whale-insights

analysts_signals_all

Read-onlyIdempotent

All analysts' signal history in one request (public, free-tier, MCP-compatible) — Returns the last 7 days of signals for all 10 analysts grouped by analystId in a single response — ideal for AI agents that need a cross-analyst comparison without 10 round-trips. Analyst ids in the response: chain_hawk (ChainHawk, BTC & macro), whale_watch (WhaleWatch, multi-chain whales), alpha_scout (AlphaScout, emerging tokens), defi_pulse (DeFiPulse, DeFi/stables/bridges), quant_edge (QuantEdge, signal risk/convergence). Always free-tier depth (last 7 days, up to 200 signals per analyst). No authentication required. No query parameters needed. Response: { results: { [analystId]: signals[] }, tier: 'free', updatedAt }. Each signal: id (number), tokens (array), typeLabel, outcome ('win'|'loss'|null), returnPct (null if unresolved), createdAt (ISO-8601), analystId. To fetch a subset of analysts, use GET /api/public/analysts/signals?id=chain_hawk,whale_watch. — Use this for all analyst signals in one response; use analysts_sign

Input Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Output Schema

TableJSON Schema

Name	Required	Description
`tier`	No	Always 'free' for this public endpoint
`results`	No	Keys are analyst slugs (chain_hawk, whale_watch, alpha_scout, defi_pulse, quant_edge); values are arrays of signal objects.
`updatedAt`	No
`attribution`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedSep 3, 2026

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "properties": {
+    "attribution": {
+      "$ref": "#/components/schemas/Attribution"
+    },
+    "results": {
+      "description": "Keys are analyst slugs (chain_hawk, whale_watch, alpha_scout, defi_pulse, quant_edge); values are arrays of signal objects.",
+      "properties": {
+        "alpha_scout": {
+          "items": {
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "chain_hawk": {
+          "items": {
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "defi_pulse": {
+          "items": {
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "quant_edge": {
+          "items": {
+            "type": "object"
+          },
+          "type": "array"
+        },
+        "whale_watch": {
+          "items": {
+            "type": "object"
+          },
+          "type": "array"
+        }
+      },
+      "type": "object"
+    },
+    "tier": {
+      "description": "Always 'free' for this public endpoint",
+      "type": "string"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}

AddedJun 19, 2026

TDQS

A4.7/5.0

Behavior5/5

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

Beyond annotations, the description discloses free-tier depth, the 7-day window, up to 200 signals per analyst, lack of authentication, and the exact response envelope. This goes well beyond the readOnly/idempotent hints and gives an accurate model of runtime behavior.

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

Conciseness4/5

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

The purpose is front-loaded and the description packs in meaningful details like response fields, auth, and alternatives. It is one long flowing paragraph with some redundancy (last 7 days repeated twice), but not wastefully long for the amount of context provided.

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?

Covers auth, scope, response format, signal fields, and the alternative subset endpoint. It is slightly incomplete because it claims to list analyst IDs but only enumerates 5 of the 10, and the final sentence is cut off; still, the core calling context is fully explained.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters and the schema already reflects that, so the baseline is 4. The description adds useful confirmation that no query parameters are needed, which removes any ambiguity about optional inputs.

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?

Clearly states it returns all analysts' signal history in one request, covering the last 7 days for all 10 analysts grouped by analystId. It distinguishes itself from a subset endpoint and makes the resource and response shape explicit.

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?

Explicitly says this tool is for getting all analyst signals in one response and gives the alternative endpoint for fetching a subset of analysts. It also notes no authentication and no query parameters, so an agent knows exactly when to call it.

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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