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get_requisition

Retrieve one Lever requisition. Default output omits compensation band, internal notes, custom fields, and approval internals; full details require a reason.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
expandNoLever expand parameter for endpoint-supported objects.
reasonNoRequired when detail_profile requests contact, content, values, or full details.
includeNoLever include parameter for endpoint-supported fields.
detail_profileNooperational returns an operations view; full returns the raw endpoint payload.operational
requisition_idYesLever requisition ID.

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses that the default output omits compensation band, internal notes, custom fields, and approval internals, and that full details require a reason. This is meaningful behavioral context beyond what a read-only hint would provide, though not exhaustive.

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 action, and every phrase adds value. It is concise and well-structured.

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 tool has 5 parameters and no output schema. The description, combined with the fully documented schema, provides enough context for correct invocation: it clarifies the reason requirement and default output behavior. It does not explain return value structure, but there is no output schema, so it is not strictly required.

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 coverage is 100%, so baseline is 3. The description adds value by explaining what the default output includes/excludes (e.g., compensation band, internal notes) and that full details require a reason, which complements the schema's detail_profile and reason parameters.

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 the specific verb 'Retrieve' and names the resource 'one Lever requisition', clearly distinguishing it from list_requisitions (plural) and get_requisition_field (different resource). The additional detail about default output omissions clarifies the tool's scope.

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 states it retrieves a single requisition, which implies use when a specific requisition ID is known. It also notes that full details require a reason, giving guidance on when to provide that parameter. However, it does not explicitly name alternatives or exclusion criteria, so it falls short of a 5.

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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TDQS

B3.1/5.0
Disambiguation4/5

Most tools target distinct resource-action combinations, but the sheer count (108) and the presence of closely related tools like list_opportunity_feedback / get_opportunity_feedback may cause occasional agent confusion.

Naming Consistency5/5

Tool names follow a highly consistent verb_noun pattern (e.g., create_*, get_*, list_*, update_*, delete_*, add_*, remove_*). Minor exceptions like apply_to_posting still fit the overall structure.

Tool Count2/5

With 108 tools, the surface is excessively large for most agent workflows. Many tools could be merged or removed without losing essential functionality, leading to decision overload.

Completeness5/5

The tool set covers the full Lever API surface comprehensively, including opportunities, postings, requisitions, users, webhooks, templates, files, and compliance data, leaving no obvious gaps.

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