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CoinRithm

CoinRithm/coinrithm-agent-trading

Official

Get my performance

get_performance
Read-only

Retrieve the calling key's realized performance: total and per-venue PnL, trade count, win/loss/neutral counts, and win rate from closed paper trades.

Instructions

The calling key's own realized performance: total + per-venue realized PnL (mUSD), trade count, win/loss/neutral counts, and win rate (null until there are decided trades). Closed trades only — the scorecard for this agent. Paper trading only — virtual funds (50,000 mUSD). Not financial advice.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentTraceNoOptional private trace metadata stored in the caller's ledger.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
httpStatusYesHTTP status returned by CoinRithm, or 0 for network errors.
okYesTrue when CoinRithm returned a successful 2xx response.
ledgerEventIdNoPrivate AgentActionEvent id returned by /api/agent/*, when present.
ledgerStatusNoLedger write status header returned by CoinRithm, when present.
bodyNoParsed CoinRithm response body, or raw text when the response is not JSON.
Behavior4/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds key behavioral details: 'Closed trades only', 'Paper trading only', and the specific metrics included, which goes beyond annotation signals and clarifies the tool's scope.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences that front-load the main purpose, then add scope and disclaimer. No redundant words; every sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 100% schema coverage, useful annotations, and an existing output schema (per context signal), the description fully covers what the tool returns and its usage constraints. No missing critical information for an AI to select and invoke the tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% for the single optional parameter agentTrace, which is fully documented in the schema. The description adds no further parameter information, so baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states 'calling key's own realized performance' and enumerates specific metrics (realized PnL, trade count, win/loss/neutral counts, win rate), clearly distinguishing it from sibling tools like get_agent_ledger, get_my_trades, or get_portfolio.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides clear context: 'Closed trades only', 'Paper trading only', and 'Not financial advice'. It guides when to use (for checking agent scorecard) but does not explicitly state when not to use or name alternatives among siblings.

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

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