pyxel-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's a non-executing validation tool (implied read-only/safe), performs AST parsing, checks for anti-patterns, and is optimized for speed. It doesn't mention error formats, rate limits, or authentication needs, but covers the core behavior well for a validation tool.

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 efficiently structured with a clear purpose statement upfront, followed by implementation details and speed comparison, ending with parameter documentation. Every sentence adds value: the first states what it does, the second explains how, the third provides usage context, and the fourth clarifies the parameter.

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's moderate complexity (validation with AST parsing), no annotations, 0% schema coverage, but presence of an output schema, the description is mostly complete. It explains purpose, usage context, and parameter meaning well. The output schema likely handles return values, so the description appropriately focuses on behavioral context rather than output details.

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?

With 0% schema description coverage for the single parameter, the description compensates by explaining 'script_path' as 'Absolute path to the .py script to validate.' This adds crucial semantic context beyond the schema's basic string type. However, it doesn't specify path format requirements or file existence expectations.

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 clearly states the specific action ('Validate a Pyxel script without running it') and resource ('.py script'), distinguishing it from siblings like 'run_and_capture' by emphasizing it's a pre-execution check. It explicitly mentions what it does (AST parsing, checking for anti-patterns) versus what it doesn't do (running the script).

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 provides explicit guidance on when to use this tool ('for catching syntax errors and obvious mistakes before execution') and when to use alternatives ('Much faster than run_and_capture'). It clearly differentiates from sibling tools by positioning it as a pre-execution validation step.

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