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bzsasson

Screaming Frog SEO Spider MCP Server

read_crawl_data

Read CSV export data from a previous crawl. Retrieve rows with pagination, offset, and optional filtering by column value using contains, exact, or regex modes.

Instructions

Read CSV data from an export. Use after export_crawl.

Args: export_id: The export_id from export_crawl file: CSV filename to read (from the file list in export_crawl output) limit: Max rows to return (default 100, max 1000) offset: Number of rows to skip (for pagination) filter_column: Optional column name to filter by filter_value: Optional value to match in the filter column filter_mode: How to match filter_value: "contains" (default, case-insensitive substring), "exact" (case-insensitive exact match), or "regex" (Python regex)

Returns: CSV data as formatted text with column headers.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
export_idYes
fileYes
limitNo
offsetNo
filter_columnNo
filter_valueNo
filter_modeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

With no annotations, the description details parameter behaviors including default values, max limit, and filter modes. It discloses that it returns formatted CSV text. It could add error handling or performance notes, but is largely transparent.

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 concise yet comprehensive, starting with purpose then a clean Args list. Every sentence adds value without redundancy.

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?

Given 7 parameters and no annotations, the description covers pagination, filtering, and output format. Missing details like error handling or encoding, but sufficient for its read operation.

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

Parameters5/5

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

The description explains all 7 parameters in detail, including the meaning of filter_mode values (contains, exact, regex). This fully compensates for the 0% schema description coverage.

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?

The description clearly states 'Read CSV data from an export. Use after export_crawl.' This specifies the exact action and resource, distinguishing it from sibling tools like export_crawl or crawl_site.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly instructs to use after export_crawl, providing a clear sequential usage context. However, it does not mention when not to use this tool or alternatives for similar tasks.

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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