horus-flow-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns (detailed microstructure intelligence with specific fields), data source (Alpaca IEX feed), and operational constraints (market hours). It doesn't mention rate limits, authentication needs, or error handling, but provides substantial behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured and front-loaded with the core purpose, followed by detailed return values, operational notes, parameter explanation, and example usage. Every sentence adds value with zero wasted text, making it efficient for an AI agent to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has an output schema (which covers return values), the description provides excellent context: clear purpose, detailed behavioral information, parameter semantics, usage constraints, and an example. For a single-parameter tool with output schema, this description is comprehensive and complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage for the single parameter, the description fully compensates by providing clear semantics: it explains that 'symbol' represents a 'US stock ticker' and gives concrete examples (AAPL, NVDA, TSLA, MSFT). This adds essential meaning beyond the bare schema.

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

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

The description clearly states the tool's purpose with specific verb ('Get') and resource ('real-time institutional orderflow signal for a US equity stock'), distinguishing it from sibling tools like get_crypto_flow and scan_crypto_flow by specifying US equity focus. It provides concrete details about what intelligence is returned from the Alpaca IEX feed.

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

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

The description explicitly states when to use this tool ('US equity stock') and provides time constraints ('during market hours 14:30-21:00 UTC'), but doesn't explicitly mention when not to use it or name alternatives like the sibling crypto tools. The context is clear but lacks explicit exclusion guidance.

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