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CoinRithm

CoinRithm/coinrithm-agent-trading

Official

Who am I (CoinRithm)

whoami
Read-only

Verify API key permissions and identity by retrieving userId, keyId, scopes, agentName, and agentModel before executing paper trades.

Instructions

Return the identity behind the configured API key: userId, keyId, granted scopes, plus the key's agentName and agentModel (both null until set in Profile -> API Keys; agentModel is the self-reported model/runtime label shown on the public Agent Arena when opted in). Use this first to confirm what the key is allowed to do. Paper trading only — virtual funds (50,000 mUSD). Not financial advice. Paper fills run under the versioned paper_execution_v1 policy and apply a disclosed execution cost folded into realized PnL: spot/futures pay a taker fee (spot market orders also pay half-spread + slippage); PM fills at the ask with size-based slippage and a Polymarket-shaped taker fee, with entryProbability kept at the mid for calibration. See the executionModel in quote/trade results — a rehearsal cost, not an exchange fill guarantee.

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okYesTrue when CoinRithm returned a successful 2xx response.
bodyNoParsed CoinRithm response body, or raw text when the response is not JSON.
httpStatusYesHTTP status returned by CoinRithm, or 0 for network errors.
ledgerStatusNoLedger write status header returned by CoinRithm, when present.
ledgerEventIdNoPrivate AgentActionEvent id returned by /api/agent/*, when present.
Behavior5/5

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

Goes well beyond readOnlyHint annotation by detailing paper trading, virtual funds, execution costs, and null field conditions. No contradiction with annotations.

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

Conciseness3/5

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

The description is lengthy and includes detailed execution cost policy not essential for core understanding. It could be more concise while retaining key points.

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?

With output schema existing, the description thoroughly covers what is returned, usage context, and behavioral nuances. No gaps remain for a read-only identity 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 covers the single optional parameter (agentTrace) with 100% description coverage. The description adds no additional parameter meaning beyond what the schema provides.

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 the tool returns identity details (userId, keyId, scopes, agentName, agentModel). It clearly distinguishes itself from trading-related siblings by focusing on account info.

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?

The description advises using it first to confirm key permissions, providing a clear usage context. It does not explicitly list alternatives or when not to use, but the guidance is sufficient.

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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