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junetic

mcp-usercall

by junetic
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Remote

delete_study

Permanently delete a study and all associated data while releasing unused reserved credits.

Instructions

Permanently deletes a study and all associated data. Releases unused reserved credits.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
study_idYes

Implementation Reference

  • src/index.ts:202-213 (handler)
    The handler for delete_study tool, which calls the Usercall API with DELETE method.
    async (input) => {
  const payload = await callUsercallApi(
    `/api/v1/agent/studies/${input.study_id}`,
    { method: "DELETE" },
  );
  return result(
    appendNote(
      payload,
      "Study permanently deleted. All recordings and data have been removed. Unused credits have been released.",
    ),
  );
},
  • src/index.ts:199-201 (schema)
    Input schema for delete_study, requiring a UUID study_id.
    {
  study_id: z.string().uuid(),
},
  • src/index.ts:196-198 (registration)
    Registration of the delete_study tool.
    server.tool(
  "delete_study",
  "Permanently deletes a study and all associated data. Releases unused reserved credits.",

Tool Definition Quality

A3.8/5.0
Behavior4/5

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

With no annotations provided, the description carries full behavioral disclosure burden. It succeeds by warning of irreversibility ('Permanently'), scope of destruction ('all associated data'), and economic side effects ('Releases unused reserved credits'). Deducted one point for not indicating failure behavior (e.g., what happens if study_id doesn't exist).

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

Conciseness5/5

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

Two sentences, zero waste. Critical information ('Permanently') front-loaded. First sentence covers the core operation; second sentence covers the credit side effect. No redundancy or generic filler.

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

Completeness3/5

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

Covers the essential risks (destruction, credits) for a destructive tool with no output schema. However, missing error handling patterns (404 behavior), authorization requirements, or confirmation requirements prevents a higher score.

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

Parameters2/5

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

Schema description coverage is 0%, requiring the description to compensate. It fails to mention the study_id parameter, its expected format (UUID), or how to obtain it, even though this is the sole parameter. While somewhat inferable from the tool name, the description adds zero semantic value beyond the schema structure.

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

Purpose5/5

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

Excellent specificity: 'Permanently deletes' provides a precise verb, 'study' identifies the resource, and 'all associated data' clarifies scope. The description clearly distinguishes this from sibling tools like update_study (modification vs destruction) and get_* (read-only).

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

Usage Guidelines3/5

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

The word 'Permanently' implicitly signals this is for complete removal, not modification (update_study) or creation (create_study). However, it lacks explicit guidance on when to prefer deletion over archival, or prerequisites like 'study must be in terminal state'.

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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