Agent Einstein — Crypto & Market Intelligence

Ask Einstein

ask_einstein

Read-onlyIdempotent

Open-ended crypto and DeFi analysis from Einstein's full research stack — use this when no more specific tool fits, or when the question spans several domains. Returns a written analysis grounded in live on-chain and market data. [Paid: $1.00 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
`prompt`	Yes	The question or analysis request, in plain language.

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

A4.5/5.0

Behavior4/5

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

Annotations already establish this as read-only, idempotent, and non-destructive. The description adds valuable behavioral detail: it costs $1.00 per call from the Einstein credit balance, returns 'a written analysis,' and grounds that analysis in 'live on-chain and market data.' This goes beyond the structured metadata without contradicting it.

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?

Three compact sentences, each earning its place: what it does, when to use it, and cost with an alternative pointer. The 'use this when' condition is front-loaded right after the main purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter, open-ended analysis tool, the description is complete: it covers purpose, when to use it, what the return looks like, data grounding, cost, and where to find cheaper alternatives. No critical operational detail is missing.

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?

The input schema already fully documents the single 'prompt' parameter with a clear description. The tool description adds only that the prompt is the 'question or analysis request,' which is marginal value since the schema already says 'The question or analysis request, in plain language.'

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 the tool's verb and resource: 'Open-ended crypto and DeFi analysis from Einstein's full research stack.' It distinguishes itself from the many specialized sibling tools by saying it is for when 'no more specific tool fits' or the question 'spans several domains.'

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

Usage Guidelines5/5

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

Usage guidance is explicit: use it as the default catch-all when specialized tools don't fit or for multi-domain questions. It also flags the paid nature and points to list_einstein_capabilities for free alternatives, giving clear decision 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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