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chat_send

Send a message to an active cloud architecture session and get a response with usage metrics. Use for design requests, modifications, or cost inquiries after creating a session.

Instructions

Send a message to an existing conversation session and get a response.

Returns {'response': str, 'spec': dict|None, 'usage': dict, 'cumulative_usage': dict}. spec is populated when the turn produced or modified an ArchSpec. usage reports LLM token counts for this turn; cumulative_usage totals across the whole session.

When to use: Every turn after chat_create_session. For zero-state single-shot calls use design_architecture / modify_architecture instead.

Behavior: Calls an LLM — incurs API costs proportional to the conversation history length (history grows each turn). Persists updated session state back to the session store.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_idYesSession handle returned by `chat_create_session`. Must reference an existing session; otherwise the tool returns `{'error': ...}`.
messageYesUser message for this conversation turn. Can be a design request, a modification instruction, a question about the current spec, or meta-commands (e.g. 'show me the cost').
Behavior5/5

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

Discloses that it calls an LLM with API costs, history growth, session state persistence, and error handling for invalid session. No annotations present, so description fully carries the burden.

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?

Well-organized with separate sections for purpose, return values, usage, and behavior. Every sentence is informative without redundancy.

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?

Despite no output schema, the description fully explains return format, error cases, cost implications, and side effects, making it complete for a conversational tool.

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

Parameters4/5

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

Schema already covers both parameters (100% coverage). Description adds examples for message and clarifies session_id requirement, providing extra value beyond schema.

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?

The description clearly states it sends a message to an existing session and gets a response. It distinguishes from siblings like design_architecture and chat_create_session by specifying when to use each.

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

Usage Guidelines5/5

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

Explicitly states 'When to use: Every turn after chat_create_session. For zero-state single-shot calls use design_architecture / modify_architecture instead.' Also implies prerequisite of an existing session.

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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