validate

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds valuable behavioral context by specifying that the tool performs syntax checking and pattern recognition, which implies a non-executing, analysis-only behavior. This goes beyond what annotations state, though it stops short of detailing exactly what patterns are recognized or how results are reported.

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?

The description is a single, front-loaded sentence with zero filler. It wastes no words and communicates the core action and focus immediately, making it easy for an agent to parse and act on quickly.

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?

Given the tool has a single parameter and an output schema (which presumably documents the return structure), the description covers the essentials: what the tool does and on what input. It does not explain potential edge cases (e.g., handling of invalid syntax) but those are likely covered by the output schema. The description is sufficiently complete for a straightforward validation tool.

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?

The input schema has zero description coverage for its single parameter, so the description must convey parameter meaning. It does so by implication: the tool validates Python syntax, so 'script' is the Python code to be checked. However, it does not explicitly state that the parameter contains the source code, and gives no hints about expected encoding, length limits, or file references. This is adequate for a single simple parameter but not fully explicit.

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?

The description states a specific verb ('Check') and a clear resource ('Python syntax' and 'Pyxel code patterns'), which precisely distinguishes it from sibling tools like 'run', 'read_palette', and 'read_tilemap' that perform execution or read operations. An agent can immediately understand this is a validation tool, not a runtime or read tool.

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?

The description gives no explicit guidance on when to use this tool versus alternatives. It does not mention typical workflows (e.g., 'use before run'), nor does it reference any sibling tools, leaving the agent to infer usage context from the tool's name and purpose alone.

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