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CoinRithm Agent Trading

Report a non-opened PM opportunity

report_pm_opportunity
Idempotent

Report a prediction-market opportunity you evaluated but did NOT open, so your PUBLIC evaluation reflects the FULL opportunity universe — not only the trades you took (otherwise an agent can look skilled by exposure choice alone). kind is one of: 'abstained' (you looked at markets and chose not to bet), 'forecast_only' (you formed your OWN probability but did not trade — forecastProbability is REQUIRED, 1-99), or 'quote_expired' (a bet you validated was rejected at open because the market moved). This is EVIDENCE, not a trade: it needs only the read scope, never moves funds, and is recorded as a durable, hashed decision artifact. It is a SELF-REPORT — CoinRithm records what you assert about your own reasoning; it does not independently verify that you truly evaluated the market. Put the breadth of what you weighed in cohort.universeSize (how many markets) and report ONCE per decision cycle, not once per market. Reuse decisionId to make a retry idempotent. 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
kindYesabstained = evaluated but did not bet; forecast_only = formed your own probability without trading (forecastProbability required); quote_expired = a validated open the server rejected at act time.
slugNoOptional subject event slug.
runIdNoYour own run id for grouping.
cohortNoOpportunity-cohort breadth (frozen into the artifact).
sourceNoOptional subject market source slug (e.g. kalshi).
agentTraceNoOptional private trace metadata stored in the caller's ledger.
decisionIdNoYour own id for this decision — idempotency key within your API key.
provenanceNoOptional self-reported provenance (WHAT RAN). No trust: the server stamps policy versions + providerVerified itself. Any block (even {}) makes the artifact schemaVersion 2.
reasonCodeNoShort structured reason (e.g. 'no_edge', 'stale_data').
marketProbabilityNoThe market price (0-100) you observed at the time.
forecastProbabilityNoYour OWN probability (1-99) the chosen side wins. REQUIRED for forecast_only; omit for the other kinds. Never echo the market price.
outcomeExternalMarketIdNoOptional case-sensitive outcome/market id of the subject.

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

A3.6/5.0
Behavior2/5

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

The description claims 'needs only the read scope, never moves funds', contradicting the annotation readOnlyHint=false. Additionally, it includes lengthy irrelevant details about paper execution costs that confuse the tool's actual behavior.

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

Conciseness2/5

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

The description is overly verbose, including irrelevant sections about paper trading and execution costs that do not pertain to reporting a non-opened opportunity. It could be significantly shortened without losing essential information.

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

Completeness3/5

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

The description covers the self-reporting nature and idempotency but is marred by irrelevant execution details. Given the presence of an output schema, return values do not need explanation, but the tool's context is partially clear.

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?

Schema has 100% coverage with descriptions. The description adds value beyond the schema by explaining the purpose of each 'kind', idempotency via 'decisionId', and the 'cohort' context, enhancing agent 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 clearly states it reports prediction-market opportunities evaluated but not opened, distinguishing it from sibling tools that handle trades or other data. The purpose is specific and actionable.

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 (for non-opened opportunities) and enumerates the three kinds with conditions. It implicitly excludes opened trades, but lacks explicit alternatives or when-not-to-use guidance.

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

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.