Factorial ATS Ops Control Plane

by app.vercel.ats-ops-control-plane-gateway

get_answer

Get one answer. Application answers for qualification and application-completeness analysis.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`id`	Yes	answer ID.
`include`	No
`query_json`	No	Additional documented query parameters, including bracketed filter keys.
`path_params`	No	Values for path placeholders such as {id} in a write operation.
`detail_profile`	No	operational (default) returns a compact recruiting-ops projection with names, prose, and other personal fields omitted; pass full to include the raw API payload with those fields.	operational

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

Changed3 schema fields changedJun 7, 2026

changedInput schema / properties / detail_profile / default
```
Previous value: -"full"New value: +"operational"
```

changedInput schema / properties / detail_profile / description

Previous value: -"full returns raw API payload; operational returns a compact recruiting-ops projection."New value: +"operational (default) returns a compact recruiting-ops projection with names, prose, and other personal fields omitted; pass full to include the raw API payload with those fields."

removedInput schema / properties / reason

Removed value: -{
-  "description": "Required when detail_profile=full.",
-  "maxLength": 500,
-  "minLength": 12,
-  "type": "string"
-}

First observedJun 5, 2026

TDQS

C2.9/5.0

Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of disclosing behavioral traits. It only states 'Get one answer' with no mention of safety, read-only nature, response format, error handling, or side effects. This is a significant gap for a tool with nested parameters and no output schema.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is very concise—two short sentences with no filler words. Both sentences contribute meaning (what it does and what domain it applies to). However, the extreme brevity leaves out critical usage and behavior details, preventing a 5.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 5 parameters, nested objects, no output schema, and no annotations, the description is woefully incomplete. It does not explain return values, when to use it, how parameters interplay, or distinguish from list_answers. The description provides only a minimal hint of purpose, leaving the agent under-informed for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 80% (high), so the baseline is 3. The tool description itself adds no parameter-level meaning beyond what the schema provides. The schema already covers most parameters, though 'include' lacks a description, and the tool description does not fill that gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get one answer,' specifying a single resource retrieval. It adds context with 'Application answers for qualification and application-completeness analysis,' clarifying the domain. However, it does not explicitly differentiate from sibling tools like list_answers or get_application, so it stops short of a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives. It neither names sibling tools nor provides contextual triggers, leaving the agent without direction on choosing get_answer over list_answers or other get_* tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

C2.8/5.0

Disambiguation5/5

Each get/list tool targets a distinct entity (answers, applications, candidates, etc.), and the generic api_request is clearly an escape hatch for undocumented endpoints rather than an overlapping tool. The singular/plural lists are unambiguous.

Naming Consistency4/5

Tools predominantly follow a consistent verb_noun snake_case pattern (create_x, get_x, list_xs, update_x, delete_x). Two outliers exist: api_request (noun_noun) and get_control_plane_capabilities (not a resource CRUD), but they are minor.

Tool Count2/5

At 39 tools, the server is heavily over-populated. Nearly every entity has both a get and list tool, and many CRUD combinations exist, but the count exceeds what is typically needed for an MCP server and could overwhelm agents.

Completeness4/5

The read surface is comprehensive with get/list for 13 entities, and write coverage for core resources (candidates, applications, feedback, job postings, webhooks). Missing delete operations and some create/update limits are acceptable for an ops control plane, though a direct update_application_phase would fill a gap.

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