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Assistant Manage Tool

assistant_manage

Manage AI assistant conversations by listing, retrieving, sending messages, or clearing them within the FleetQ MCP server.

Instructions

Manage AI assistant conversations. Actions: conversation_list, conversation_get (conversation_id), send_message (conversation_id, message), conversation_clear (conversation_id).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
actionYesAction to perform: conversation_list, conversation_get, send_message, conversation_clear
limitNoMax results (default 20, max 50)
conversation_idYesConversation UUID
messageYesThe message to send to the assistant
context_typeNoContext binding: experiment | project | agent | crew | workflow
context_idNoUUID of the bound context entity
Behavior2/5

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

Annotations are empty, placing full burden on description. Fails to disclose that conversation_clear is destructive, whether send_message triggers synchronous or async behavior, or what permissions are required. No mention of rate limits or pagination behavior for conversation_list despite 'limit' parameter existing.

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?

Highly concise single-line format. Action list with parenthetical parameters is efficiently structured, though bullet formatting would improve readability. No filler content, though brevity comes at cost of completeness.

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?

Inadequate for a polymorphic 6-parameter tool. Critical omissions: context binding parameters (context_type/context_id) usage unexplained, parameter requirements per action undefined (schema shows conflicting required fields), and no output format guidance despite lack of output schema.

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 coverage is 100%, establishing baseline 3. Description adds value by mapping parameters to actions (e.g., 'send_message (conversation_id, message)'), but omits context_type/context_id binding behavior and limit parameter usage entirely. Does not clarify that schema incorrectly marks conversation_id and message as universally required when they are action-specific.

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 specific verb 'Manage' and resource 'AI assistant conversations' clearly. Lists four specific actions available. However, with sibling tools like 'agent_manage' and 'chatbot_manage' present, it lacks explicit distinction of what constitutes an 'assistant' versus an 'agent' in this system.

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?

Lists available actions but provides no guidance on when to use this tool versus sibling alternatives (agent_manage, chatbot_manage). No mention of prerequisites, workflow sequencing, or when specific actions (like conversation_clear) should be preferred.

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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