coaching_coaching_suggest_thresholds

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

With no annotations, the description must carry the behavioral burden. It discloses that the tool uses the user's past transaction records and that an LLM produces the suggestion with reasoning, but it does not explicitly state that the operation is read-only, whether permissions or existing history are required, or what happens on failure.

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 structured and front-loaded, with purpose first and Args/Returns sections afterward. It is appropriately sized for a one-parameter advisory tool, with only minor redundancy in restating the LLM analysis.

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 covers the core purpose, input examples, and a basic return shape, which is adequate for a simple advisory tool. However, with no annotations and no output schema, it should say more about prerequisites such as transaction-history availability and error behavior.

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?

The schema has one required parameter with 0% description coverage, so the description's Args section does add meaning by giving examples such as interest rates, FX, commodities, A-shares, and US stocks. It still does not define an enum or validation constraints for asset_class.

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 states a specific verb and resource: suggest numeric thresholds to trigger deep analysis. It also names the data source (past transaction records) and the asset-class scope, making the tool's intent clear, though it does not explicitly distinguish itself from sibling coaching tools.

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 use case is implied: analyze past trades to suggest a magnitude threshold for a given asset class. However, there is no explicit guidance on when to use this tool versus alternatives such as coaching_start_coaching or coaching_continue_coaching, so the agent must infer the context.

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