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arbeitsagentur-mcp

arbeitsagentur-mcp

by slopinger
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

get_profession

Read-onlyIdempotent

Retrieve BERUFENET occupation details by profession ID, including tasks, access requirements, pay, training, and alternatives, plus the salary code needed for salary lookups.

Instructions

BERUFENET occupation profile: tasks, access requirements, pay, training, alternatives.

Also returns salary_kldb_code for get_salaries.

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": {
      "profession_id": "<profession_id>"
    },
    "name": "get_profession"
  }
}

Input Schema

NameRequiredDescriptionDefault
sectionsNoSection titles (or parts of them) to include, e.g. ['Verdienst', 'Zugang', 'Kompetenzen']. Default: overview, tasks, access, working conditions, pay, further training, alternatives
profession_idYesBERUFENET id from search_professions

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint and openWorldHint, so the safety profile is covered. The description adds one useful behavioral fact beyond the schema – that the result carries salary_kldb_code for downstream get_salaries calls – but says nothing about rate limits, auth, or how the external BERUFENET lookup behaves.

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?

Two short sentences, front-loaded with the resource and its contents, followed by the single cross-tool fact. Nothing is wasted or padded.

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?

An output schema exists, so return values need not be described, and the description covers the profile's contents plus the downstream salary linkage. It is essentially complete for a read-only lookup, with only minor gaps in explaining the external lookup's behavior.

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%: both profession_id (BERUFENET id from search_professions) and sections (with default list and examples) are fully documented in the schema itself. The description adds no parameter detail, so baseline 3 applies.

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 the resource (BERUFENET occupation profile) and enumerates the content it returns (tasks, access requirements, pay, training, alternatives), which distinguishes it from the sibling search_professions by signalling a detail fetch. It never states the verb explicitly ('retrieves/returns a profile'), but the content list makes the intent unmistakable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

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

Usage is implied through chaining cues: the schema ties profession_id to search_professions and the description notes salary_kldb_code is consumed by get_salaries, so an agent can infer the workflow. However, there is no explicit when-to-use or when-not-to-use statement (e.g. search first vs. fetch directly).

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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