Create a company-scoped webhook subscription. Use for outbound company-level event integrations. Returns a signing_secret once — store it to verify the x-hires-signature-v2 header on incoming deliveries.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Company ID | |
| url | Yes | Webhook destination URL. Must be HTTPS and point to a public host (no localhost / private / link-local IPs). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=false, destructiveHint=false) already indicate mutation, but the description adds crucial context: the signing_secret is returned only once and must be stored for signature verification. This goes beyond 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?
Three concise, front-loaded sentences: purpose, usage, and a critical post-creation instruction. No unnecessary words, well structured.
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?
For a tool with no output schema, the description adequately covers the return value (signing_secret) and signature verification header. Two parameters are fully explained. Complexity is low, and the description is 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?
Schema covers 100% of parameters. The description adds concrete constraints for the 'url' parameter (must be HTTPS, public host, no localhost/private IPs), which is not in the schema description.
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 verb (create), resource (webhook subscription), and scope (company-scoped). It distinguishes from sibling 'hires_create_job_webhook' by explicitly specifying 'company-scoped'.
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 explicit usage context ('Use for outbound company-level event integrations') and post-creation guidance for storing the signing_secret. It does not include when-not-to-use or explicit alternatives, but the scope is clear.
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.
