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Tiberriver256

Azure DevOps MCP Server

get_pipeline_log

Fetch a specific Azure DevOps pipeline run log using run ID and timeline log ID; optionally limit lines and choose plain or JSON output.

Instructions

Retrieve a specific pipeline log using the timeline log identifier

Input Schema

TableJSON 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: MyProject)
startLineNoOptional starting line number for the log segment
pipelineIdNoOptional pipeline numeric ID for reference only

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv1.0.6
    • addedInput schema / properties / endLine / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / logId / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / pipelineId / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / runId / maximum
      Added value: +9007199254740991
    • addedInput schema / properties / startLine / maximum
      Added value: +9007199254740991
  2. Addedv1.0.0

TDQS

C2.9/5.0
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 behavioral burden, yet it only says what is retrieved. It does not disclose that log output can be large or paginated via startLine/endLine, whether ranges are inclusive, permission requirements, or the default format.

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 zero filler; the resource and identifier mechanism come first. It is efficient, though it is arguably too terse to earn a top score given the tool's 7-parameter surface.

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?

With 7 parameters, no annotations, and no output schema, the description should do more work than one sentence. It omits segment/range behavior, format defaults, and the fact that the logId originates from a timeline record, leaving an agent to reconstruct the calling workflow from the schema alone.

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% and all seven parameters are documented in the schema, so the baseline of 3 applies. The description only echoes the logId semantics ('timeline log identifier') and adds no meaning beyond the schema, e.g. how logId relates to runId or how line ranges behave.

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 (retrieve) and resource (pipeline log) and identifies the keying mechanism (timeline log identifier). An agent can distinguish it from list_pipelines or get_pipeline_run, but the description never names or contrasts those adjacent siblings for differentiation.

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?

There is no explicit when-to-use guidance, no prerequisites, and no mention of alternatives such as pipeline_timeline (which supplies the logId) or get_pipeline_run. Usage is only implied by the tool name and the phrase 'using the timeline log identifier'.

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