get_jobFetch the full details of a single Arbeitnow job posting by its slug, INCLUDING the full HTML description. There is no single-job endpoint upstream, so this scans the most recent pages (~3) to find the matching slug. If the job has scrolled off the recent listings it cannot be retrieved — use search_jobs instead.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The job slug (from list_jobs/search_jobs results). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that there is no dedicated upstream endpoint, so the tool scans ~3 recent pages. This is valuable behavioral context beyond the annotations (which already indicate safety and idempotency). No contradiction with annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences: the first states the core purpose, the second provides crucial constraints and alternatives. No superfluous text; every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simple input (single slug), lack of output schema, and rich annotations, the description covers the tool's behavior, limitations, and fallback completely. No gaps for an agent to misunderstand.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema covers 100% of the single parameter 'slug' with a description that matches the tool's context. The description does not add significant meaning beyond the schema, meeting the baseline without exceeding.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Explicitly states that the tool fetches full details of a single job posting by slug, including the full HTML description. It also distinguishes itself from the sibling tool 'search_jobs' by noting when the job cannot be retrieved.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Clearly explains when to use (job within recent pages) and when not to (job scrolled off), and explicitly suggests the alternative 'search_jobs'. Provides actionable context for agent decision-making.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a clearly distinct purpose, from job searching to company research to bet analysis. Even closely related tools like ask_pipeworx and ask_pipeworx_grounded are differentiated by one being hallucination-resistant. Memory and subscription tools are clearly separated.
Most tools follow a verb_noun pattern (e.g., search_jobs, validate_claim, subscribe). However, some tools like pipeworx_feedback, pipeworx_trending, entity_profile deviate with noun_noun or proper noun patterns, creating minor inconsistency.
29 tools is above the typical 3-15 range, but the server covers a wide breadth of domains (jobs, company data, betting, memory, monitoring) so each tool earns its place. Slightly over-scoped but reasonable.
The tool set covers many domains but has notable gaps. For jobs, only search/list/get exist (no create/update/delete). For company data, update is missing. For betting, there is analysis but no placement. The set is broad but not deeply complete for any single domain.