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get_weather_page_content_israel

Extract visible text from the current weather page to get actual forecast data. Use after navigating to a city forecast to answer weather questions.

Instructions

Extracts and returns the visible text content of the currently open weather page. Call this after navigating to a city forecast to give the LLM the actual weather data.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does well: it discloses that the tool reads only visible text, depends on a currently open page, and should be invoked after navigation. It could add failure behavior for when no page is open, but the core stateful dependency is explicitly stated.

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?

Two sentences carry exactly the needed information: the first defines the operation, the second defines the invocation context. No filler or redundancy.

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 zero-parameter, read-only extraction tool with an output schema, the description is complete. It states the precondition ('after navigating') and the content scope ('visible text'), so an agent knows when and how to use it.

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?

The tool has zero parameters, so schema coverage is trivially 100% and the baseline is 4. No parameter documentation is needed, and the description appropriately focuses on the output content rather than inputs.

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 names a specific action ('Extracts and returns') and a concrete resource ('visible text content of the currently open weather page'). It also distinguishes this tool from siblings by emphasizing that it reads the visible page content after navigation, rather than fetching forecast data directly.

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?

The description gives clear timing context: 'Call this after navigating to a city forecast.' It does not explicitly list alternative tools or state when not to use it, so it misses the full when/when-not guidance, but the intended workflow is clear.

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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