Resonance Index

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

Annotations indicate readOnlyHint=true, and the description confirms this is a read-only computation. Beyond annotations, the description adds behavioral context by explaining the scoring logic and output structure, which helps the agent understand the tool's behavior without contradicting annotations.

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 concise and well-structured, front-loading the core purpose. Every sentence provides useful information: definition, thresholds, input format, output fields, and use cases. No wasted words.

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 and the presence of an output schema, the description fully covers what the tool does, what input it expects (with field details), and what output it returns. It leaves no significant gaps for agent understanding.

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 100%, so the schema already describes both parameters. The description reinforces the input structure by listing required fields (name, hex, archive, source, notes) and output fields, adding value beyond the schema without being redundant.

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 tool's purpose: scoring alignment between material origin and social consequence of colors. It provides specific score thresholds (1.00, 0.80, 0.50) and distinguishes it from palette generators, making the purpose highly specific and differentiating it from siblings.

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 lists explicit use cases (investigative reports, forensic briefs, museum content, editorial PDFs) and notes it as a key differentiator for Colour Memory. However, it does not explicitly mention when not to use or alternative tools, but the context is clear.

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