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calculate_ux_metrics

Compute key UX metrics like SUS, NPS, and task success rate from raw data. Obtain benchmark scores and interpretation for usability evaluation.

Instructions

Calculate key UX metrics and benchmarks. Computes SUS score, NPS, task success rate, and provides interpretation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
metric_typeYesType of UX metric to calculate
dataYesRaw data (e.g., 'SUS responses: 4,2,5,4,3,2,5,4,4,3' or 'NPS scores: 9,8,10,7,6,9,10')
Behavior2/5

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

With no annotations provided, the description carries full burden but only states it calculates and provides interpretation. It does not disclose whether it is read-only, any side effects, or how the output is structured. The lack of detail on behavior (e.g., data mutability, required permissions) reduces transparency.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise: two sentences, no filler. It front-loads the primary action and lists key metrics efficiently. Every word adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description should clarify what the tool returns (e.g., score values, benchmarks, interpretation text). It only vaguely says 'provides interpretation' without specifics. The data parameter format is hinted at in the schema description but not reiterated here. Completeness is insufficient for a tool with two required parameters.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the schema already describes both parameters. The description mentions metric types but does not add additional meaning beyond the schema's enum and descriptive property descriptions. Baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool calculates UX metrics and benchmarks, listing specific examples (SUS, NPS, task success rate). The verb 'Calculate' and resource 'UX metrics' are precise. It differentiates from sibling tools which focus on design analysis and accessibility, not metric computation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives or when not to use it. It only states what it does, leaving the agent to infer usage context. No exclusions or alternative tools are mentioned.

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

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