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github_get_job_logs

Read-only

Download and read the log output for a specific GitHub Actions job. Prefer the exact owner from github_list_repositories; 'repo' also accepts the combined 'owner/name' form. Returns the actual console output from the job execution, showing build errors, test failures, and other details. Use this after getting workflow run jobs to read the logs for a failed job.

Input Schema

NameRequiredDescriptionDefault
repoYesRepository name. Also accepts the combined 'owner/name' form.
ownerNoRepository owner (e.g. 'octocat'). Prefer the exact owner from a prior github_list_repositories call. May be omitted when the repository name is unambiguous in this organisation, or embedded in 'repo' as 'owner/name'.
job_idYesThe job ID. Get this from github_get_workflow_run_jobs.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior3/5

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

readOnlyHint=true already tells the agent this is a safe read, so the bar is lower. The description adds useful content about what is returned ('actual console output... build errors, test failures'), but says nothing about log size, truncation, or rate limits — meaningful gaps for a log-download tool that can return very large payloads.

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?

Four short sentences, front-loaded with the purpose and then the usage rule; little waste. There is mild redundancy with the schema on the 'owner/name' form, but nothing bloated.

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

Completeness4/5

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

With no output schema, the description usefully compensates by describing the returned console output and its diagnostic value, and it names the prerequisite tool for the job_id. It stops short of covering pagination/truncation behavior, which an agent handling large logs would want.

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 the schema already documents the owner-preference and combined 'owner/name' behavior that the description restates, meaning the description adds no new parameter semantics. Baseline 3 is appropriate when the schema carries the parameter burden.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The first sentence states a specific verb ('Download and read') and an unambiguous resource ('the log output for a specific GitHub Actions job'). This clearly separates it from siblings like github_download_artifact (artifact files), github_get_workflow_run_jobs (job metadata) and get_pipeline_step_logs (pipeline, not Actions job).

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?

It gives a concrete ordering rule: 'Use this after getting workflow run jobs to read the logs for a failed job,' which anchors the tool in the workflow-run investigation sequence. It does not, however, state when NOT to use it (e.g. vs get_pipeline_step_logs or github_download_artifact), so a sibling distinction is left implicit.

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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