Skip to main content
Glama

OneQAZ Trading Intelligence

Sector Correlations

get_sector_correlations_tool
Read-onlyIdempotent

Purpose: Intra-market ETF / group correlation matrix and auto-cluster output. Quantifies structural co-movement (e.g. ARKK <-> QQQ) for diversification and sector-avoidance reasoning. Triggers (casual questions too): "which sectors move together?", "어떤 섹터끼리 같이 움직여?", "am I too concentrated?", "ETF 상관관계 보여줘", "is tech basically one trade right now?". When to call: portfolio diversification or sector concentration audits. Prerequisites: none. Next steps: get_symbol_peer_links_tool for per-symbol lead-lag inside a sector. Caveats: refreshed every 6 hours; 60-day lookback.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
top_kNoNumber of top pairs to return
market_idNocoin / kr_stock / us_stock. Aliases coin/kr/us and any letter case are accepted.us_stock

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
full_dataNo
timestampYesRFC3339 UTC, server build time
disclaimerYesCanonical compliance disclaimer (always present)
request_idYes32-hex per-response correlation id
is_real_moneyNo
data_classificationNo
is_investment_adviceNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / additionalProperties
      Added value: +false
  2. Changed2 schema fields changed
    • addedOutput schema / properties
      Added value: +{
      +  "data_classification": {
      +    "anyOf": [
      +      {
      +        "const": "research_information_only",
      +        "type": "string"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  },
      +  "disclaimer": {
      +    "description": "Canonical compliance disclaimer (always present)",
      +    "type": "string"
      +  },
      +  "full_data": {
      +    "anyOf": [
      +      {
      +        "additionalProperties": true,
      +        "description": "`full_data` for get_sector_correlations_tool — 실응답에서 추출(2026-09-23).",
      +        "properties": {
      +          "clusters": {
      +            "items": {},
      +            "type": "array"
      +          },
      +          "market_id": {
      +            "anyOf": [
      +              {
      +                "type": "string"
      +              },
      +              {
      +                "type": "null"
      +              }
      +            ],
      +            "default": null
      +          },
      +          "top_pairs": {
      +            "items": {},
      +            "type": "array"
      +          },
      +          "total_pairs": {
      +            "anyOf": [
      +              {
      +                "type": "integer"
      +              },
      +              {
      +                "type": "null"
      +              }
      +            ],
      +            "default": null
      +          }
      +        },
      +        "type": "object"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  },
      +  "is_investment_advice": {
      +    "anyOf": [
      +      {
      +        "const": false,
      +        "type": "boolean"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  },
      +  "is_real_money": {
      +    "anyOf": [
      +      {
      +        "const": false,
      +        "type": "boolean"
      +      },
      +      {
      +        "type": "null"
      +      }
      +    ],
      +    "default": null
      +  },
      +  "request_id": {
      +    "description": "32-hex per-response correlation id",
      +    "type": "string"
      +  },
      +  "timestamp": {
      +    "description": "RFC3339 UTC, server build time",
      +    "type": "string"
      +  }
      +}
    • addedOutput schema / required
      Added value: +[
      +  "disclaimer",
      +  "request_id",
      +  "timestamp"
      +]
  3. Changed3 schema fields changed
    • addedInput schema / properties / market_id / description
      Added value: +"coin / kr_stock / us_stock. Aliases coin/kr/us and any letter case are accepted."
    • addedInput schema / properties / market_id / enum
      Added value: +[
      +  "crypto",
      +  "kr_stock",
      +  "us_stock"
      +]
    • addedInput schema / properties / top_k / description
      Added value: +"Number of top pairs to return"
  4. Added

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/openWorld, so the safety profile is covered; the description adds genuinely useful non-structured context with data freshness ('refreshed every 6 hours') and scope ('60-day lookback'). These constrain how an agent should interpret the result, though response/pagination behavior is left to the output schema.

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?

Well front-loaded with labeled sections (Purpose, Triggers, When to call, Prerequisites, Next steps, Caveats). Slightly padded by the bilingual trigger examples, but that length serves trigger matching rather than being waste.

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 two-parameter read tool with a rich output schema, the definition covers purpose, usage triggers, prerequisites, freshness caveats, and a next-step handoff. Nothing an agent needs to select or invoke it correctly is missing, and return values are legitimately delegated to the output schema.

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 both parameters (top_k, market_id with enum + aliases) are fully documented in the schema. The description adds no syntax, defaults, or semantic nuance beyond the schema, so 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?

States a specific resource and scope: 'Intra-market ETF / group correlation matrix and auto-cluster output', explicitly quantifying structural co-movement with a concrete example (ARKK <-> QQQ). The 'intra-market' framing implicitly separates it from the sibling get_cross_market_correlation, so an agent can place it without opening either schema.

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?

Gives an explicit 'When to call' (portfolio diversification or sector concentration audits), trigger phrasings, prerequisites ('none'), and a next step routing to get_symbol_peer_links_tool. It lacks an explicit negative case (e.g. 'for cross-market, use get_cross_market_correlation instead'), which keeps it just below a 5.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.