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rlaput

Azure Logs MCP

by rlaput

Get Request Logs by Order Number

getRequestLogsByOrderNumber

Retrieve Azure Application Insights request logs by searching for a specific order number in request names, URLs, or custom dimensions within a defined time range.

Instructions

Retrieves request logs from Azure Application Insights by order number. Searches through request logs containing the order number in name, URL, or custom dimensions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
durationNoTime range for the query in ISO 8601 duration format (default: P7D for 7 days)P7D
limitNoMaximum number of log entries to return (default: 50)
orderNumberYesThe order number to search for in the Azure Application Insights logs
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 of behavioral disclosure. It mentions retrieval and search behavior but fails to cover critical aspects like authentication requirements, rate limits, error handling, or the format of returned logs. This leaves significant gaps for a tool interacting with a cloud service.

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, efficient sentence that front-loads the core purpose and includes essential details about the search scope. Every word contributes value without redundancy, making it appropriately sized and well-structured.

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?

Given the complexity of querying Azure Application Insights, no annotations, and no output schema, the description is insufficient. It lacks details on authentication, response format, error cases, or operational constraints, leaving the agent with incomplete context for effective use.

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?

Schema description coverage is 100%, with each parameter well-documented in the schema (e.g., duration format, limit range, orderNumber pattern). The description adds no additional parameter semantics beyond what the schema provides, so it meets the baseline but does not enhance understanding.

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 the verb ('retrieves') and resource ('request logs from Azure Application Insights'), specifying the search scope (by order number in name, URL, or custom dimensions). However, with no sibling tools provided, it cannot demonstrate differentiation from alternatives, preventing a perfect score.

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 description implies usage for searching logs by order number in Azure Application Insights, but it does not explicitly state when to use this tool versus other methods or tools, nor does it provide exclusions or prerequisites. With no sibling tools, it lacks comparative guidance.

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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