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system_ping

Verify server liveness with a ping, returning a pong and TouchDesigner frame. Choose detail and format (YAML/JSON) for health monitoring.

Instructions

Liveness canary. Returns pong + TD frame.

detail (str | None): full (default) | summary (long lists cut to 25 + count) | minimal (top-level scalars only).

response_format (str | None): yaml (default, token-cheap) | json.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
detailNo
response_formatNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.4.0
    • addedInput schema / properties / detail
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Detail"
      +}
    • addedInput schema / properties / response_format
      Added value: +{
      +  "anyOf": [
      +    {
      +      "type": "string"
      +    },
      +    {
      +      "type": "null"
      +    }
      +  ],
      +  "default": null,
      +  "title": "Response Format"
      +}
  2. First observedv0.2.0

TDQS

A3.7/5.0
Behavior3/5

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

With no annotations provided, the description carries the full behavioral disclosure burden. It does disclose the return shape ('pong + TD frame') and the output format options (yaml 'token-cheap' vs json), which is genuinely useful. However, it never states that the operation is non-mutating/safe, nor any auth or side-effect behavior; the read-only nature is only implied by the word 'canary.'

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?

The description is compact and front-loaded: the purpose ('Liveness canary. Returns pong + TD frame.') comes first, followed by two tightly-worded parameter lines. Every sentence earns its place, with no filler or repetition of schema field names.

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?

For a simple two-parameter, no-output-schema health check, the description covers the return content and both parameter behaviors thoroughly. Minor gaps remain: it doesn't explicitly assert non-mutation/safety (which would matter given zero annotations) and doesn't position itself against the neighboring system_info tool. Overall quite adequate for its complexity.

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 description coverage is 0%, so the description must fully compensate for the parameters — and it does. Both 'detail' (full/summary/minimal with the 25+count and top-level-scalars semantics) and 'response_format' (yaml default token-cheap vs json) are explained with their allowed values and defaults, adding meaning the bare schema cannot convey.

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 opens with 'Liveness canary' and 'Returns pong + TD frame,' giving a concrete verb-plus-resource statement that clearly identifies this as a health check. It is distinguishable from the bridge_* siblings (bridge_status, bridge_health), which are scoped to the bridge, but it does not explicitly separate itself from the similar sibling system_info, so the distinction is slightly incomplete.

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?

The phrase 'Liveness canary' and 'ping' in the name imply this tool is used to verify system liveness, but the description never explicitly states when to reach for it versus alternatives such as system_info or bridge_status. There are no named exclusions or alternative-routing cues, leaving the when-to-use decision mostly to inference.

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