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update_requisition

Use Lever PUT /requisitions/: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.
record_idYesLever requisition or requisition-field ID.
perform_asYesLever user ID for perform_as when the Lever endpoint needs one.

Schema Changelog

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

  1. First observed

TDQS

C2.1/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It implies a mutation through 'PUT,' but does not explain the scope of changes, whether the operation is reversible, what permissions are needed, or how the write affects the requisition. This is minimal and insufficient for a write 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 very short, but this is not effective conciseness; it is under-specification. The single sentence provides no substantive information beyond the endpoint path, so it does not earn its place.

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

Completeness1/5

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

The tool has 6 parameters, a generic body object, and no output schema or annotations. The description fails to explain what the tool actually does, how it relates to other requisition tools, or what 'updating a requisition' involves. This is a completely inadequate context for an agent to select and invoke the tool correctly.

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 parameters are already well documented in the schema. The description adds no additional semantic meaning for parameters like 'body', 'record_id', or 'perform_as', so the baseline 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 only says 'Use Lever PUT /requisitions/:id for recruiting operations,' which restates the endpoint implied by the tool name and gives no semantic description of what updating a requisition entails. It neither specifies the verb and resource in a meaningful way nor distinguishes from sibling tools like update_requisition_field or create_requisition.

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. The broad phrase 'for recruiting operations' provides no context about specific use cases, prerequisites, or situations where another tool would be more appropriate.

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