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glass_baseline_save

Save the current window as a named visual baseline for later diffing with glass_diff, enabling change detection without sending both before and after images. Baselines replace silently and persist until the server exits.

Instructions

Save the current frame as a named visual baseline — a reference image glass_diff and glass_wait_for_region later compare against, so you can ask what changed without spending image tokens on a before-and-after pair. Captures the whole window at call time (not a saved region), so settle the UI first if something is still animating. Saving over an existing name replaces it silently; baselines live outside the app under a per-server directory and last until the server exits, surviving glass_stop. Use this plus glass_diff to detect change; use glass_screenshot when you actually need to look at the pixels.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYesName to file this baseline under, reused by `glass_diff` and `glass_wait_for_region`. ASCII letters, digits, `-` and `_` only; saving over an existing name replaces it without warning.
Behavior5/5

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

No annotations are provided, so the description carries full behavioral disclosure. It reveals key traits: captures whole window, silently replaces existing baselines, persists under a per-server directory, survives glass_stop, and lives until server exit. This is rich, non-obvious behavior beyond a simple 'save' 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?

Three dense sentences with zero waste. The main purpose is front-loaded, and subsequent sentences add high-value context about animation, overwrite semantics, persistence, and alternatives. Every sentence earns its place.

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?

The tool is simple (one parameter, no output schema), and the description fully covers lifecycle, overwrite behavior, and comparison tools. It provides enough context for an agent to select and use the tool correctly without needing additional information.

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 description coverage is 100% for the single 'name' parameter, and the schema already explains naming constraints and overwrite behavior. The description adds no additional parameter-specific meaning beyond what the schema provides, so the baseline score of 3 is appropriate.

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 specific verb ('Save the current frame as a named visual baseline') and clearly distinguishes from siblings by referencing glass_diff, glass_wait_for_region, and glass_screenshot. This is a precise purpose statement that leaves no ambiguity.

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?

Explicitly says when to use this tool ('Use this plus glass_diff to detect change') and when not to ('use glass_screenshot when you actually need to look at the pixels'). Also gives context about settling the UI first if animating, providing clear operational guidance.

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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