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Jobroulette

Draft a job application (Bewerbung) by email

draft_job_application
Read-onlyIdempotent

Use this when the user wants to apply for one of their matched jobs (Bewerbung). Drafts an application by email for that job: recipient from the posting, subject, cover letter and the stored resume document as attachment. Sends nothing. Show the user the draft, let them edit the cover letter and sign it with their name. If the posting asks for more (salary expectation, earliest start date, a cover letter, certificates), forderungen names each with a hint for the user; the cover letter then holds a line with [bitte eintragen] that must be filled in or removed before sending. If the posting names no email address for applications, the call is refused and names the posting. Scope: cv:lesen.

Input Schema

NameRequiredDescriptionDefault
stelleIdYes

Output Schema

NameRequiredDescriptionDefault
urlYes
titelYes
anhangYes
betreffYes
stelleIdYes
empfaengerYes
anschreibenYes
arbeitgeberYes
forderungenYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior5/5

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

Beyond the annotations, the description discloses that the tool creates a draft only, builds recipient/subject/cover letter/resume attachment, refuses the call when no application email exists, and inserts [bitte eintragen] placeholders for missing requirements. These are substantive behavioral details an agent needs before invoking it.

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?

The trigger is front-loaded and the sentences are information-dense with little waste. It is somewhat long, but most of the length is justified by the draft, placeholder, and refusal behaviors it must convey.

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?

The description covers the draft workflow, refusal condition, placeholder behavior, attachment handling, and scope, and an output schema exists so return values need not be explained. The main remaining gap is that it does not explicitly route the user to send_job_application for the send step or clarify the stelleId parameter.

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?

There is one required parameter, stelleId, but schema description coverage is 0%. The description refers only to 'that job' and 'matched jobs' and never explicitly explains that stelleId is the UUID of the matched posting to draft against.

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 description states a specific verb and resource: it drafts an email application for a matched job. It also immediately distinguishes itself from send_job_application by saying 'Sends nothing', so an agent can tell which sibling to select.

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 clear trigger: use when the user wants to apply for one of their matched jobs. It also says to show the draft for editing and signing, but it does not explicitly name send_job_application as the follow-up tool for actually sending.

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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