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arambarnett

robinhood-chain-mcp

by arambarnett

related_markets

Find markets and items exposed to an entity or topic, with exposure type, strength score, and reasons to inform decisions.

Instructions

Find the markets/items exposed to an entity or topic — prediction markets, tickers, or other tradeable/actionable items depending on the graph. Each item includes an exposure type, a 0-1 strength score, and human-readable reasons — the "connections to make better choices."

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
slugYesCanonical entity slug from lookup_entity, or a topic like "ai" or "elections"
limitNoMax items to return (default 15)
Behavior3/5

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

With no annotations, the description carries the burden. It discloses output structure and mentions the input relies on a canonical slug from lookup_entity, but does not discuss behavioral traits like rate limits, destructive nature, or authentication. Some transparency exists, but gaps remain.

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 description is concise at three sentences, with the primary purpose front-loaded. No extraneous information. It could be slightly more structured, but is effective.

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?

For a tool with 2 parameters, no output schema, and no annotations, the description is fairly complete: it explains the type of results and their components. Lacks edge-case or error information, but sufficient given the simplicity.

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 coverage is 100%, so the schema already describes both parameters. The description does not add extra meaning beyond the schema. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool finds markets/items exposed to an entity or topic, with specific output components (exposure type, strength score, reasons). It does not explicitly differentiate from sibling tools like entity_connections, but the purpose is unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It implies a dependency on lookup_entity but does not explain when to choose related_markets over entity_connections or entity_signals.

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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