hires_delete_company
Delete (soft-delete) a company — takes its public career site offline. Use for lifecycle control in partner tenancy management.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Company ID |
Delete (soft-delete) a company — takes its public career site offline. Use for lifecycle control in partner tenancy management.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Company ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations already declare destructiveHint=true and readOnlyHint=false. The description adds value by specifying that the delete is a 'soft-delete' and that it 'takes its public career site offline.' This provides behavioral context beyond the annotations, indicating the action is reversible and has a specific observable effect. No contradiction with annotations.
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 two sentences long and to the point. The first sentence states the action and its immediate effect, while the second provides usage context. Every sentence is informative, and there is no redundant or unnecessary information.
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 has a single parameter, no output schema, and rich annotations, the description covers the core aspects: action type (soft-delete), effect on career site, and recommended use case. It does not detail what happens to associated data (like jobs or candidates) or explicitly mention restoration, but the sibling tool 'hires_restore_company' implies reversibility. Overall, it is adequate for the tool's simplicity.
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?
Schema description coverage is 100%; the input schema includes a description for the 'id' parameter ('Company ID'). The tool description does not add any additional meaning or nuances about the parameter. Since the schema already documents the parameter adequately, a baseline score of 3 is appropriate.
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 action: 'Delete (soft-delete) a company — takes its public career site offline.' It uses a specific verb ('Delete'), identifies the resource ('company'), and explains the effect ('takes its public career site offline'). This distinguishes it from other sibling tools, such as hires_restore_company or hires_delete_application.
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 provides context: 'Use for lifecycle control in partner tenancy management.' This suggests the tool is intended for administrative scenarios where a company needs to be deactivated. However, it does not explicitly mention when not to use it or name alternatives, such as when restoration is needed. The context is clear but lacks exclusions.
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 have clearly distinct purposes due to specific entity and action combinations. However, with 133 tools, there is some overlap (e.g., multiple ways to move applications) and similar-sounding operations (e.g., batch_remove_tags vs remove_candidate_tag) that could cause confusion. The detailed descriptions help but the sheer number increases ambiguity.
All tools follow a consistent 'hires_verb_noun' pattern with snake_case. Verbs are descriptive (create, list, get, delete, update, batch) and nouns match the domain entities (candidate, application, job, etc.). No mixing of conventions like camelCase or inconsistent verb styles.
133 tools is excessive for a typical server scope. While a full-featured ATS requires many operations, this count suggests insufficient aggregation. Tools for similar entities (e.g., multiple update/delete variants) could be consolidated. The high number overwhelms the tool surface and increases complexity.
The tool set covers core CRUD operations for major entities (candidates, applications, jobs, companies, users, messages, forms, etc.) plus batch operations, webhooks, and advanced features like AI scoring and nurture campaigns. Minor gaps exist (e.g., no direct reporting/analytics tools), but most workflows can be executed.