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psprakhar020

Azure Image Pipeline MCP

by psprakhar020

queue_image_pipeline

Queue an Azure image pipeline run only when writes are enabled and an exact confirmation token is supplied, using runtime, image flavour, and location.

Instructions

Queue an image pipeline only when writes are enabled and the exact confirmation token is supplied.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
branchNorefs/heads/main
locationYes
confirmationYes
image_flavourYes
image_versionNo
runtime_versionYes
enable_security_scanNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.3/5.0
Behavior3/5

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

With no annotations, the description carries the full behavioral burden. It usefully discloses the write-enablement gate and exact confirmation-token requirement, but it omits side effects of queuing, error behavior for invalid tokens, idempotency, and any authorization details beyond 'writes are enabled.'

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 a single front-loaded sentence with no wasted words. It is structurally clean, though extremely terse for a mutation tool with seven parameters.

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?

For a seven-parameter mutation tool with no annotations and zero schema description coverage, the description is too thin. The output schema can cover return values, but the description still needs to clarify input semantics, preconditions, and side effects.

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% across seven parameters, so the description must compensate and largely does not. It hints that confirmation must be an exact token, but runtime_version, image_flavour, location, branch, image_version, and enable_security_scan remain semantically undocumented.

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?

States a specific verb and resource: 'Queue an image pipeline.' The action is clearly distinct from the read-oriented siblings list_recent_image_runs, get_image_run_status, and get_image_run_evidence, but the description never explicitly differentiates or names them.

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

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear precondition for use: only when writes are enabled and the exact confirmation token is supplied. This implies when not to use it, but it does not name alternative tools or explain what to do if the condition is not met.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.