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azure-utils-mcp

by BrianDeacon

servicebus_peek_dlq_to_file

Peek at messages in a Service Bus dead letter queue without removing them, and save message bodies to a JSON file keyed by sequence number.

Instructions

Non-destructively peek at messages in the dead letter queue for an Azure Service Bus queue, saving bodies to a file.

Message bodies are written to output_file as JSON (keyed by sequence number). Only metadata (dead letter reason, error description, sequence number, enqueue time) is returned in context.

connection_string_env_var: name of the environment variable holding the Service Bus connection string. If the variable is set, connection-string auth is used; otherwise DefaultAzureCredential is used.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceYes
queueYes
output_fileYes
max_countNo
connection_string_env_varNoAZURE_SERVICEBUS_CONNECTION_STRING

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations are present, so the description must cover behavioral traits. It correctly states non-destructiveness and output details (bodies to file, metadata returned). It also explains authentication logic. Missing details on file overwrite behavior, error handling, and performance implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, with two clear paragraphs. It uses line breaks for readability. The first sentence effectively states the core purpose. It could be more structured (e.g., listing parameters) but is efficient with no redundant information.

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

Completeness3/5

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

Given the complexity (5 params, output schema exists) and no annotations, the description covers the main behavior and authentication but misses edge cases like file overwrite behavior, error conditions, and a full explanation of max_count. It is adequate but has gaps.

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

Parameters2/5

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

Schema description coverage is 0%. The description only explains the connection_string_env_var parameter (fallback auth). Other parameters (namespace, queue, output_file, max_count) are not described beyond their names and one mention of output_file. This does not sufficiently compensate for the lack of schema descriptions.

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 tool peeks at dead letter queue messages and saves bodies to a file, specifying the verb 'peek', resource 'dead letter queue', and output destination. It distinguishes from siblings like servicebus_peek_dlq by mentioning file output and metadata-only context, but could explicitly differentiate from similar tools.

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 provides context: non-destructive operation, file output, and authentication fallback. However, it does not explicitly state when to use this tool over siblings like servicebus_peek_dlq or servicebus_purge_dlq, nor does it offer guidance on the max_count parameter.

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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