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zhugejun
by zhugejun

suggest_chart

Analyzes raw data and natural-language intent to select, render, and return the optimal chart with a rationale.

Instructions

Given raw data and a natural-language description of intent (e.g., 'show quarterly sales trends'), ChartOne's AI picks the best chart type and theme, renders the chart, and returns it with a rationale.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYes
widthNo
formatNopng
heightNo
user_intentYes
Behavior3/5

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

Discloses AI selection, rendering, and rationale. No annotations provided. Does not mention limitations, error handling, or potential side effects. Adequate but not comprehensive.

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?

Single sentence is concise and front-loaded with purpose. Could be more structured with separate parameter explanations, but overall efficient.

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?

Tool has 5 parameters, nested objects, AI decision-making, and output (chart image + rationale). Description is too brief to cover all aspects. No output schema. Missing details on output format, error scenarios, or constraints.

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?

Provides meaning for 'data' (raw data) and 'user_intent' (natural-language description). Schema description coverage is 0%, so description partially compensates. Optional parameters (width, height, format) are not explained.

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?

Description clearly states it picks chart type/theme, renders chart, and returns rationale. Verb 'picks' indicates AI selection. However, it does not explicitly distinguish from sibling 'render_chart', which likely renders a predefined chart type.

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?

Implies usage when you have raw data and need AI to choose chart. Sibling tool is listed but no guidance on when to use one over the other. No explicit when-not-to-use or alternatives.

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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