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list_opportunities

List Lever opportunities for recruiting-ops investigations. Default output omits contact PII while preserving stage, owner, source, tag, application, archive, snooze, and timestamp fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoComma-separated tag filters. Tags are case-sensitive.
emailNoFilter by exact candidate contact email.
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.
originNoComma-separated origin filters, such as sourced or applied.
reasonNoRequired when detail_profile requests contact, content, values, or full details.
sourceNoComma-separated source filters.
includeNoLever include parameter for endpoint-supported fields.
snoozedNo
archivedNo
stage_idNoComma-separated stage IDs.
contact_idNoComma-separated contact IDs.
posting_idNoComma-separated posting IDs.
created_at_endNo
detail_profileNooperational omits contact PII; contact includes name, emails, phones, links, and URLs.operational
updated_at_endNo
advanced_at_endNo
archived_at_endNo
confidentialityNo
created_at_startNoUnix timestamp in milliseconds.
updated_at_startNo
advanced_at_startNo
archive_reason_idNoComma-separated archive reason IDs.
archived_at_startNo
archived_posting_idNoComma-separated archived posting IDs.

TDQS

A3.5/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It usefully discloses that the default output omits contact PII while preserving specific fields, which is valuable context. However, it does not mention pagination behavior, read-only nature, or the effects of detail_profile, leaving several behavioral aspects undocumented.

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 short sentences with the verb and resource front-loaded. Every clause adds useful information, and there is no filler or repetition of schema details.

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

Completeness3/5

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

For a tool with 26 parameters, no output schema, and no annotations, the description is serviceable but not comprehensive. It gives a clear default behavior, but omits pagination, expand/include options, detail_profile implications, and the broader range of filters, relying heavily on the schema for completeness.

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?

Schema coverage is 62%, and many parameters already have descriptive text. The description adds little parameter-level meaning beyond hinting at output fields like stage, source, and tag, which map to some filters. It does not compensate for the remaining undocumented parameters, so it stays at the baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List'), resource ('Lever opportunities'), and context ('recruiting-ops investigations'), and adds meaningful detail about the default PII-safe output. It is distinct from many sibling tools at a glance, though it does not explicitly differentiate itself from similar list tools like list_deleted_opportunities or list_opportunity_applications.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies use for recruiting-ops investigations and emphasizes the PII-safe default, which hints at when this tool is appropriate. However, it does not explicitly state when to prefer it over alternatives such as get_opportunity or list_opportunity_applications, nor does it provide exclusions.

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.

Resources