recall_similar_trades

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 key behaviors: it's a read-only retrieval tool (implied by 'Find past trades'), discloses the matching algorithm ('Uses OWM scoring... falls back to keyword matching'), and mentions the return format ('Returns trades with their reflections and outcomes'). However, it doesn't cover potential limitations like rate limits, error conditions, or authentication needs.

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 usage guidance, return details, algorithm explanation, and parameter semantics. Every sentence earns its place with no redundant information, making it efficient and easy 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's moderate complexity (4 parameters, similarity matching), no annotations, but with an output schema (which handles return values), the description is largely complete. It covers purpose, usage, behavior, and parameters effectively. The main gap is the lack of explicit safety or limitation disclosures (e.g., data availability constraints), which would be beneficial for a tool used in trading decisions.

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 description coverage is 0%, so the description must compensate. It provides meaningful context for all parameters: 'symbol' is explained as 'Trading instrument to filter by', 'market_context' as 'Current market conditions to match against', 'strategy_name' as 'Optional strategy filter', and 'limit' with its default value. This adds substantial value beyond the bare schema, though it doesn't detail format constraints (e.g., symbol syntax).

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 verbs ('Find past trades with similar market context') and distinguishes it from siblings by focusing on similarity matching for learning from past trades. It explicitly mentions what it returns ('trades with their reflections and outcomes') and how it works ('Uses OWM scoring when episodic memories exist, falls back to keyword matching'), making it highly specific and differentiated.

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 provides explicit guidance on when to use this tool ('Use this before making a trade to learn from past experience'), which clearly indicates its purpose in a trading workflow. It also implicitly distinguishes it from siblings like 'recall_memories' or 'get_trade_reflection' by focusing on similarity-based retrieval for decision support, though it doesn't name alternatives directly.

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