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Load deterministic demo chart

chart_load_demo

Reset the chart by generating deterministic synthetic OHLCV data for testing and onboarding.

Instructions

Reset the chart to deterministic synthetic OHLCV for testing and onboarding.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
seedNo
countNo
symbolNoDEMO:MARKET
intervalNo60
Behavior3/5

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

The annotations already declare destructiveHint=false and readOnlyHint=false. The description adds that the data is 'deterministic synthetic OHLCV', which clarifies it's a safe demo/reset function. However, the word 'reset' could imply destructive behavior, but it's consistent with the non-destructive demo purpose. No additional behavioral details like what gets cleared or what happens to existing data are disclosed.

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 a single, front-loaded sentence that directly states the action and purpose. It is concise and contains no fluff, earning full marks for efficiency.

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?

Despite having 4 parameters and no output schema, the description provides minimal context. It does not explain return values, the relationship between parameters and the generated data, or how this tool interacts with the chart state. For a testing/onboarding tool, the lack of parameter and behavior details makes it incomplete.

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

Parameters1/5

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

With 0% schema description coverage, the description was expected to compensate by explaining what seed, count, symbol, and interval do. It does not mention any parameters at all, leaving the agent with no understanding of how these affect the synthetic data generation. This is a critical gap.

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 uses specific verbs 'Reset' and 'load' with a clear resource ('the chart' and 'deterministic synthetic OHLCV'), indicating it loads demo data. This clearly distinguishes it from sibling tools like chart_import_csv (import real data) and chart_set_data (set specific data). The purpose is immediately clear.

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 phrase 'for testing and onboarding' provides some context for when to use this tool, but it does not explicitly state when not to use it or mention alternatives. No exclusions or comparisons to other chart_* tools are provided, leaving the agent to infer usage boundaries.

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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