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fahali_get_correlation_matrix

Get cross-asset correlation matrix from tail_dependence engine. Returns per-symbol market correlation, dependence strength, and contagion risk level.

Instructions

Get cross-asset correlation matrix from the tail_dependence engine. Returns per-symbol correlation with market, dependence strength, list of affected correlated symbols, contagion risk level, and timestamp. Covers the correlation and tail_dependence engines. Public data — no tier required.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations provided, so description must cover behavioral traits. It states the tool is a 'Get' operation (read), returns specific data, and is public. However, it does not mention side effects, latency, or rate limits. While sufficient for a simple read, more explicit safety info would improve clarity.

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 concise sentences: first specifies action and source, second enumerates return fields, third notes engine coverage and access. No redundancy, well-structured, and front-loaded with key purpose.

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?

Given no output schema, the description adequately details the return fields (correlation, dependence, affected symbols, etc.). It also clarifies engine coverage and access level. Lacks explicit structure format, but the list of fields suffices for a simple retrieval tool.

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?

No parameters exist, so the description carries no parameter burden. It effectively describes the output and engine coverage, adding value beyond the empty schema. Baseline for 0 params is 4, and it meets that.

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 retrieves a cross-asset correlation matrix from the tail_dependence engine. It lists specific return fields (per-symbol correlation, dependence strength, etc.) and mentions it covers both correlation and tail_dependence engines, distinguishing it from siblings like contagion maps or portfolio metrics.

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?

The description notes that data is public and no tier is required, but does not explicitly specify when to use this tool versus alternatives like fahali_get_contagion_map or fahali_get_portfolio_risk. It implies usage for correlation analysis but lacks direct 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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