Get a filled evaluation form with all answers. Returns evaluator info, summary score, summary text, and individual question answers. Use for detailed review of evaluator feedback on a candidate application.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Evaluation form ID |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true and destructiveHint=false, so the description does not need to repeat safety. It adds value by listing specific return fields (evaluator info, summary score, etc.), but does not disclose any behavioral traits beyond what annotations provide. The description is adequate but not extraordinary.
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: first states the action and return values, second provides usage context. Every sentence adds value; no redundancy or waste. Front-loaded with the key 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 a single parameter, clear annotations, and no output schema, the description is largely complete. It explains what the tool does, what it returns, and when to use it. Minor omission: could mention where to get the evaluation ID, but not critical.
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?
The input schema has 100% description coverage for the single parameter 'id' ('Evaluation form ID'). The description does not add any extra context about the parameter (e.g., how to obtain the ID), so it meets the baseline without exceeding it.
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 ('filled evaluation form'), and explicitly states the return contents (evaluator info, summary score, summary text, individual answers). It clearly distinguishes itself from sibling tools like hires_list_application_evaluations by focusing on a single evaluation's full details.
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 last sentence 'Use for detailed review of evaluator feedback on a candidate application' provides clear context for when to use this tool. It implies that this is for detailed review rather than listing, but it does not explicitly mention alternatives or when not to use it.
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.
