Skip to main content
Glama

list_opportunity_resumes

List resume metadata for a Lever opportunity. Default output omits parsed resume details and download URLs; full metadata requires detail_profile=full with a reason.

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

A4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses two important behavioral traits: default output omits parsed resume details and download URLs, and full metadata requires a reason. This adds useful context beyond a simple 'list' statement. However, it does not discuss pagination behavior, response structure, or error conditions, leaving some transparency gaps.

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, directly stating the purpose and a key behavioral nuance with no filler. It is front-loaded and easy to parse, every sentence earns its place.

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, a clear schema, and no output schema. The description covers the essential behavior (list vs full), while the schema covers parameter details. It could be more explicit about return format or pagination, but given schema richness and simplicity of the operation, it is reasonably 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 schema provides 100% coverage with detailed descriptions for all five parameters, so the baseline is 3. The description adds marginal value by reiterating that detail_profile=full requires a reason and that default output is operational, but it does not clarify parameter syntax or add meaning beyond what the schema already states.

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 action (list), the resource (resume metadata), and the scope (for a Lever opportunity). It distinguishes itself from sibling tools like download_opportunity_resume and get_opportunity_resume by focusing on metadata listing, and further specifies default vs full metadata behavior.

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 implies this tool is for listing resume metadata rather than downloading or fetching a single resume. It provides clear usage guidance within the tool: use detail_profile=full with a reason to get full metadata, and notes the default omits parsed details. However, it does not explicitly contrast with alternatives or state when not to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

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