Fetch a single Tesla Careers job posting by its numeric job ID, returning structured details for one role from the list endpoint.
Tesla Jobs single posting. Returns one Tesla Careers posting by its numeric job id (the id field returned by the list endpoint).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Tesla job id |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It correctly frames this as a single-item read, but says nothing about authentication, whether unpublished/expired postings are returned, or failure behavior for an invalid id. Adequate but with real gaps for an annotation-free tool.
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, no filler, with the core purpose front-loaded and the id provenance immediately after. Every clause 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?
For a single-parameter detail fetch with no output schema and no annotations, the description covers what it returns and where the input comes from. It omits return-shape and error behavior, which keeps it just short of complete.
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 coverage is 100% (baseline 3), and the description adds genuinely new meaning: the id is 'numeric' and originates from the list endpoint's `id` field. That goes beyond the schema's terse 'Tesla job id'.
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?
States a specific verb and resource ('Returns one Tesla Careers posting') and distinguishes itself from its sibling tesla_jobs_list by naming the retrieval pattern ('the `id` field returned by the list endpoint'). An agent can tell it apart from the list tool without opening either schema.
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?
Makes the usage pattern clear: call tesla_jobs_list first, then feed its `id` into this tool. It stops short of explicitly naming the sibling tool or stating when-not-to-use, but the context is unambiguous for a detail-fetch tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.