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by io.github.tickerbot
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tickerbot_get_etf_sectors

Returns an ETF's sector weights, heaviest first. Always complete, since sector breakdowns are small. When the ticker is not an ETF, is_etf is false and sectors is empty.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tickerYesETF symbol. Case-insensitive.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
as_ofYesServer time this response was assembled (ISO 8601).
countYesSectors returned.
is_etfYesWhether the symbol is an ETF, from the instrument type on its ticker record.
tickerYesThe ETF you asked for.
sectorsYesSector weights, heaviest first, in the vendor's ETF-profile vocabulary.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "additionalProperties": false,
+  "properties": {
+    "as_of": {
+      "description": "Server time this response was assembled (ISO 8601).",
+      "type": "string"
+    },
+    "count": {
+      "description": "Sectors returned.",
+      "type": "number"
+    },
+    "is_etf": {
+      "description": "Whether the symbol is an ETF, from the instrument type on its ticker record.",
+      "type": "boolean"
+    },
+    "sectors": {
+      "description": "Sector weights, heaviest first, in the vendor's ETF-profile vocabulary.",
+      "items": {
+        "type": "string"
+      },
+      "type": "array"
+    },
+    "ticker": {
+      "description": "The ETF you asked for.",
+      "type": "string"
+    }
+  },
+  "required": [
+    "as_of",
+    "ticker",
+    "is_etf",
+    "count",
+    "sectors"
+  ],
+  "type": "object"
+}
  2. Added

TDQS

A4.3/5.0
Behavior5/5

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

With no annotations, the description fully discloses key behaviors: it guarantees completeness, specifies ordering, and handles non-ETF tickers by returning is_etf=false and empty sectors. This goes beyond the schema and provides essential edge-case context.

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?

The description is three short sentences, front-loaded with the main purpose, and includes only necessary behavioral details. No fluff 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?

For a simple read tool with a single parameter and an existing output schema, the description covers return content, ordering, completeness, and edge-case behavior. Nothing essential is missing for an agent to invoke it correctly.

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 schema already describes the ticker parameter as an ETF symbol and case-insensitive, so the description adds no additional parameter semantics. With 100% schema coverage, the baseline of 3 is appropriate.

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 purpose: returns an ETF's sector weights, ordered heaviest first. It also distinguishes itself from the sibling tickerbot_get_etf_holdings by focusing on sectors rather than holdings.

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 is implied – an agent would infer to use this when needing sector weight data for an ETF. However, the description does not explicitly mention when not to use it or suggest alternative tools like tickerbot_get_etf_holdings, leaving the selection somewhat to inference.

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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