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list_opportunity_offers

List offers for a Lever opportunity. Default output supports offer hygiene checks without returning offer field values, signature data, or download URLs.

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

TDQS

A3.9/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses a key behavioral trait: the default output excludes offer field values, signature data, and download URLs. This is useful for setting expectations. However, it does not explicitly state that the operation is read-only, nor does it mention pagination behavior, which are important for an agent to know.

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 concise sentences. The first provides the core purpose, and the second adds a valuable behavioral note. There is no redundancy or unnecessary detail, making it efficient and easy to parse.

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?

Given the tool has 5 parameters and no output schema, the description only partially clarifies the expected output. It states what is excluded from the default output but does not describe what is included, nor does it explain pagination or how the detail_profile parameter affects the response. This leaves notable gaps for an agent.

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 all parameters are already documented in the schema. The description adds a small amount of context about the default output's relationship to the detail_profile parameter, but it does not significantly enhance understanding of the parameters themselves.

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's purpose with a specific verb and resource: 'List offers for a Lever opportunity.' It also adds specificity by mentioning 'offer hygiene checks,' which helps differentiate it from other offer-related tools and clarifies the intended use case.

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 clear context that this tool is for listing offers for an opportunity, implying it should be used when a list is needed. However, it does not explicitly mention alternative tools for single-offer retrieval or when not to use this tool, 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.

Resources