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get_page_text

Extract plain text from a webpage, prioritizing article content for easy reading. Provide a tab ID to retrieve text without HTML formatting.

Instructions

Extract raw text content from the page, prioritizing article content. Ideal for reading articles, blog posts, or other text-heavy pages. Returns plain text without HTML formatting. If you don't have a valid tab ID, use tabs_context first to get available tabs. Output is limited to 50000 characters by default; if it exceeds the limit it is truncated with a note giving the full size.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tabIdYesTab ID to extract text from. Must be a tab in the current group. Use tabs_context first if you don't have a valid tab ID.
max_charsNoMaximum characters for output (default: 50000). Set to a higher value if your client can handle large outputs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
provenanceNo
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses the output type (plain text), the default output limit (50000 chars), and the truncation behavior including the note with full size. It does not cover all possible edge cases, but it provides substantial behavioral context for a read operation.

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 compact but information-dense: purpose, use case, prerequisite, and output limitation are each covered in a single sentence. No wasted words, and the most important information is front-loaded.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a text extraction tool with an output schema and 100% parameter coverage, the description provides all essential context: what it does, when to use it, how to handle missing tab IDs, and output limits/truncation. It is fully sufficient for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds value beyond the schema by clarifying that tabId should be obtained via tabs_context if unknown and by explaining the truncation behavior for max_chars, which the schema only states as a default.

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 opens with a specific verb and resource: 'Extract raw text content from the page,' and adds a distinguishing feature, 'prioritizing article content' and 'without HTML formatting.' This clearly differentiates it from sibling tools like read_page and find.

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 states when to use the tool ('Ideal for reading articles, blog posts, or other text-heavy pages') and instructs to use tabs_context first if no valid tab ID. It does not explicitly mention alternatives or exclusions, but the guidance is clear and practical.

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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