CoinRithm Agent Trading

Export private agent ledger

export_agent_ledger

Read-only

Export up to 1,000 private ledger rows for the calling API key as JSON. Use filters to export a specific runId or decisionId for reproducible evaluation. No public Arena user can see this data. 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

Name	Required	Description
`to`	No	Optional ISO end timestamp.
`from`	No	Optional ISO start timestamp.
`runId`	No	Optional run id filter.
`venue`	No	Optional venue filter.
`status`	No	Optional ledgerStatus filter.
`eventType`	No	Optional event type filter.
`agentTrace`	No	Optional private trace metadata stored in the caller's ledger.
`decisionId`	No	Optional decision id filter.

Output Schema

TableJSON Schema

Name	Required	Description
`ok`	Yes	True when CoinRithm returned a successful 2xx response.
`body`	No	Parsed CoinRithm response body, or raw text when the response is not JSON.
`httpStatus`	Yes	HTTP status returned by CoinRithm, or 0 for network errors.
`ledgerStatus`	No	Ledger write status header returned by CoinRithm, when present.
`ledgerEventId`	No	Private AgentActionEvent id returned by /api/agent/*, when present.

TDQS

A4.4/5.0

Behavior5/5

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

Annotations indicate readOnlyHint=true and destructiveHint=false. The description expands on this by stating the export limit (1,000 rows), the paper trading context, virtual funds, and details of execution fees. It adds behavioral context such as 'No public Arena user can see this data' and 'Paper fills run under...', which are valuable beyond annotations.

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

Conciseness4/5

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

The description is front-loaded with the core purpose in the first sentence. It then logically adds usage, constraints, and detailed execution context. However, the lengthy explanation of paper trading fees might be trimmed for brevity. Overall, it is well-structured but slightly verbose.

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 the complexity of 8 parameters, nested objects, and the presence of an output schema, the description covers the tool's function, constraints, and behavioral nuances. It explains limitations (1,000 rows), paper trading specifics, and fee structure, making it comprehensive for an agent to understand when and how to use it.

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?

The input schema covers all 8 parameters with descriptions, achieving 100% coverage. The description mentions the purpose of filters (runId, decisionId) but does not add new semantics beyond what is in the schema. The baseline score of 3 is appropriate as the description neither harms nor significantly enhances parameter understanding.

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 'Export up to 1,000 private ledger rows for the calling API key as JSON.' This clearly defines the verb (export), resource (private ledger rows), and scope (for the calling API key). It distinguishes from sibling 'get_agent_ledger' by implying export vs. retrieval.

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 'Use filters to export a specific runId or decisionId for reproducible evaluation,' providing a concrete use case. However, it does not explicitly differentiate from the sibling 'get_agent_ledger' or other tools, leaving some ambiguity about when to use this tool versus alternatives.

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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TDQS

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, but a few could be confused (e.g., get_performance vs get_equity_curve, get_portfolio vs get_wallet). Descriptions help differentiate them.

Naming Consistency4/5

Predominantly verb_noun (get_*, place_*, open_*, etc.) with a consistent pm_data_* prefix for prediction market data tools. Minor outliers like whoami and futures_quote/spot_quote without a verb are exceptions.

Tool Count4/5

37 tools is slightly high but appropriate for a multi-venue trading platform covering spot, futures, and prediction markets along with extensive data and performance tracking tools.

Completeness4/5

Covers core trading lifecycle (quote, open, close, cancel) for all venues, plus market data, ledger exports, and arena leaderboards. Lacks spot order modification but otherwise well-rounded.

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