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list_requisitions

List Lever requisitions for open headcount, filled headcount, owner, hiring manager, team, department, and status analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoResults per page. Lever accepts 1-100; default is endpoint-specific.
cursorNoLever pagination offset token from a previous response. Use next_cursor from the prior tool result.
expandNoLever expand parameter for endpoint-supported objects.
reasonNoRequired when detail_profile requests contact, content, values, or full details.
statusNoFilter requisitions by Lever status, such as open.
includeNoLever include parameter for endpoint-supported fields.
created_at_endNo
detail_profileNooperational returns an operations view; full returns the raw endpoint payload.operational
confidentialityNo
created_at_startNoUnix timestamp in milliseconds.
requisition_codeNo

TDQS

A3.5/5.0
Behavior2/5

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

No annotations are provided, so the description must convey behavioral traits. It only says 'List', which implies a read-only operation, but gives no details about pagination, return format, rate limits, or default behavior. It does not mention how limit/cursor work or what the response structure is. This is a significant gap for a tool with many parameters.

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 description is a single sentence and efficiently conveys the core purpose. It does not waste words, though the long list of analysis dimensions could be more structured. It earns a 4 because it is compact while still informative.

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

Completeness2/5

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

With 11 parameters and no output schema, the description does not sufficiently cover context. It fails to state what the response looks like, whether pagination is included, or how to choose filters. The analytical framing gives some context, but for a complex list endpoint, more guidance is needed to be complete.

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

Parameters3/5

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

The input schema covers 73% of parameters with descriptions, and the tool description does not add parameter-level semantics. It mentions 'status' as an analysis dimension, which loosely relates to the status parameter, but does not explain how to use it. Given the schema's baseline coverage, a score of 3 is appropriate; the description adds no extra parameter meaning.

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 clearly specifies the action ('List') and resource ('Lever requisitions'), and goes beyond a bare verb by highlighting the analytical dimensions (open headcount, filled headcount, owner, hiring manager, team, department, status). This distinguishes it from sibling tools like get_requisition (single item) or create_requisition, while the mention of analysis sets it apart from list_requisition_fields.

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 a clear use case ('for ... analysis'), implying when to use it. However, it does not explicitly mention alternatives or exclusions, such as using get_requisition for a single record. It earns a 4 because the context is clear, though it lacks explicit comparisons to sibling tools.

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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