Run Python AST & Contrast Verification Suite

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

Annotation Contradiction: annotations declare readOnlyHint=true, but the description states that the tool 'does not mutate source files or modify disk state unless 'capture' is specifically invoked.' This explicitly opens a path to disk modification, contradicting the read-only annotation. The description also discloses useful environmental details (Python 3.10+, sandboxed subprocess), but the contradiction forces a score of 1.

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 well-structured with clear PURPOSE, BEHAVIOR, USAGE GUIDELINES, and RETURNS headings, and the purpose is front-loaded. It is somewhat longer than necessary because the alternatives are named twice and the action list is repeated from the schema, but the organization makes it easy to scan and each section earns its place.

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 complexity (5 parameters, 8 enum values, conditional requirements) and the presence of a rich output schema, the description is largely complete: it covers environment dependencies, sandboxing, read-only behavior, when to use vs. alternatives, and return structure. The only completeness gap is rooted in the read-only/capture contradiction, which is already penalized under behavioral transparency.

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 description coverage is 100%, so the parameter meanings are already fully documented in the schema. The description adds some contextual framing by explaining that returned outcomes depend on the invoked action)Skip and by repeating conditional use cases, but it does not add meaning beyond what the schema already provides. Baseline 3 is appropriate.

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 a specific verb ('Execute'), a specific resource (the Python ink_verifier suite), and the exact scope: deep AST static analysis, contrast matrix calculation, and headless layout audits. It also names the sibling alternatives it is not, so an agent can distinguish it from ink_validate_design and ink_audit_security without inspecting their schemas.

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 when-to-use guidance for deep Python AST analysis, explicit when-NOT-to-use guidance for fast CSS validation and client-side security audits, and names the alternative sibling tools. This is exactly the kind of decision routing an agent needs.

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