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Get Jobs Status

get_jobs_status

Get the last build status for every Jenkins job matching a pattern in one request, replacing repeated per-job build queries.

Instructions

Last build of every job matching a pattern, in one call (use this instead of list_builds per job)

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_jobs_status"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNoMaximum number of jobs, 1-1000 (default 100)
folder_depthNoThe maximum depth of folders to traverse (default 3)
fullname_patternNoRegex searched in the job full name, e.g. "^Branch-Retail/prod-branch-retail-cloud/"

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.6.0+microtech.5

TDQS

A4/5.0
Behavior3/5

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

No annotations are supplied, so the description carries the disclosure burden; the naming convention and 'last build' phrasing imply a read-only bulk query, and 'in one call' hints at the batching efficiency. It does not say what happens to jobs with no builds, whether results are truncated at the limit, or how folder traversal affects the match set. Those gaps matter somewhat, but the presence of a full output schema and 100%-documented params limits the cost.

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 sentence with the primary behavior front-loaded and the disambiguation parenthetical at the end. No filler, and the most decision-relevant fact (bulk last-build lookup) comes first.

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?

Output schema is present so return shape need not be explained, and all three parameters are schema-documented. What remains thin is edge-case behavior (empty jobs, truncation, depth implications) for a regex-driven bulk query over a potentially large folder tree. Adequate to call correctly, slightly short of fully predictive.

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%, so limit, folder_depth and fullname_pattern are already fully documented, and the description adds nothing about regex semantics, defaults, or traversal cost. The phrase 'matching a pattern' loosely ties to fullname_pattern, but that is already in the schema. Baseline 3 applies when the schema does the heavy lifting.

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?

States a specific resource and scope: 'Last build of every job matching a pattern', which tells an agent exactly what comes back (one latest build per matching job) rather than a build list. It also names the sibling it replaces, so it is distinguishable from list_builds and get_build without opening any schema.

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?

Explicitly routes the agent away from 'list_builds per job', which is a concrete alternative with a stated condition (bulk pattern matching). It stops short of the inverse guidance – e.g. when to prefer get_build or list_builds for a single known job – so it is strong but not fully exhaustive.

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