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Backtest360

by com.backtest360

get_ticker_info

Identity and data coverage for one symbol, in a single call.

    Metadata only — no market data, so no paid plan is needed. Returns the
    asset's identity (name, asset class, exchange, currency, and whether it
    is still active) together with a coverage summary for the given
    frequency: the available date range and an estimated bar count. Use it
    to confirm a symbol resolves and that the history you need exists before
    requesting a quote or a price fetch. For the precise per-frequency range
    use get_data_range.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
frequencyNodaily

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It clearly states metadata-only, no market data, no cost, and describes return fields (identity, coverage summary). Does not claim any destructive behavior, and the read-only nature is clear.

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?

Single paragraph, every sentence adds value: purpose, cost implication, return structure, usage guidance, sibling reference. Front-loaded with key info, no redundancy.

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 output schema exists, description covers return values adequately (identity fields and coverage summary). Missing error handling or behavior for invalid symbols, but for a metadata tool this is sufficient. Sibling differentiation helps completeness.

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 coverage is 0%, meaning description does not explain the parameters. While 'symbol' is self-explanatory, 'frequency' is not described (valid values, effect). Description mentions 'for a given frequency' but lacks detail to compensate for missing schema descriptions.

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?

Description clearly states verb+resource: 'Identity and data coverage for one symbol'. It distinguishes from sibling tools like 'get_data_range' and implies use before quote/price fetch. Specific and actionable.

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

Usage Guidelines4/5

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

Explicitly states when to use ('confirm a symbol resolves... before requesting a quote or a price fetch') and mentions metadata-only with no paid plan. Names an alternative tool ('get_data_range') for precise range, providing good context.

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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TDQS

A4.2/5.0
Disambiguation5/5

Every tool targets a distinct operation or resource: backtesting, comparison, macro data, reference catalogs, etc. Even similar tools like run_backtest and compare_backtests are clearly differentiated by purpose and inputs.

Naming Consistency4/5

Overall consistent verb_noun pattern in snake_case, with a few exceptions like engine_info (noun_noun) and export_backtest (verb_noun but less common verb). The pattern is predictable and aids agent selection.

Tool Count4/5

20 tools is slightly above the ideal range but justified by the breadth of the platform (backtesting, data retrieval, reference, export). Each tool serves a clear purpose without redundancy.

Completeness4/5

Covers the full backtesting lifecycle: strategy validation, data sourcing, backtesting, comparison, export, and reference lookups. Minor gaps exist (e.g., no explicit strategy persistence), but the core workflow is complete.

Resources