Evaluate the strategy on the most recent bar only — no P&L, no stats.
Returns the latest signal (-1/0/1), which
condition slots fired, and the bar timestamp. Use for "what would this
strategy do right now" questions; use run_backtest for performance.
| Name | Required | Description | Default |
|---|---|---|---|
| strategy | Yes | ||
| execution | No | ||
| data_inputs | No | ||
| data_source | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses that it operates on the most recent bar only, no P&L, and no stats. Given no annotations, this is good but could mention side effects or read-only nature.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise, front-loads the core purpose, and uses a clear pattern to differentiate from run_backtest. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite having 4 complex object parameters and no schema descriptions, the description offers no parameter guidance. It is incomplete for an agent to correctly invoke the tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema has 4 parameters with 0% description coverage. The description does not explain any parameters or their structure, leaving agents to guess how to provide strategy, execution, data_inputs, or data_source.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states it evaluates the strategy on the most recent bar only, returning the latest signal (-1/0/1), condition slots, and timestamp. This clearly distinguishes it from siblings like run_backtest and compare_backtests.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says 'Use for "what would this strategy do right now" questions; use run_backtest for performance.' This provides clear guidance on when to use this tool vs. alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
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.
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.
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.
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.