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backtest360-mcp

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by Backtest360

search_tickers

Search and resolve asset mentions to exact tickers. Filter by stocks, crypto, forex, or indices for precise identification.

Instructions

Search available assets by ticker or name (relevance-ranked).

Use to resolve a user's asset mention ("bitcoin", "S&P") to the exact ticker before requesting a server-side data fetch. asset_class filters to 'stocks', 'crypto', 'forex', or 'indices'.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo
queryYes
asset_classNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description discloses relevance-ranked search and acceptable values for asset_class. It does not cover pagination or error behavior, but given the existence of an output schema, the behavioral context is adequate.

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?

Two sentences plus a brief example, all front-loaded with the core purpose. No wasted words; highly efficient.

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?

For a search tool with an output schema, the description covers purpose, filter usage, and the typical workflow step. It is mostly complete, though it could mention case sensitivity or partial matching.

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 input schema has no descriptions (0% coverage), so the description adds essential meaning: query is a user mention, asset_class filters to specific values ('stocks', 'crypto', etc.), and limit has a default. This is sufficient but could elaborate on query format.

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 clearly states it searches available assets by ticker or name with relevance ranking, and specifies the use case of resolving user mentions to exact tickers before data fetch. This distinguishes it from siblings like list_tickers.

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?

The description explicitly instructs when to use the tool ('to resolve a user's asset mention... before requesting data'), implying it is a preliminary step. It does not explicitly state when not to use, but the guidance is clear.

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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