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delete_feedback_template

Use Lever DELETE /feedback_templates/:id for recruiting operations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyNoOptional JSON 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.
actor_idYesLever user ID associated with this action when needed.
template_idYesLever template ID.

Schema Changelog

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

  1. First observed

TDQS

C2.2/5.0
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 fails to mention whether deletion is permanent, whether confirmation is required, any side effects, idempotency, or authorization needs. The description only points to an endpoint without explaining what happens when the tool is invoked.

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

Conciseness3/5

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

The description is a single sentence with no wasted words, so it is concise. However, the brevity sacrifices substance; it provides barely more than the tool name and endpoint. A concise but insufficient description is not ideal.

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 lacks an output schema and annotations, so the description must provide context about return values, success/failure behavior, and operational semantics. It does not. The description simply states the endpoint and parameterized context is absent, leaving the agent without enough information to safely and correctly use the tool.

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 have descriptions in the schema. The tool description adds no additional meaning beyond the schema, which is sufficient to meet the baseline. However, some parameter descriptions (e.g., body) are vague, but this is not the description's fault.

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

Purpose3/5

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

The description references the Lever DELETE endpoint and resource, but it reads more as a command to use the API than a functional statement of what the tool does. It distinguishes the resource (feedback templates) but does not clearly say 'deletes a feedback template' or describe the outcome. The verb is implied by the HTTP method, not explicitly stated.

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?

The description gives no guidance on when to use this tool versus alternatives (e.g., create_feedback_template, update_feedback_template) and no exclusions or prerequisites. The phrase 'for recruiting operations' is too generic to help an agent decide between deletion and other operations.

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