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get_opportunity_offer

Retrieve one Lever offer by scanning the documented Lever offers list for this opportunity. Default output supports offer hygiene checks without returning offer field values, signature data, or download URLs.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
reasonNoRequired when detail_profile requests contact, content, values, or full details.
offer_idYesLever offer ID.
detail_profileNooperational returns an operations view; full returns the raw endpoint payload.operational
opportunity_idYesLever opportunity ID.

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the burden of disclosing behavior. It reveals that the tool works by 'scanning the documented Lever offers list' and that the default output is limited to non-sensitive data, which adds context beyond a simple 'retrieve offer'. It does not discuss error handling or authentication, but for a read-type tool, this is reasonable.

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 ('Retrieve one Lever offer'), and every clause adds useful detail. There is no fluff or redundancy.

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?

The description explains what the default output does *not* contain but does not specify what it *does* contain, which is a gap given the absence of an output schema. It also does not mention error behavior or the relationship to list_opportunity_offers, making it adequate but not fully 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?

Schema description coverage is 100%, so the baseline is 3. The description does not add additional meaning to the parameters beyond what the schema already provides. The 'detail_profile' parameter is described in the schema with enum values, and the description does not elaborate further.

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 states the tool retrieves a single Lever offer for a specific opportunity, using the verb 'Retrieve' and identifying the resource. It also differentiates from siblings like list_opportunity_offers and download_opportunity_offer_file by explicitly noting what the default output does not include.

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 provides a clear use case: 'supports offer hygiene checks' and indicates that the default output omits offer field values, signature data, and download URLs, implying it is for quick verification rather than detailed data retrieval. However, it does not explicitly name alternative tools for those needs.

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