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analyze_funding

Analyzes air quality funding data to identify trends and allocations, with optional filters for specific cities or years.

Instructions

Analyze air quality funding data.

Args: city: Optional city to filter by year: Optional year to filter by

Returns: Funding analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNo
yearNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries full burden for behavioral disclosure. While 'Analyze' suggests a read operation, it doesn't clarify what type of analysis is performed, whether it requires specific permissions, what format the analysis takes, or any limitations. The description is too minimal for a tool with no annotation coverage.

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

Conciseness4/5

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

The description is appropriately concise with a clear purpose statement followed by parameter and return sections. However, the 'Returns' section is redundant since an output schema exists, and the parameter documentation is insufficient given the 0% schema coverage.

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

Completeness3/5

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

The description is incomplete for a tool with no annotations and 0% schema coverage. While an output schema exists (reducing the need to describe return values), the description fails to adequately explain the tool's behavior, parameter usage, or differentiation from siblings. It's minimally viable but has significant gaps.

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

Parameters2/5

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

Schema description coverage is 0%, so the schema provides no parameter documentation. The description only lists parameter names ('city', 'year') without explaining their purpose, format requirements, or constraints. It doesn't compensate for the complete lack of schema documentation, leaving parameters essentially undocumented.

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

Purpose3/5

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

The description states 'Analyze air quality funding data' which provides a clear verb ('analyze') and resource ('air quality funding data'), but it's somewhat vague about what specific analysis is performed. It doesn't distinguish this tool from potential sibling tools like 'plot_funding_trend' or 'compare_cities' that might also analyze funding data in different ways.

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?

The description provides no guidance on when to use this tool versus alternatives. With siblings like 'plot_funding_trend', 'compare_cities', and 'query_table' that might handle similar data, there's no indication of when this specific analysis tool is appropriate versus those other options.

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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