Upload a file attachment to an application. Provide the file as base64-encoded data. Commonly used for signed documents and interviewer artifacts.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Application ID. | |
| file | Yes | File to upload. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate non-read-only and non-destructive nature. The description adds the requirement to provide base64-encoded data, which is useful but does not disclose other behavioral traits like file size limits, auth requirements, or return value. Partial transparency beyond schema and 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?
Two sentences with no wasted words. The first sentence states the core functionality; the second provides encoding format and typical use cases. Well-structured and easy to parse.
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?
The description covers the main purpose and input format but lacks information about the return value (e.g., attachment ID). Given no output schema, the description should ideally mention what the tool returns. Also missing prerequisites like whether the application must exist. Adequate for a simple upload tool but incomplete for a mutation.
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% and all fields have descriptions. The description reinforces the base64 encoding requirement but adds little new semantic meaning beyond the schema. The 'commonly used for' phrase provides context but not parameter-level detail.
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 ('Upload a file attachment') and the resource ('to an application'), and the use case ('signed documents and interviewer artifacts') distinguishes it from sibling tools like `hires_download_attachment` and generic uploads.
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 typical use cases ('Commonly used for signed documents and interviewer artifacts') but does not explicitly state when to use this tool vs alternatives such as `hires_upload_attachment` or `hires_upload_candidate_file`. Usage context is implied but not rigorously defined.
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.
