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get_city_dashboard

Get a web-quality dashboard for a US city, including audited site count, mean score, top and bottom performers, and niche breakdown.

Instructions

Get the small business web-quality dashboard for a US city. Returns audited site count, mean score, top/bottom performers, and niche breakdown.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYesUS city name (e.g. "Frisco", "Dallas", "Austin")
Behavior2/5

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

With no annotations, the description must carry behavioral transparency. It discloses what data is returned (audited site count, scores, etc.) but not any behavioral traits such as data freshness, computation method, or potential limitations. No mention of side effects, permissions, or error handling, leaving the tool's behavior underexplained.

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 two concise sentences, front-loading the purpose and then listing key return values. There is no redundant or unnecessary wording, making it highly efficient and easy to parse.

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

Completeness4/5

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

Given the tool's simplicity (one parameter, no output schema), the description covers the essential details: what the dashboard is for, its scope, and what it returns. The lack of output schema is compensated by the explicit return breakdown. Minor gaps exist around error handling or exact city matching, but these are not critical for a simple dashboard getter.

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?

The input schema provides full coverage for the single parameter 'city' with an example and description. The tool description adds no additional parameter semantics beyond what the schema already states, so the baseline 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 retrieves a city-level dashboard, with specific verb 'get' and resource 'small business web-quality dashboard'. It also lists the exact return contents (site count, mean score, top/bottom performers, niche breakdown), distinguishing it from siblings that focus on individual audits, comparisons, or redesigns.

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

Usage Guidelines3/5

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

The description implies the tool is for city-level analysis, not for auditing a specific website. It provides clear context ('for a US city') but does not explicitly mention alternatives or when to use other tools like audit_website or compare_websites. No exclusionary language is present.

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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