Parse an HTML table into rows and columns as JSON or CSV. Pure CPU, instant.
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": "html_table"
}
}| Name | Required | Description | Default |
|---|---|---|---|
| html | Yes | HTML containing a table |
Changes observed during successful MCP inspections.
Input schema / properties / htmlAdded value: +{
+ "description": "HTML containing a table",
+ "type": "string"
+}Input schema / requiredAdded value: +[
+ "html"
+]Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. 'Pure CPU, instant' usefully discloses that this is a local, fast operation with no network dependency, but it does not cover malformed-table handling, multiple-table behavior, or how JSON versus CSV output is selected.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences with zero waste. The core purpose is front-loaded, followed by a useful performance note.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple and the description covers the basic transformation, but it says output may be JSON or CSV without explaining how the caller selects the format, and no output schema exists to clarify the return shape. For a one-parameter parser this is adequate but leaves a notable call-time ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the single 'html' parameter is already documented as 'HTML containing a table.' The description mentions the resource is an HTML table but adds no further meaning about the parameter's expected structure or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Parse an HTML table' into rows/columns as JSON or CSV. This clearly distinguishes it from sibling converters such as csv_to_json or json_to_csv by naming the input type and output shape.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Usage is implied by the input type: call this when you have HTML containing a table and need structured rows/columns. However, it does not explicitly say when to use this versus alternatives like scrape or extract, nor does it mention exclusions or prerequisites.
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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