smc_get_market_structure

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

Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description reinforces that it is a read operation ('Read market structure') and details the return format, adding value beyond annotations without contradiction.

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 concise, with two paragraphs: the first states the purpose, the second describes the return format. No unnecessary words, and key information is front-loaded.

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?

The description provides a pseudo-schema for the JSON return, which is helpful given an output schema exists. However, it fails to explain the parameters, which are numerous and have no schema descriptions. For a tool with 5 parameters and 0% schema coverage, the description is incomplete.

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?

Schema description coverage is 0%, meaning the description does not describe any parameters. The input schema has five parameters (symbol, interval, limit, lookback, response_format) but the description only mentions the output. This is a significant gap for a tool with 0% schema coverage.

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 reads market structure, specifically swing points, BOS/CHoCH events, and trend bias. It distinguishes itself from sibling tools (e.g., smc_find_fair_value_gaps) by focusing on core structure rather than specific patterns.

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 implies use for obtaining overall market structure and directional bias. It does not explicitly state when to use or when not to use this tool versus alternatives, but the context of siblings and the description's focus on structure provides sufficient clue for an AI agent.

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