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plot_funding_trend

Visualize funding trends across cities over time to analyze investment patterns and identify growth areas in financial data.

Instructions

Plot funding trends over years by city.

Args: cities: Optional list of cities to include title: Optional title

Returns: Base64 encoded plot.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
citiesNo
titleNo

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 the full burden of behavioral disclosure. It mentions that the tool returns a 'Base64 encoded plot', which is useful context about the output format. However, it lacks critical details such as what data source is used, whether it requires specific permissions, how it handles missing data, or any rate limits. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 highly concise and well-structured. It starts with a clear purpose statement, followed by brief but informative sections for 'Args' and 'Returns'. Every sentence earns its place, with no redundant or vague language. The information is front-loaded and easy to parse.

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?

Given the tool's complexity (plotting with parameters), no annotations, and an output schema that likely only specifies the Base64 string format, the description is minimally adequate. It covers the purpose and parameters but lacks context on data sources, error handling, or integration with sibling tools. The presence of an output schema reduces the need to explain return values, but more behavioral details would improve completeness.

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

Parameters4/5

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

The description adds meaningful context beyond the input schema, which has 0% description coverage. It explains that 'cities' is an 'Optional list of cities to include' and 'title' is an 'Optional title', clarifying their purposes and optional nature. This compensates well for the schema's lack of descriptions, though it doesn't specify format details (e.g., city naming conventions).

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

Purpose4/5

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

The description clearly states the tool's purpose: 'Plot funding trends over years by city.' This specifies the verb ('Plot'), resource ('funding trends'), and scope ('over years by city'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'plot_time_series' or 'plot_comparison', which might have overlapping functionality.

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 multiple sibling plotting tools (e.g., 'plot_time_series', 'plot_comparison', 'plot_hourly_pattern'), there's no indication of how this tool differs or when it's the appropriate choice. The agent must infer usage from the name and description alone.

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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