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Azure DevOps MCP Server
by billg118

get_pipeline_log

Retrieve a specific Azure DevOps pipeline run log by run ID and timeline log ID, with optional line-range and JSON/plain formatting to inspect build or deployment output.

Instructions

Retrieve a specific pipeline log using the timeline log identifier

Input Schema

NameRequiredDescriptionDefault
logIdYesLog identifier from the timeline record
runIdYesPipeline run identifier
formatNoOptional format for the log contents (plain or json)
endLineNoOptional ending line number for the log segment
projectIdNoThe ID or name of the project (Default: no default project)
startLineNoOptional starting line number for the log segment
pipelineIdNoOptional pipeline numeric ID for reference only

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.54

TDQS

C2.9/5.0
Behavior2/5

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

With no annotations, the description must carry the full burden. It states 'Retrieve' indicating a read operation, but omits whether it's safe, requires auth, handles missing logs, or returns partial content via startLine/endLine. No behavioral context beyond the basic action.

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?

A single, front-loaded sentence with no wasted words. It is appropriately sized, though it could include slightly more context without harming conciseness.

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?

The tool has 7 parameters and no output schema. The description does not explain what the log contains, how to use range parameters, or what to expect from the 'format' enum. This leaves key context missing for an agent to call it effectively.

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 coverage is 100%, so all parameters are described in the schema. The description adds no meaning beyond the schema; it only reiterates that a log identifier is used. Baseline 3 applies.

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: 'Retrieve a specific pipeline log'. The phrase 'using the timeline log identifier' hints at the input source and distinguishes it from a general log fetch. However, it does not explicitly contrast with siblings like pipeline_timeline or get_pipeline_run.

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?

Provides no explicit when-to-use guidance, prerequisites, or alternatives. The mention of 'timeline log identifier' implies you need a logId from the timeline tool, but it doesn't state when to use this over pipeline_timeline or how to obtain the ID.

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