mcp_opendaw_set_effect_parameter_int

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It adds useful context by listing the covered fields, flagging the Delay 'version' field as internal, and clarifying its fallback status. However, as a mutating tool it does not disclose error behavior when parameter_name is invalid, whether changes are reversible/undoable, or range validation on the integer value — gaps that matter without annotation support.

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-organized and front-loaded: a one-sentence purpose, a compact bulleted list of covered fields, an explicit usage note, and a short parameter legend. Every sentence adds distinct value — the coverage list, the sibling-precedence note, and the 0-based clarification are all non-redundant.

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?

For a 4-parameter mutation tool with no annotations and an output schema, the description covers purpose, scope, alternatives, and all parameter meanings — quite thorough. The main missing piece is error/edge-case behavior (e.g., what happens with an unknown parameter_name or out-of-range value), which keeps it from being fully complete.

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 0%, so the description must fully compensate. It does so by explaining all four parameters, including the crucial clarification that effect_index is 0-based, concrete examples for parameter_name ('bandCount', 'bits', 'overSampling'), and the basic meaning of value and unit_index. This substantially exceeds the bare schema titles.

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 opens with a specific verb+resource statement ('Set an integer parameter on an audio effect') and goes further by enumerating exactly which device-specific integer fields it covers (bandCount, panningMixing, overSampling, bits, version). It also distinguishes itself from the generic float setter and the dedicated device-specific setters among its siblings, so an agent can unambiguously identify its role.

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 gives explicit guidance: device-specific tools (set_vocoder_band_count, set_fold_oversampling, etc.) are preferred when available, and this tool is a generic fallback for any Int32Field. It also explains what it covers versus the generic float setter, clearly stating when to use this tool and when to choose an alternative.

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