Change job status via dedicated endpoint. Recommended for publish/unpublish/archive transitions and status automation workflows.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Job ID (numeric) or alias | |
| status | Yes | New job status (e.g. Draft, Public, Archived). See GET /taxonomy/statuses. | |
| include | No | Comma-separated related resources to embed: workflow, hiring_team, pipeline_stages |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate destructiveHint=true and readOnlyHint=false, correctly marking it as a modification. The description adds 'dedicated endpoint' but does not elaborate on side effects or dependencies. Without contradicting annotations, it provides minimal additional behavioral insight.
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?
Two sentences, front-loaded with the action, zero fluff. Every sentence adds meaning: the first states what it does, the second specifies when to use it.
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 simple status change tool with no output schema and good annotations, the description is nearly complete. It lacks prerequisites or return value hints, but these are not critical given low complexity.
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%, but the description adds value beyond schema: it clarifies 'id' accepts numeric or alias, provides examples for 'status' and references a taxonomy endpoint, and lists embeddable resources for 'include'. This enriches parameter understanding.
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 changes job status via a dedicated endpoint, distinguishing it from general job update. It specifies recommended use cases (publish/unpublish/archive transitions and status automation), making the purpose unambiguous.
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 explicitly recommends this tool for specific transitions and automation workflows, providing clear usage context. However, it does not mention when not to use it or suggest alternatives, which would strengthen guidance.
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.
