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NotHarshhaa

mainframe-mcp-server

by NotHarshhaa

get_job_capacity

Read-onlyIdempotent

Retrieves per-step and total CPU consumption for a job from JESMSGLG, including an MSU estimate when CAPACITY_MSU_RATING is configured.

Instructions

CPU consumption of a job — per step and total from JESMSGLG (IEF374I/IEF376I), with an MSU estimate when CAPACITY_MSU_RATING is configured.

Input Schema

NameRequiredDescriptionDefault
jobIdYesJES job id, e.g. "JOB01234".
environmentNoNamed target environment (see list_environments), e.g. "dev", "prod". Omit to use the server default.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv3.0.0

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover read-only, idempotent and non-destructive semantics, and the description adds real value on top: it discloses the data source (JESMSGLG, IEF374I/IEF376I) and the fact that MSU figures only appear when CAPACITY_MSU_RATING is configured. It stops short of saying what happens when those log records are missing or the job's JESMSGLG has been purged.

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 front-loaded sentence that carries the source, the specific message IDs and the conditional behaviour with no filler. Every clause is load-bearing.

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 only two parameters, full schema coverage and no output schema, the description does a fair amount of return-value work by previewing the shape (per step, total, optional MSU estimate). A note on behaviour when the log records are absent is the main remaining gap.

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% — jobId and environment are both documented inline, including the pointer to list_environments. The description adds nothing about either parameter, so this sits at the baseline where the schema does all the work.

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?

Names a specific resource (CPU consumption of a job) and scopes it precisely to per-step and total figures, plus a conditional MSU estimate. It is distinctive enough that an agent can separate it from get_job_status or get_job_output, though it never explicitly names those siblings as alternatives.

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 when-to-use, when-not-to-use, or alternative-naming guidance. The description never tells the agent to prefer estimate_mlc_cost for cost figures or get_job_output for raw log text, so routing must be inferred from the noun phrase alone.

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