mcp-ci-triage

job_log_tail

Fetch a bounded, sanitized tail of a GitHub Actions job log to triage CI failures and see why a job failed without exposing untrusted content.

Instructions

Return a bounded, sanitized tail of an untrusted GitHub Actions job log.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "repo": "<repo>",
      "job_id": "<job_id>"
    },
    "name": "job_log_tail"
  }
}

Input Schema

Name	Required	Description	Default
`repo`	Yes
`lines`	No
`job_id`	Yes

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 7, 2026

TDQS

B3.1/5.0

Behavior3/5

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

With no annotations, the description carries the full burden. It does disclose real behavioral traits beyond the schema: the output is truncated ('bounded'), content is scrubbed ('sanitized'), and the source is 'untrusted', which is a useful safety signal. However, it omits what sanitization removes, whether auth/scope is required, and any rate-limit or failure behavior.

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

Conciseness5/5

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

A single tight sentence with zero filler, and the resource and its key constraints are front-loaded. Nothing could be trimmed without losing 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?

An output schema exists, so return-value explanation is not required, and the sentence conveys the essential behavior. But for a 3-parameter tool with zero schema descriptions, the missing parameter semantics and lack of usage routing leave it only minimally complete.

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% and the description adds no meaning for repo, job_id, or lines. The word 'tail' weakly implies that 'lines' controls how many trailing lines are returned (default 80), but this is inference, not documentation, so it only partially compensates for the coverage gap.

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 ('Return') and resource ('tail of an ... GitHub Actions job log'), with three meaningful qualifiers: bounded, sanitized, untrusted. This clearly distinguishes it from siblings like recent_runs and failing_jobs, which enumerate jobs rather than fetch log content, though it never 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 Guidelines2/5

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

No statement of when to use this versus recent_runs, failing_jobs, or mixed_outcome_workflows, and no prerequisites (e.g., that a job_id must first be obtained from one of those tools). Usage is only inferable from the name.

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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