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update_user

Use Lever PUT /users/:id for recruiting operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYesJSON body to send to the documented Lever endpoint.
reasonNoReason for this Lever write.Requested through Lever Ops Control Plane.
confirmNoSet false only when you explicitly want to block execution.
dry_runNoWhen true, preview the write without sending it to Lever.
user_idYesLever user ID.
actor_idYesLever user ID associated with this action when needed.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

C2/5.0
Behavior1/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only mentions a PUT endpoint, with no details about mutation side effects, required permissions, idempotency, rate limits, or response shape. This is insufficient for an update operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence, but it is under-specified and wastes words on the vague phrase 'for recruiting operations.' It lacks a clear structure that front-loads meaningful content, resembling a placeholder more than a concise description.

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 six parameters, a nested body object, and no annotations or output schema, the tool is moderately complex. The description provides zero context about operation behavior, returned data, or error handling, and fails to differentiate from the many sibling tools. It is far from 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 descriptions for all six parameters, achieving 100% coverage. The description itself adds no parameter information, but the schema fulfills the baseline requirement, so a score of 3 is appropriate.

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

Purpose2/5

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

The description states 'Use Lever PUT /users/:id for recruiting operations,' which references an endpoint but does not explicitly say that it updates a user's fields. It fails to distinguish from sibling tools like create_user, deactivate_user, or reactivate_user, and the phrase 'for recruiting operations' is vague.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives such as create_user, deactivate_user, or list_users. No context about prerequisites, use cases, or exclusions is provided, leaving the agent without clear decision criteria.

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