OmniSnap MCP

The page as text

read_page

Read-only

Extracts a page's text and heading outline so AI agents can answer content questions from readable text instead of screenshots.

Instructions

Returns the page's text and heading outline. Use this first when the question is what the page says rather than what it looks like: it costs a fortieth of a screenshot and a model reads a paragraph far more reliably than a picture of one. Reach for a capture when the question is visual.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "read_page"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Maximum characters.
`scope`	No	"page" prefers the main content region; "viewport" is only what is on screen.	page

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.3Nov 11, 2026

TDQS

A4.5/5.0

Behavior4/5

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered; the description adds genuinely useful behavioral context about cost ('a fortieth of a screenshot') and reliability of textual extraction. It omits what happens when the page text exceeds the limit (truncation behavior), which is the one operational detail an agent would still want.

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?

Three short sentences, front-loaded with the return value, then the decision rule, then the alternative. The cost comparison earns its place by making the tradeoff concrete; nothing is padded or repeated.

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 two-parameter, fully documented read-only tool with no output schema, the description covers purpose, return shape at a high level, cost profile, and the sibling it competes with. Nothing an agent needs in order to decide or call is missing.

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%, with limit and scope both documented in-schema including an enum explanation, so the baseline of 3 applies. The description adds no parameter-level meaning beyond what the schema already provides, such as how scope interacts with the returned heading outline.

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?

States a concrete verb and resource: 'Returns the page's text and heading outline.' An agent immediately knows this is a text-extraction read, and the framing of text-vs-visual separates it from capture_page and capture_element without needing to open either schema.

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

Usage Guidelines5/5

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

Gives an explicit selection rule ('Use this first when the question is what the page says rather than what it looks like') plus an explicit counter-rule ('Reach for a capture when the question is visual'). The when-to-use and when-to-use-something-else conditions are both present and unambiguous.

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