add_effect

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Add effect to pattern' implies a mutation operation, but it doesn't disclose any behavioral traits: no information about permissions needed, whether the effect is reversible, rate limits, error conditions, or what happens to the pattern after the effect is applied. This leaves the agent with significant uncertainty about how the tool behaves.

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 extremely concise at three words, with no wasted verbiage. However, it's under-specified rather than efficiently informative—it lacks necessary context that would make it truly helpful. It's front-loaded but too minimal to be considered excellent.

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 complexity of a mutation tool with no annotations and no output schema, the description is incomplete. It doesn't explain what 'pattern' is, what effects are available, how parameters are formatted, or what the tool returns. The high schema coverage helps with parameters, but overall, the description fails to provide enough context for safe and effective use.

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 100% description coverage, with clear parameter descriptions: 'effect' (required, effect name) and 'params' (effect parameters). The description 'Add effect to pattern' adds minimal semantic value beyond the schema—it implies the tool applies an effect to a pattern, but doesn't clarify what 'pattern' refers to or provide examples of effect names or parameter formats. Given the high schema coverage, the baseline score of 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 'Add effect to pattern' is a tautology that essentially restates the tool name 'add_effect'. It doesn't specify what kind of effect, what type of pattern, or what domain this operates in (audio, visual, etc.). While it includes a verb ('Add') and resource ('pattern'), it lacks specificity and doesn't distinguish itself from sibling tools like 'remove_effect' or 'apply_scale'.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing an existing pattern), exclusions, or comparisons to sibling tools like 'remove_effect' or 'ai_enhance_pattern'. There's no context about appropriate scenarios or limitations.

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