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bkuri
by bkuri

strategy_metadata

Retrieve metadata and version information for trading strategies to assess performance metrics, certification status, and testing results.

Instructions

Get metadata and version info for a strategy.

Args: name: Strategy name

Returns: Dict with strategy metadata including version, test_count, test_pass_count, certified status, and certification thresholds

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It partially compensates by detailing the return dictionary structure (version, test_count, certified status, etc.), which helps predict output. However, it lacks information about side effects, error handling (e.g., strategy not found), caching behavior, or whether this is a read-only operation.

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 uses a clean docstring format with distinct Args and Returns sections. Every sentence earns its place: one for purpose, one for parameter documentation, and one for return value structure. No redundancy or fluff is present.

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 has only one parameter and an output schema exists (per context signals), the description adequately covers the parameter and provides return value details. However, with zero annotations and no mention of error conditions or authentication requirements, there are gaps in operational context for an agent deciding whether and how to invoke the tool.

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?

Schema description coverage is 0%, requiring the description to compensate. The Args section provides 'Strategy name' for the 'name' parameter, which supplies basic semantic meaning absent from the schema. However, it lacks format constraints, examples, or clarification on whether this accepts display names, IDs, or file paths.

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 'Get[s] metadata and version info for a strategy' using a specific verb and resource. However, it does not explicitly differentiate from sibling tools like backtesting_read_strategy or strategy_analyze_optimization_impact, which could help the agent select the correct tool for metadata versus code inspection.

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 (e.g., when to check metadata before deployment versus when to run backtest_analyze_regimes). There are no prerequisites, conditions, or exclusions mentioned.

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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