Get a notification email message (e.g. rejection email) by ID. Returns subject, body, sender, recipient, and schedule metadata. Use candidate messages list to discover notification message IDs.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Notification email message ID. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds behavioral context by listing the returned fields (subject, body, sender, recipient, schedule metadata), surpassing what annotations alone provide. No contradictions.
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 with no wasted words. The core action is front-loaded, and every sentence serves a purpose: describing the action, return value, and ID procurement.
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 read-only tool with full schema coverage and informative annotations, the description is complete. It explains what the tool does, what it returns, and how to get the required ID, leaving no gaps.
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% with the parameter 'id' described as 'Notification email message ID.' The description adds context by explicitly saying 'by ID' and connecting to ID discovery, but this is marginal given the schema already covers meaning.
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 uses a specific verb 'Get' and resource 'notification email message' (e.g., rejection email), clearly differentiating it from sibling tools like 'hires_get_message' which handles other message types. It also specifies the returned fields and hints at how to obtain IDs.
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 advises to 'Use candidate messages list to discover notification message IDs', providing a prerequisite for using this tool. However, it does not explicitly state when not to use it or contrast with related tools like 'hires_get_message'.
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.
