memoire

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 and does so comprehensively. It explains error behavior (returns isError if token not found), partial success scenarios (local update succeeds even if Figma push fails silently), and verification requirements (capture screenshot to verify push). It also clarifies that only provided modes are updated while others are preserved.

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 clear sections: purpose, prerequisites, return behavior, error handling, and usage guidance. Every sentence earns its place by providing essential information without redundancy. The information is front-loaded with the core purpose immediately stated.

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 (mutation with optional remote sync, 3 parameters, no annotations, no output schema), the description provides complete context. It covers purpose, prerequisites, parameters, behavior, error handling, success confirmation, and sibling tool differentiation. The absence of an output schema is compensated by explaining the return format ('Plain confirmation string') and error indicators.

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?

While the input schema has 100% description coverage, the description adds valuable context about parameter semantics beyond the schema. It explains that 'name' must match get_tokens output, provides examples of token names, clarifies that 'values' performs a merge operation preserving other modes, and explains the practical implications of 'pushToFigma' default behavior and connection requirements.

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 with specific verbs ('update a design token value', 'push the change back to Figma') and identifies the resource ('local registry', 'Figma'). It distinguishes this tool from sibling 'sync_design_tokens' by explaining this is for single token overrides while that tool is for bulk mapping to Tailwind.

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 ('to apply a token override and optionally propagate it to Figma immediately') and when to use an alternative ('For bulk token mapping to Tailwind, use sync_design_tokens instead'). It also specifies prerequisites ('Token must already exist', 'plugin connection is also required') and error handling scenarios.

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