Agent Einstein — Crypto & Market Intelligence

Crypto Influencer Accuracy

get_analyst_accuracy

Read-onlyIdempotent

Scored track record of public crypto commentators and influencers whose calls Einstein has graded against what actually happened. Ranked by measured hit-rate, not follower count. Reports how many calls are graded versus still awaiting their horizon, and says plainly when the record is too thin to rank.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No	Maximum rows to return (1-25).

Output Schema

TableJSON Schema

Name	Required	Description
`rows`	No	One source per row.
`object`	No	Always "source-leaderboard".
`reason`	No	Why the payload is absent, when `available` is false.
`available`	No	False when this call has no data — a snapshot that is not warm yet, a domain switched off, or an argument that was rejected. NOT an error, and NOT a statement about the market.
`pending_calls`	No	Calls made but not yet resolvable.
`sources_tracked`	No	Sources with any graded call.
`sources_past_gate`	No	Sources that cleared the gate — the only ones whose rate means anything.
`reliability_gate_calls`	No	Graded calls a source needs before it is ranked.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "additionalProperties": true,
+  "properties": {
+    "available": {
+      "description": "False when this call has no data — a snapshot that is not warm yet, a domain switched off, or an argument that was rejected. NOT an error, and NOT a statement about the market.",
+      "type": "boolean"
+    },
+    "object": {
+      "description": "Always \"source-leaderboard\"."
+    },
+    "pending_calls": {
+      "description": "Calls made but not yet resolvable."
+    },
+    "reason": {
+      "description": "Why the payload is absent, when `available` is false.",
+      "type": "string"
+    },
+    "reliability_gate_calls": {
+      "description": "Graded calls a source needs before it is ranked."
+    },
+    "rows": {
+      "description": "One source per row.",
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "decayed_samples": {
+            "description": "Sample count after time decay."
+          },
+          "graded_calls": {
+            "description": "Calls graded so far."
+          },
+          "hit_rate": {
+            "description": "Hits ÷ graded calls, 0-1. Meaningless below the gate."
+          },
+          "hits": {
+            "description": "Calls graded correct."
+          },
+          "misses": {
+            "description": "Calls graded wrong."
+          },
+          "pending": {
+            "description": "Calls awaiting resolution."
+          },
+          "source_id": {
+            "description": "Stable source id."
+          },
+          "source_label": {
+            "description": "Display name."
+          },
+          "source_type": {
+            "description": "Kind of source."
+          },
+          "weight": {
+            "description": "Weight this source carries downstream."
+          }
+        }
+      },
+      "type": "array"
+    },
+    "sources_past_gate": {
+      "description": "Sources that cleared the gate — the only ones whose rate means anything."
+    },
+    "sources_tracked": {
+      "description": "Sources with any graded call."
+    }
+  },
+  "type": "object"
+}

AddedAug 17, 2026

TDQS

A4.3/5.0

Behavior5/5

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

Beyond the readOnly/idempotent/destructive annotations, the description discloses ranking criteria, that it reports both graded and pending-horizon calls, and that it will openly decline to rank thin records. This meaningfully informs the agent about output limitations and behavior.

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 purposeful sentences front-load the core purpose, then add ranking philosophy and output caveats. No filler or redundancy.

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?

The tool is simple: one optional parameter, no required fields, an output schema, and strong annotations. The description covers result interpretation, ranking methodology, and a key edge case (too-thin records), making it complete for correct invocation.

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?

Input schema coverage is 100%: the only parameter, limit, is already documented with default and range. The description adds no parameter-specific detail, so the baseline 3 applies.

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 resource—'scored track record of public crypto commentators and influencers'—and a clear evaluation method: calls graded against actual outcomes. It also distinguishes itself from popularity-based tools by saying 'ranked by measured hit-rate, not follower count,' which separates it from sibling social/sentiment tools.

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

Usage Guidelines3/5

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

Usage context is implied: an agent can infer this tool is for influencer accuracy, but the description gives no explicit when-to-use guidance, exclusions, or named alternatives. It is adequate but leaves the selection reasoning to the agent.

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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