anki-workflow-mcp

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Validate Tables Field

validate_tables_field

Validates HTML table syntax, mobile screen constraints, and markdown table leaks, returning PASS/FAIL with diagnostics for Anki field content.

Instructions

Validate HTML table syntax, mobile screen constraints, and check for markdown table leaks. Returns {status: 'PASS'|'FAIL', diagnostics: list}.

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": {
      "html": "<html>"
    },
    "name": "validate_tables_field"
  }
}

Input Schema

Name	Required	Default
`row`	No
`face`	No
`html`	Yes
`field`	No	Notas Adicionais

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.3.1Nov 14, 2026

TDQS

B3/5.0

Behavior3/5

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

No annotations are supplied, so the description carries the behavioral burden. It discloses the PASS/FAIL status and diagnostics return contract, and 'validate' implies a non-mutating check, but it does not explicitly state read-only behavior, side effects, permissions, or error handling.

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?

Two tightly written sentences with the validation scope front-loaded and the return contract summarized afterward. There is no filler or redundancy, and every sentence contributes useful information.

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?

The output schema covers return values and the description names the validation checks, but with four input parameters, 0% schema description coverage, and no annotations, the definition is incomplete. An agent cannot confidently determine what 'row', 'face', and 'field' should contain or when this validator should be selected over siblings.

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%, so the description should compensate for parameter meaning. It only indirectly implies what 'html' contains; the roles of 'row', 'face', and 'field' are completely unexplained.

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 states a specific verb and resource: validate HTML table syntax, mobile screen constraints, and markdown table leaks. This clearly distinguishes it from image/tag field validators, though it does not explicitly name a sibling alternative.

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?

It implies use when validating a tables field, but gives no explicit when-to-use guidance, prerequisites, or alternatives such as sanitize_card_field or validate_batch. The agent must infer invocation context from the tool name alone.

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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