get_emotion_pnl

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

No annotations are provided, so the description carries the full burden. It discloses the output grain (average PnL and win rate per mindset) and the grouping key (entry emotion), which is useful, but says nothing about permissions, whether data is scoped to the active account, or any latency/limit behavior.

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?

Purpose is front-loaded in the first sentence, the grouping behavior follows immediately, and the example questions are set off compactly with no redundant prose. Every element earns its place.

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?

With no output schema, the description must convey return semantics, and it does by stating average PnL and win rate per emotion. The lack of any note on account scoping or empty-result behavior is a minor gap, but an agent has enough to call it correctly.

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 100% with all three parameters (account, date_from, date_to) documented in the schema itself. The description only indirectly touches dates via the "for this month" example and adds no syntax or filtering nuance beyond the schema, so baseline 3 applies.

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?

States a concrete analytical operation: measuring how entry emotions (Fear, FOMO, Confident, Greedy, Calm, Anxious, Impatient) affect PnL and win rate by grouping trades by entry emotion. This clearly separates it from siblings like get_overview_stats, get_mistake_audit, and get_edge_by_market.

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 example questions give strong, concrete triggers ("Which emotion costs me the most money?", "Show my emotion PnL breakdown for this month") that map user intent directly to this tool. It does not, however, name an alternative tool or state when not to use it.

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