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slidecold-mcp

by slidecold
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Python
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Get a conversation

get_conversation
Read-onlyIdempotent

Retrieve a conversation and all its messages in oldest-first order by ID. Marks unread inbound messages as read while returning their prior read status.

Instructions

Get a conversation. Required API key scope: conversations:read. GET /conversations/{id} Returns the conversation with all messages (oldest first). Side effect - marks unread inbound messages as read (the returned messages still show their prior isRead).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "id": "<id>"
    },
    "name": "get_conversation"
  }
}

Input Schema

NameRequiredDescriptionDefault
idYesPath parameter `id`.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4/5.0
Behavior5/5

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

Goes well beyond the annotations: it names the required API key scope (conversations:read), documents the response ordering (all messages, oldest first), and discloses a non-obvious side effect — unread inbound messages get marked as read while the returned payload still reflects the prior isRead value. That last detail is exactly the kind of behavior an agent could not infer from schema or annotations.

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?

Four short lines, front-loaded with purpose, then scope, endpoint, and behavioral caveat in a logical order. The opening "Get a conversation" restates the title, a small redundancy, but every other sentence carries distinct information.

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

Completeness5/5

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

With no output schema, the description still characterizes the return value (conversation plus all messages, oldest first) and warns about the read-status side effect. Auth scope and endpoint are also covered, leaving nothing essential for a correct call unstated.

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?

There is only one parameter and schema description coverage is 100%, so the schema already carries the meaning of `id`. The description adds the path form /conversations/{id} but nothing about id format or where to obtain it, so this is baseline performance.

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?

States a specific verb and resource ("Get a conversation") and pins down the exact endpoint GET /conversations/{id}, so the agent knows precisely which object is returned. It does not explicitly distinguish itself from siblings like list_conversations or update_conversation, which keeps it from 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 Guidelines3/5

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

The single-resource retrieval is implied by the required `id` and the endpoint, but there is no explicit when-to-use guidance (e.g., use list_conversations to find an id first, or use update_conversation to mutate). Usage is inferable rather than stated.

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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