Agent Einstein — Crypto & Market Intelligence

Strategy Backtest

run_backtest

Read-onlyIdempotent

Backtest a trading strategy on real historical data: describe rules in plain language for a custom event-driven backtest, run a standard strategy template, or optimize a strategy’s parameters. [Paid: $0.75–$2.00 per call from your Einstein credit balance. Free alternatives exist for several of these — see list_einstein_capabilities.]

Input Schema

TableJSON Schema

Name	Required	Description	Default
`kind`	No	custom (plain-language rules) · standard · engine · optimize.	custom
`asset`	No	Asset to backtest against.
`strategy`	Yes	Plain-language strategy description or template name.

Output Schema

TableJSON Schema

Name	Required	Description
`skill`	No	Which Einstein capability answered. These tools route onto one of many skills by an enum argument, so this names the branch that actually ran.
`reason`	No	Why there is no analysis, when `available` is false.
`analysis`	No	The written answer, identical to the result's text block. This is the field to read: the rest of the payload is whichever capability answered, and its shape varies by tool and by argument.
`available`	No	True when the analysis ran. False when it did not — no capability matched the arguments, the caller is out of credit, billing was unavailable, or the skill produced nothing. NOT a statement about the market.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 4, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "analysis": {
+      "description": "The written answer, identical to the result's text block. This is the field to read: the rest of the payload is whichever capability answered, and its shape varies by tool and by argument.",
+      "type": "string"
+    },
+    "available": {
+      "description": "True when the analysis ran. False when it did not — no capability matched the arguments, the caller is out of credit, billing was unavailable, or the skill produced nothing. NOT a statement about the market.",
+      "type": "boolean"
+    },
+    "reason": {
+      "description": "Why there is no analysis, when `available` is false.",
+      "type": "string"
+    },
+    "skill": {
+      "description": "Which Einstein capability answered. These tools route onto one of many skills by an enum argument, so this names the branch that actually ran.",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedAug 17, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already indicate readOnly, idempotent, and non-destructive behavior. The description adds the meaningful cost disclosure ('$0.75–$2.00 per call from your Einstein credit balance') and clarifies that it runs on historical data, which is useful behavioral context beyond the schema.

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 well-structured sentence that front-loads the core purpose, then efficiently lists supported modes and adds cost/alternative guidance. No filler or redundant repetition of the title.

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?

With an output schema present and annotations covering safety, the description is nearly complete: it explains the main invocation modes, mentions cost, and points to alternatives. The only minor gap is that it does not explain the 'engine' kind, but the schema already documents that enum value.

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 100%, so the baseline is 3. The description partially reinforces the meaning of 'strategy' and the 'kind' modes, but it does not add significant new meaning for parameters like 'asset' or the 'engine' kind beyond what the schema already provides.

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 states a specific verb ('Backtest') and resource ('a trading strategy on real historical data'), and explicitly enumerates the main modes: custom plain-language rules, standard template, and parameter optimization. This clearly distinguishes it from sibling analysis and forecasting tools.

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 gives clear context on what the tool does and notes that 'free alternatives exist for several of these', pointing to list_einstein_capabilities. It does not provide exhaustive when-not-to-use guidance, but it does alert the agent to cost and alternatives.

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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