter expression to count specific requests (e.g., "Method eq 'GET'")
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 implies a read-only operation but never explicitly states that, nor does it describe the return format (e.g., an integer), whether it counts all matching logs by default, or any potential performance implications. The optional filtering is mentioned, but nothing else about behavior.

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 front-loads the main purpose and mentions the optional filter. No wasted wording or unnecessary repetition.

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?

The tool is simple with one parameter, no output schema, and no annotations. The description states the purpose and the optional filter, which is enough for a count operation. However, it does not explicitly confirm what the count represents or what the response looks like, though this is largely inferable from the name and nature of the tool.

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 single parameter 'filter' is fully described in the input schema with an OData example, giving 100% schema coverage. The description adds only the phrase 'optional filtering', which adds minimal value beyond what the schema already states. Baseline 3 applies because the schema does the heavy lifting.

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

Purpose5/5

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

The description clearly states the tool gets a total count of request logs, with an optional filter. This distinguishes it from sibling count tools like get_transactions_count and get_message_count by naming the resource (request logs). The verb 'Get' and resource 'request logs' are specific.

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 gives no guidance on when to use this tool versus alternatives such as get_requests (which lists requests) or other count tools. It does not mention exclusions or context like 'use this when you only need a count, not the list'. This leaves the agent to infer usage from the tool name alone.

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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