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smeet666

mcp-lever

Read one opening

get_job
Read-onlyIdempotent

Retrieves the complete job posting from a Lever board, including sections and published salary, for a specific opening at a company.

Instructions

Read one Lever opening in full: the advert, its named sections, and the salary as published. company_slug and instance are the ones the row carried, and a site living on both instances holds different openings on each.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
job_idYesThe identifier of one opening, as a search returns it.
instanceNoThe Lever instance the row came from. Left out, the global one is read.
company_slugYesThe Lever site name, as resolve_company returns it.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
jobYes
notesYes
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds meaningful behavior beyond annotations: it specifies what is returned (advert, named sections, salary) and warns that a site on both instances may hold different openings, helping the agent interpret results correctly. 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.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with the core purpose. Every clause contributes: the first sentence defines the output, the second clarifies parameter provenance and cross-instance behavior. No redundant wording or filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a focused read tool with an output schema and strong annotations, the description is complete. It states what the tool returns, how to obtain parameters, and a critical edge case (differing data per instance). No obvious missing context given the tool's simplicity and the presence of an output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds semantic value by explaining that company_slug and instance should be the ones 'the row carried', linking them to a search result. The instance nuance (different data per instance) further clarifies the parameter's meaning. This is a clear addition beyond the schema.

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 uses a specific verb ('Read') and names the exact resource ('one Lever opening in full'), and distinguishes this tool from siblings by emphasizing the full detail retrieval vs. searching or listing (search_jobs, list_filter_values). It also names the key output components (advert, sections, salary), making the purpose unambiguous.

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?

The description establishes a clear context: use this when you need the full content of a specific opening, identified by a row from a prior search. It also provides a key nuance about instance-specific data. However, it does not explicitly mention when not to use it or name alternatives, though the sibling list implies search_jobs for discovery.

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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