recall_memories

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

With no annotations provided, the description carries the full burden. It discloses behavioral traits such as scoring methodology (outcome quality, context similarity, etc.) and return format (ranked memories with score breakdown), but lacks details on permissions, rate limits, or error handling.

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 key information in the first paragraph, followed by a clear 'Args' section. Minor redundancy exists in listing scoring factors, but overall it's efficient with zero waste sentences.

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 (7 parameters, no annotations) and the presence of an output schema, the description is largely complete. It explains the scoring logic and parameter purposes, though it could benefit from more behavioral context like error cases or performance expectations.

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. It adds meaningful context for all parameters (e.g., 'symbol' as trading instrument, 'market_context' for matching, defaults for 'memory_types' and 'limit'), though it could elaborate on 'context_regime' enums or 'context_atr_d1' units.

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 ('Recall memories using OWM outcome-weighted scoring') and resources ('episodic and semantic memories'), distinguishing it from siblings like 'recall_similar_trades' or 'remember_trade' by specifying the scoring methodology and memory types.

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 for retrieving ranked memories based on scoring factors, but does not explicitly state when to use this tool versus alternatives like 'recall_similar_trades' or 'get_trade_reflection'. No exclusions or prerequisites are mentioned.

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