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Agent Einstein — Crypto & Market Intelligence

by io.emc2ai
OverviewDiscussionsAdmin

Content Integrity Scan

check_content_integrity
Read-onlyIdempotent

AI moderation of text you supply: a 0-10 quality score with a written rationale and a recommendation, or the list of yield vaults Einstein has scanned. [Paid: $0.05–$0.10 per call from your Einstein credit balance. Free alternatives exist for several of these — see list_einstein_capabilities.]

Input Schema

NameRequiredDescriptionDefault
kindNojudge = score the `content` you supply · vaults = list scanned vaults.judge
contentNoThe text to judge, for `judge`.

Output Schema

NameRequiredDescriptionDefault
skillNoWhich Einstein capability answered. These tools route onto one of many skills by an enum argument, so this names the branch that actually ran.
reasonNoWhy there is no analysis, when `available` is false.
analysisNoThe 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.
availableNoTrue 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.

  1. Changed3 schema fields changed
    • changedInput schema / properties / content / description
      Previous value: -"Content or vault identifier to assess."New value: +"The text to judge, for `judge`."
    • changedInput schema / properties / kind / description
      Previous value: -"judge = content quality · deep_scan = manipulation scan · vaults = list scanned vaults."New value: +"judge = score the `content` you supply · vaults = list scanned vaults."
    • changedInput schema / properties / kind / enum
      Previous value: -[
-  "judge",
-  "deep_scan",
-  "vaults"
-]New value: +[
+  "judge",
+  "vaults"
+]
  2. Changed1 schema field changed
    • 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"
+}
  3. Added

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already cover readOnly, idempotent, non-destructive and openWorld behavior, so the bar is lower. The description adds genuinely new behavioral context the annotations lack: the per-call cost, the credit-balance source, and the shape of the output (score + rationale + recommendation).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The core purpose is front-loaded, but the single run-on sentence awkwardly welds two unrelated operations together ('...recommendation, or the list of yield vaults...'), and the bracketed payment note is dense. It is compact but not cleanly structured.

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?

An output schema exists, so return values need not be detailed, and the description nonetheless sketches them. Cost, credit source, and mode routing are covered; only the absence of explicit when-to-use-vs-alternatives guidance keeps it from being fully complete.

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%, and the enum for `kind` is fully documented in the schema, so the baseline is 3. The description's 'text you supply' and 'vaults Einstein has scanned' restate what the schema already explains rather than adding format, length, or constraint detail.

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 gives a specific verb+resource: AI moderation of supplied text returning a 0-10 score with rationale and recommendation, plus a secondary 'vaults' listing mode. It is clear what the tool does, though the two unrelated modes are squeezed into one sentence and no sibling is named to disambiguate the tool within the crowded analysis toolset.

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?

It flags that the tool is paid ($0.05–$0.10 per call) and explicitly directs the agent to list_einstein_capabilities for free alternatives, which is real routing guidance. It does not, however, state when to prefer this tool over those alternatives or when each mode applies, leaving that to the schema.

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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