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isina-nej
by isina-nej

9router stream chat

nine_chat_stream

Streams a chat completion using the specified model and prompt, returning concatenated text output. Supports custom system prompts, max tokens, and timeout settings.

Instructions

SSE chat; returns concatenated text.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelYes
promptYes
systemNo
max_tokensNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

C2.6/5.0
Behavior2/5

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

Annotations are all false and thus provide no meaningful safety or behavioral signal. The description adds 'SSE' and 'returns concatenated text,' which tells the agent the tool streams and aggregates output, but it omits that this is an external AI call that may incur cost and latency. It also does not document timeout behavior, error handling, or what happens if the stream fails, despite a timeout_seconds parameter.

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?

The description is extremely concise, with no filler or repetition. The two phrasal fragments front-load the most important information: streaming via SSE and concatenated text output. However, the brevity borders on under-specification, leaving room for ambiguity about what 'SSE chat' actually executes.

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?

For a tool with 5 parameters, 0% schema coverage, neutral annotations, and a large sibling set including nine_chat, a one-line description is insufficient. It does not explain request execution, timeout behavior, output format beyond concatenation, or how it differs from alternatives. The output schema exists but does not compensate for the missing usage and behavioral guidance.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not explain any of the five parameters: model, prompt, system, max_tokens, and timeout_seconds. It provides no compensation for the missing schema descriptions. The chat context is a weak hint, but the description itself adds no parameter-level meaning.

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 names a specific resource ('chat') and states two key behaviors: transport via SSE and output form as concatenated text. This makes it reasonably clear that it is a streaming chat tool, and the name/title reinforce the distinction from non-streaming siblings like nine_chat. However, it lacks an explicit action verb, relying on the noun 'chat' and the tool name for the full picture.

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?

The description gives no guidance on when to use this tool versus the many sibling tools, especially nine_chat, nine_fanout, or nine_combos. It does not state conditions, alternatives, or when not to use it. The word 'stream' implies usage for streaming scenarios, but that remains implicit rather than explicit.

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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