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Delete a sci-bot conversation

scibot_delete_conversation

Delete a specific conversation permanently from your Sci-bot account by providing its conversation ID, ensuring unwanted scientific queries and answers are removed from account data.

Instructions

Permanently deletes one conversation of the signed-in account.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesConversation id from scibot_conversations.

Schema Changelog

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

  1. First observedv0.2.1

TDQS

A3.6/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It clearly states the operation is permanent ('Permanently deletes') and scoped to the signed-in account, which are important destructive and auth-related traits. It doesn't mention cascading effects on related data or behavior for invalid ids, but the core side effect is disclosed.

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?

A single, well-formed sentence delivers the action, scope, and permanence without filler. The most critical information is front-loaded.

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

Completeness4/5

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

For a simple one-parameter delete tool with no output schema, the description covers the essential details: what is deleted, whose data is affected, and that it is permanent. It falls slightly short on describing related-data consequences and alternative routing, but is generally complete enough for correct invocation.

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?

The input schema already documents the single parameter thoroughly, including that id comes from scibot_conversations. The description adds no extra parameter-level meaning, but because schema description coverage is 100%, the baseline score of 3 is appropriate.

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 uses a specific verb ('deletes'), names the resource ('conversation'), and adds useful scoping ('one', 'signed-in account'). It is clearly distinguishable from siblings like scibot_delete_question, though it does not explicitly call out alternatives.

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?

There is no guidance on when to use this tool versus alternatives such as scibot_delete_question or scibot_conversations. The use case is only implicit from the name and description, with no explicit conditions, exclusions, or prerequisites.

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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