Skip to main content
Glama

get_table_data

Extract structured data from an HTML table by supplying a CSS selector. Returns headers mapped to cell values as JSON.

Instructions

Parse an HTML table into structured JSON with headers mapped to cell values. Returns {headers, rows, total_rows}.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_rowsNoMax rows to return (default: 100)
selectorNoCSS selector for the table (default: 'table')
session_idYesSession ID
Behavior2/5

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

No annotations provided, so description must disclose behavior. It mentions parsing into JSON but omits error handling (e.g., missing table), prerequisites (session must be navigated), and any side effects (likely none). Lacks details on CSS selector usage and max_rows handling.

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?

Very concise single sentence plus output format. Front-loaded with action and result. Could be slightly expanded without losing brevity.

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?

Adequate for a simple parsing tool, but lacks prerequisites, error cases, and return behavior for edge scenarios (e.g., no table found). No output schema to supplement.

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?

Schema coverage is 100%, providing descriptions for all three parameters. The tool description adds no additional parameter context beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly identifies the action ('Parse an HTML table') and output structure ('headers, rows, total_rows'), distinguishing it from sibling tools like find_element or get_page_elements.

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?

Implies use for extracting tabular data, but no explicit when-to-use, when-not-to-use, or alternative tools are mentioned.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/segentic-lab/periscope-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server