CineFlow Studio

cineflow_deepseek_status

Probe internal or local LLM servers to verify availability, available models, and CineFlow Studio topology before connecting filmmaking workflows.

Instructions

Probe and verify internal or local LLM server (DeepSeek, Qwen 2.5, Llama 3, Mistral via vLLM, Ollama, SGLang, llama-server) status, models, and studio topology (Topology 1: Single-GPU External LLM vs Topology 2: Dual-Server Internal Cluster).

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

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

Input Schema

Name	Required	Description	Default
`base_url`	No	Optional custom endpoint URL (e.g. 'http://127.0.0.1:11434/v1' or 'http://internal-llm:8000/v1').

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 15, 2026

TDQS

B3.2/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the full burden. "Probe and verify" plus the list of return subjects (status, models, topology) implies a read-only diagnostic and tells the agent what classes of information come back, but it never states read-only-ness explicitly, nor timeout/error behavior when a server is down, nor how a custom endpoint interacts with defaults.

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?

One sentence, front-loaded with the verb and resource, no filler. The two long parenthetical lists (model runtimes, topology variants) make it dense but they do convey capability scope rather than being redundant.

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

Completeness3/5

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

With no output schema and no annotations, the description does reasonably well by naming what is returned (status, models, topology) and the supported server types. However, it omits any return shape, failure behavior, or differentiation from the overlapping internal_llm_status sibling, which is a meaningful gap for a diagnostic tool in a crowded status family.

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?

The single parameter has 100% schema description coverage, with base_url already documented and an example URL format given. The description adds no additional meaning about overriding the configured endpoint, so the schema does all the work — baseline 3.

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?

Specific verb+resource: "Probe and verify internal or local LLM server ... status, models, and studio topology." An agent knows exactly what is checked (status, model list, topology layout) and what backends are covered (vLLM, Ollama, SGLang, llama-server). It loses a point because the near-identical sibling cineflow_internal_llm_status is never acknowledged, so the agent cannot tell the two apart from the definition alone.

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?

There is no when-to-use / when-not-to-use guidance and no named alternative. The enumeration of topologies (Single-GPU External vs Dual-Server Internal) hints at the scenarios covered, but leaves the agent to infer when this should be called instead of cineflow_internal_llm_status or cineflow_status.

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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