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by com.cryptowhaleinsights
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analyst_archive

Read-onlyIdempotent

Analyst signal archive — paginated 1-year history (public, MCP-compatible) — Returns a paginated archive of signals attributed to a single analyst, covering up to 1 year (365 days). This is the MCP-tool-compatible variant of the analyst archive — it uses query params instead of path params so AI agents can call it directly without resolving a URL template. Analyst IDs: chain_hawk (ChainHawk, BTC & macro on-chain), whale_watch (WhaleWatch, multi-chain whale moves), alpha_scout (AlphaScout, emerging tokens), defi_pulse (DeFiPulse, DeFi/stables/bridges), quant_edge (QuantEdge, signal risk/convergence), rate_hawk (RateHawk, funding rates & derivatives), flow_tracer (FlowTracer, stablecoin & capital flows), unlock_guard (UnlockGuard, token unlock risk), sentiment_edge (SentimentEdge, social sentiment extremes), narrative_pulse (NarrativePulse, sector rotation & narratives). Filters: period (7d | 30d | 90d | 365d, default 90d), outcome (all | win | loss | neutral | pending, default all), page (1-indexed, default 1)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (1-indexed, default 1).
limitNoResults per page (10–100, default 100).
periodNoTime window: 7d | 30d | 90d | 365d (default 90d). Use 365d to access up to 1 year of history.90d
outcomeNoFilter by outcome: all | win | loss | neutral | pending (default all).all
analystIdYesAnalyst slug. Valid values: chain_hawk, whale_watch, alpha_scout, defi_pulse, quant_edge, rate_hawk, flow_tracer, unlock_guard, sentiment_edge, narrative_pulse.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoCurrent page number (1-indexed)
tierNoAlways 'starter' (up to 365-day depth) for this public endpoint
pagesNoTotal number of pages
totalNoTotal number of matching signals in the window
signalsNoSignals attributed to the requested analyst in reverse-chronological order.
analystIdNoEchoed analyst slug
updatedAtNo
attributionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "analystId": {
+      "description": "Echoed analyst slug",
+      "type": "string"
+    },
+    "attribution": {
+      "$ref": "#/components/schemas/Attribution"
+    },
+    "page": {
+      "description": "Current page number (1-indexed)",
+      "type": "number"
+    },
+    "pages": {
+      "description": "Total number of pages",
+      "type": "number"
+    },
+    "signals": {
+      "description": "Signals attributed to the requested analyst in reverse-chronological order.",
+      "items": {
+        "properties": {
+          "analystId": {
+            "description": "Analyst slug",
+            "type": "string"
+          },
+          "createdAt": {
+            "format": "date-time",
+            "type": "string"
+          },
+          "id": {
+            "description": "Unique signal row ID",
+            "type": "number"
+          },
+          "outcome": {
+            "description": "'win' | 'loss' | 'neutral' | null (pending)",
+            "nullable": true,
+            "type": "string"
+          },
+          "returnPct": {
+            "description": "Percentage-point return, e.g. 8.4 = +8.4%. Null if unresolved.",
+            "nullable": true,
+            "type": "number"
+          },
+          "tokens": {
+            "description": "Symbols involved, e.g. ['BTC']",
+            "items": {
+              "type": "string"
+            },
+            "type": "array"
+          },
+          "typeLabel": {
+            "description": "Human-readable signal type, e.g. 'Whale Move', 'Volume Breakout'",
+            "type": "string"
+          }
+        },
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "tier": {
+      "description": "Always 'starter' (up to 365-day depth) for this public endpoint",
+      "type": "string"
+    },
+    "total": {
+      "description": "Total number of matching signals in the window",
+      "type": "number"
+    },
+    "updatedAt": {
+      "format": "date-time",
+      "type": "string"
+    }
+  },
+  "type": "object"
+}
  2. Changed2 schema fields changed
    • changedInput schema / properties / analystId / description
      Previous value: -"Analyst slug. Valid values: chain_hawk, whale_watch, alpha_scout, defi_pulse, quant_edge."New value: +"Analyst slug. Valid values: chain_hawk, whale_watch, alpha_scout, defi_pulse, quant_edge, rate_hawk, flow_tracer, unlock_guard, sentiment_edge, narrative_pulse."
    • changedInput schema / properties / analystId / enum
      Previous value: -[
-  "chain_hawk",
-  "whale_watch",
-  "alpha_scout",
-  "defi_pulse",
-  "quant_edge"
-]New value: +[
+  "chain_hawk",
+  "whale_watch",
+  "alpha_scout",
+  "defi_pulse",
+  "quant_edge",
+  "rate_hawk",
+  "flow_tracer",
+  "unlock_guard",
+  "sentiment_edge",
+  "narrative_pulse"
+]
  3. Added

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the bar is lower. The description adds useful behavioral context beyond annotations: it is 'public', MCP-compatible, paginated, capped at 1 year of history, and uses query params for direct agent invocation. No contradiction with annotations is present.

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 description is front-loaded with its purpose and well-organized, but it contains redundancy: 'paginated 1-year history' is repeated as 'Returns a paginated archive ... covering up to 1 year (365 days).' The filter list also largely duplicates what the input schema already documents. It is still readable, but not every word earns its place.

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 tool with 5 parameters, 3 enums, and an output schema, the description covers the essential operational details: required analystId, all valid analyst slugs, filter options and defaults, page semantics, the 1-year history cap, and the public MCP-compatible access mode. Annotations cover safety, and the output schema covers return shape, so no critical detail appears missing.

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?

Schema coverage is 100%, so the baseline is 3. The description adds value by providing human-readable analyst labels (e.g., chain_hawk as 'BTC & macro on-chain', whale_watch as 'multi-chain whale moves') and clarifies that period 365d maps to the full 1-year cap. These enrichments go beyond the raw enum names and schema descriptions.

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 'Returns a paginated archive of signals attributed to a single analyst, covering up to 1 year (365 days).' It names a specific verb, resource, and scope, and explicitly highlights the single-analyst limitation, which separates it from all-analyst siblings like analysts_signals_all. The MCP-compatible query-param variant framing further distinguishes it from path-param alternatives.

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 when to use this tool: to fetch a single analyst's signal history, and specifically calls out that it is the MCP-compatible variant AI agents should use to avoid resolving URL templates. However, it does not explicitly say when NOT to use it in favor of related siblings such as analysts_signals, analyst_daily_summary, or signal_history_monthly, so it stops short of full alternative guidance.

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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