apply_effect

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

No annotations are provided, so the description bears full responsibility for behavioral disclosure. It describes a mutation ('Apply') but does not mention side effects (e.g., whether it overrides existing effects, requires permissions, or is reversible). This lack of detail is insufficient for an agent to understand the tool's impact.

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, fits in a few lines, and includes an explicit prerequisite, parameter description, return type, and example. The main sentence is front-loaded. However, the 'Args' and 'Returns' sections are somewhat redundant given the schema, but they don't add excessive length.

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?

With no annotations and only one parameter, the description covers the basic purpose and prerequisite but lacks details about return values (output schema exists but is not described), error cases, or behavioral context like whether the effect applies immediately or requires confirmation. It is adequate but not comprehensive.

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 single parameter, effect_id, has no description in the schema (0% coverage). The description adds minimal meaning: 'Effect number from the effect pool' and an example 'Apply effect 5'. This explains what the parameter represents but provides no constraints (e.g., valid range) or format details, leaving room for ambiguity.

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 action ('Apply a predefined effect') and the target ('to the current fixture selection'). It distinguishes from sibling tools like set_effect_speed which modify effect parameters rather than apply a stored effect. However, it could be more specific about what 'apply' means (e.g., start the effect, load parameters).

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 explicitly states a prerequisite: 'Fixtures must be selected first using set_fixture_value or create_fixture_group.' However, it does not provide guidance on when to use this tool versus sibling effect-modification tools (like set_effect_speed), nor does it mention when not to use it or list alternatives.

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