Skip to main content
Glama

create_chat_completion

Read-only

Run a one-shot, non-streaming chat completion on MisarDev's OpenAI-compatible model API. model='misar-online' grounds the answer in the web with citations; omit model for the default coding model. Spends model credits.

Input Schema

NameRequiredDescriptionDefault
modelNoModel id; 'misar-online' or 'misar-search' for web-grounded answers
messagesYesOpenAI-style messages: [{ role: 'system'|'user'|'assistant', content: string }]
max_tokensNoMaximum tokens to generate
temperatureNoSampling temperature

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

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

Adds real information beyond the annotations: the call is one-shot and non-streaming, and it 'Spends model credits' — a cost signal the readOnlyHint annotation does not convey. It does not mention authorization requirements or rate limits, but against annotations that already state openWorldHint and non-idempotency this is solid.

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?

Three short sentences, front-loaded with the operation and mode, followed by model routing and cost. Nothing is redundant and every sentence carries a decision-relevant fact.

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?

Covers mode, model routing, and cost for a 4-parameter tool with no output schema. The remaining gap is the response shape — the agent is told citations appear but not how the completion and citations are returned — which is minor but not fully covered.

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 coverage is 100%, so the baseline is 3; the description earns above that by explaining the effect of omitting model (default coding model) and that 'misar-online' yields web grounding with citations. It still says nothing about temperature or max_tokens behavior, which the schema only names.

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 ('Run a one-shot, non-streaming chat completion') against a named provider API, and the non-streaming qualifier tells the agent the execution mode. It does not differentiate itself from the sibling web_search tool, which overlaps in purpose, so it stops short of 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?

Gives model-selection guidance ('misar-online' for web-grounded answers, omit for the default coding model), which is useful invocation context. However it never says when to prefer this tool over the sibling web_search, nor when streaming or task-specific alternatives should be used; usage is only implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.