remember_trade

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

With no annotations provided, the description carries the full burden and does well by explaining the tool's behavior: it's a write operation ('Writes to episodic memory'), has automatic updates to multiple memory layers, includes backward compatibility, and mentions default values (e.g., confidence default 0.5, timestamp defaults to now). It lacks details on error handling or rate limits, but covers core behavioral traits adequately.

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 appropriately sized and front-loaded with the core purpose in the first sentence. The parameter explanations are detailed but necessary given the 0% schema coverage. Some redundancy exists (e.g., repeating 'default' info), but overall it's well-structured with clear sections.

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's complexity (15 parameters, write operation, no annotations), the description is highly complete: it explains the tool's purpose, behavior, and all parameters in detail. The presence of an output schema means return values need not be explained, and the description adequately covers the input semantics and operational context.

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%, so the description must compensate fully. It provides detailed semantic explanations for all 15 parameters, including examples (e.g., 'XAUUSD'), clarifications (e.g., 'long' or 'short'), purposes (e.g., 'Improves OWM scoring quality'), and default behaviors (e.g., 'Auto-generated if omitted'). This adds significant value 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 specific action ('Store a trade') and resource ('OWM multi-layer memory'), and distinguishes it from sibling tools by specifying it writes to episodic memory and automatically updates semantic, procedural, and affective layers, plus backward compatibility to trade_records. This is more specific than generic storage tools like store_trade_memory.

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 usage context through the parameter explanations (e.g., 'Improves OWM scoring quality'), but does not explicitly state when to use this tool versus alternatives like store_trade_memory or recall_similar_trades. No explicit when-not-to-use guidance or prerequisites are provided.

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