Create a reusable question with optional answer options for dropdown types. Used by forms and questionnaires.
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes | Question text | |
| type | Yes | Question type (from hires_list_question_types) | |
| options | No | Answer options (for select/multiselect question types) | |
| company_id | No | Target company ID (uses default company when omitted) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds context (reusable, for forms) but does not disclose behavioral traits like return value, permissions needed, or whether the question is immediately usable. Annotations are minimal, so the description carries burden but falls short.
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, front-loads the action, and contains no fluff. It efficiently communicates the core 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 4 parameters and no output schema, the description adequately explains the tool's role but misses details like the company_id context and the relationship to question types. It is adequate but not comprehensive.
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 coverage is 100%, so the description adds limited value. It mentions 'optional answer options for dropdown types' which aligns with the options parameter, but does not elaborate on constraints like options required for select/multiselect types.
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 ('create'), the resource ('reusable question'), and the context ('used by forms and questionnaires'). It distinguishes from siblings like update_question or delete_question.
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 mentions context but lacks explicit guidance on when to use this tool versus alternatives (e.g., inline question definitions in create_form). No prerequisites are stated, like needing to list question types first.
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.
