list_archive_reasons
List Lever archive reasons, optionally filtered by hired or non-hired type.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| type | No |
List Lever archive reasons, optionally filtered by hired or non-hired type.
| Name | Required | Description | Default |
|---|---|---|---|
| type | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description must carry the full burden of behavioral disclosure. It only says 'list' and 'optionally filtered', but does not disclose whether the operation is purely read-only, if there is pagination, ordering, or any other behavioral traits. This is a minimal disclosure that does not sufficiently characterize the tool's behavior.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that includes the action, resource, and the relevant filtering option without any unnecessary detail. Every word serves a purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (one optional parameter, no output schema, no annotations), the description provides enough to understand the core functionality. However, it lacks any information about the return format, whether it returns all reasons when no filter is provided, or any potential caveats. For such a simple tool, this is adequate but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The description adds meaning to the 'type' parameter by explaining it is an optional filter for 'hired' or 'non-hired' types. This goes beyond the raw schema, which only provides the enum without context. The description effectively communicates the parameter's purpose and optionality.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool lists Lever archive reasons and mentions optional filtering by type. This is a specific verb+resource combination, and it distinguishes itself from the sibling get_archive_reason by being a list operation rather than a single-fetch operation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage context by noting the optional filter, but it does not explicitly state when to use this tool versus get_archive_reason or any alternatives. It provides no exclusions or when-not-to-use guidance, so it only gives implied usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.