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preset-mcp

preset-mcp

by Evan-Kim2028
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

validate_chart_render

Validate chart rendering by running a headless browser probe to catch front-end rendering errors before they reach users.

Instructions

Validate chart rendering with a headless browser (frontend-level probe).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "chart_id": "<chart_id>"
    },
    "name": "validate_chart_render"
  }
}

Input Schema

NameRequiredDescriptionDefault
chart_idYes
timeout_msNo
settle_msNo
response_modeNostandard

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.7.2

TDQS

C2.6/5.0
Behavior2/5

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

No annotations are present, so the description must fully disclose side effects, permissions, and behavior. It only mentions 'frontend-level probe', implying a read-only validation, but does not explicitly state that it has no destructive effects, performance impact, or failure modes.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely brief (one sentence), which ensures conciseness but sacrifices necessary detail. It is not structured to front-load key information like side effects or output format.

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?

Given the tool has 4 parameters (1 required), an output schema, and no annotations, the description is insufficient for an agent to understand full behavior, parameter interactions, and expected return values. It lacks completeness for safe and effective use.

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

Parameters2/5

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

Schema description coverage is 0%, and the description adds no additional meaning to the parameters. While parameter names are somewhat self-explanatory, the tool would benefit from explaining the role of timeout_ms, settle_ms, and response_mode beyond defaults.

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?

Description clearly states a specific action: validate chart rendering using a headless browser. However, it does not differentiate from sibling tools like validate_chart or validate_dashboard_render, leaving ambiguity about the exact scope.

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?

No guidance provided on when to use this tool versus alternatives such as validate_chart or validate_dashboard_render. The description lacks context for appropriate invocation.

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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