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CoinRithm Agent Trading

by io.github.CoinRithm

Get positions

get_positions
Read-only

List open + historical positions for a venue. venue='futures' returns mock futures positions (with unrealized PnL + liquidation distance on open ones); venue='pm' returns mock prediction-market positions (with unrealized mark on open ones). Response includes asOf — pass it back as updatedSince on the next call to poll only positions that changed (catches worker-fired SL/TP, liquidations, and settlements). 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
venueYesWhich venue's positions to list.
agentTraceNoOptional private trace metadata stored in the caller's ledger.
updatedSinceNoISO 8601 cursor: only positions whose row changed since this instant. Pass the previous response's asOf back here.

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.

TDQS

A4.6/5.0
Behavior5/5

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

The description adds significant behavioral context beyond the annotations (readOnlyHint, openWorldHint, destructiveHint). It details mock data, virtual funds, execution costs, fees, slippage, and the rehearsal cost nature. This provides a comprehensive understanding of the tool's behavior and limitations.

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 main purpose and well-structured. It is somewhat lengthy but each sentence adds necessary detail. A slight reduction could improve conciseness, but overall it is efficient.

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 tool's complexity (3 parameters, nested objects, output schema exists), the description covers all necessary context: what positions are returned, how to poll for changes, paper trading nature, and execution model. It is complete without relying solely on the output schema.

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

Parameters4/5

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

With 100% schema coverage, the schema already documents parameters well. The description adds value by explaining the purpose of 'updatedSince' for polling, venue-specific position contents (unrealized PnL, liquidation distance, mark), and the optional nature of agentTrace. This goes beyond the schema's descriptions.

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 clearly states the tool lists open and historical positions for a venue, distinguishing between futures and pm with specific mock data details. It is a specific verb+resource action that differentiates from sibling tools like 'close_futures_position' or 'open_futures_position'.

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 explains when to use the tool (to list positions), provides context for polling with the 'asOf' and 'updatedSince' parameters, and clarifies it's for paper trading only. However, it does not explicitly state when not to use it or mention alternative tools among the siblings.

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

All CoinRithm Agent Trading toolsInspect
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TDQS

A4.2/5.0
Disambiguation5/5

Each tool targets a distinct resource or action (e.g., spot vs futures vs PM, quote vs open vs close, different PM data endpoints). Descriptions provide clear context and usage guidance, eliminating ambiguity.

Naming Consistency5/5

All tools follow a verb_noun pattern in snake_case (e.g., `cancel_spot_order`, `open_futures_position`, `pm_data_event`). Even `whoami` is a common exception. Naming is uniform and predictable.

Tool Count4/5

35 tools is on the high side but appropriate for a multi-venue trading platform covering spot, futures, prediction markets, analytics, and account management. Each tool serves a distinct purpose, though minor consolidation could be possible.

Completeness5/5

The tool surface covers the full trading lifecycle: quotes, order placement, cancellation, position management, SL/TP, portfolio tracking, performance, and extensive market data. No obvious gaps for the stated purpose.

Resources