get_screenshot

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

With no annotations, the description fully discloses behavioral traits: synchronous capture, timing (50-200 ms), side effect (written to rolling buffer), and access constraints (no auth/rate limits, local only).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with clear section headers (USE WHEN, NOT FOR, ALTERNATIVES, BEHAVIOR, PARAMETERS). Every sentence adds value, no redundancy, and front-loaded with key action.

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

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

For a simple tool with one parameter and an output schema, the description covers all relevant aspects: purpose, usage, behavior, parameter, and return type (base64 PNG + metadata). No gaps.

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

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

Schema coverage is 0%, but description adds rich semantics: explains monitor_index as 0-based from get_monitor_summary, notes default behavior (capture cursor's monitor), and guides on usage (omit or pass None).

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states the verb 'Capture a screenshot' and specific resource 'active monitor' with details on resolution and output format. It distinguishes from sibling tools like get_screen_text by noting different use cases.

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

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

Explicitly lists when to use (pixel-level visual context) and when not (text extraction), names alternatives (get_screen_text, get_recent, get_context_at), and provides cost/benefit reasoning ('~5x cheaper in tokens').

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