Develop Instrument

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

Annotations already declare readOnlyHint=true and openWorldHint=false, establishing safety. The description adds behavioral depth by disclosing the methodology: it walks the DeVellis sequence, includes item-writing rules, response-format choice, reliability/validity strategy, and total-survey-error control for quantitative work, and a trustworthiness plan for qualitative work. This goes beyond a simple 'develops instrument' claim, though it does not disclose potential limitations (e.g., that it only produces plans, not statistical validation).

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 tightly written with no filler. The first sentence states the core purpose; the second explains quantitative/qualitative behaviors; the third clarifies an alternative usage. All sentences contribute directly to understanding, and the structure is logical and front-loaded.

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 complex generative tool, the description reasonably covers both major modes (quantitative/qualitative) and the critique path. It implies the outputs (draft instrument, interview guide, plans) without needing to detail them, especially since there is no output schema. It could be more complete by explicitly noting that the tool produces a written instrument plus a validity/reliability plan, but the description is sufficiently sufficient given no output schema and good parameter documentation.

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% with parameter descriptions, giving a baseline of 3. The tool description adds extra semantics by explaining that 'mode' changes the underlying methodology (quantitative vs qualitative) and that 'existing_items' can be provided for critique rather than starting fresh. This reinforces and expands on the schema descriptions, providing genuine added value.

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 'Draft or critique a measurement instrument' and enumerates concrete types (survey/scale, interview protocol, observation schedule), making the tool's purpose unambiguous. It also differentiates from siblings by focusing specifically on instrument development with reliability/validity planning, rather than study design or analysis.

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 clearly indicates when to use the tool: when drafting or critiquing an instrument, and even distinguishes between quantitative (DeVellis sequence) and qualitative (trustworthiness plan) approaches. It also mentions the 'provide existing items to critique' usage scenario. However, it does not explicitly name sibling alternatives or state when NOT to use this tool, so it falls short of full exclusion guidance.

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