aipricepatterns

get_live_polymarket_trade_decision

Auto-discover the active BTC Up/Down 15m Polymarket market, combine live Polymarket pricing with pattern memory and intrabar momentum, and return BUY_YES, BUY_NO, or SKIP with entry guardrails.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`nowMs`	No
`symbol`	No		BTCUSDT
`minEdge`	No
`interval`	No		15m
`token_id`	No	Optional Manus access token. Paid tools use tokenized service access, not a monthly subscription: when token_id is omitted the server returns payment_required with a Solana Pay invoice, and after payment you retry with the same token while the server uses Manus token/resolve to recover pending access.
`marketWindow`	No		current
`allowDegradedSearch`	No
`minCombinedConfidence`	No

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden. It states that the tool returns a decision (BUY_YES/BUY_NO/SKIP) with entry guardrails, but it does not disclose whether trades are executed, side effects (e.g., network calls, payment requirements), or what happens when payment is needed. The description omits important behavioral context.

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?

A single, dense sentence that packs the main actions without repetition or filler. It is front-loaded with the primary verb and resource, but slightly overloaded with multiple clauses. Still efficient and well-structured.

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

Completeness2/5

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

The tool has 8 parameters, no output schema, and no annotations, yet the description only provides a high-level overview. It does not explain the return format, what 'entry guardrails' are, the payment flow hinted at by token_id, or failure modes. For a complex tool of this type, the description is insufficient for an agent to invoke it effectively.

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

Parameters2/5

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

Schema description coverage is only 13%, so the description must compensate. It does not explain key parameters like minEdge, allowDegradedSearch, minCombinedConfidence, or marketWindow. While symbol and interval are implicit in the market description, most parameters remain under-documented.

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 uses specific verbs ('auto-discover', 'combine', 'return') and names a specific resource ('active BTC Up/Down 15m Polymarket market'). It clearly distinguishes itself from sibling tools like get_trading_decision by focusing on the live Polymarket market and entry guardrails.

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

Usage Guidelines3/5

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

The context is implied: this is for live trading decisions on the specific Polymarket BTC Up/Down 15m market. However, there is no explicit 'when to use' or 'when not to use' guidance, nor any mention of alternative tools like get_trading_decision or backtest_strategy.

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

B3.2/5.0

Disambiguation2/5

Several tools inhabit overlapping territory: find_market_analogs, pattern_search, search_by_sketch, and get_candle_market_snapshot all relate to historical pattern matching, while get_trading_decision, get_trader_decision_v2, and get_live_polymarket_trade_decision all produce trade-oriented decisions. The descriptions add context, but an agent could still easily pick the wrong tool for a given request.

Naming Consistency3/5

The tools are consistently snake_case and mostly readable, but the naming conventions are mixed: many tools use get_<noun>, while others start with verbs like backtest, detect, find, forecast. Minor irregularities such as pattern_search and the v2 suffix in get_trader_decision_v2 also reduce predictability.

Tool Count4/5

Fifteen tools is within a reasonable size, and the server covers a broad domain: pattern search, regime detection, backtesting, track records, private datasets, live Polymarket decisions, and documentation. The count is not excessive, but some tools are functionally redundant enough that the set could be tightened.

Completeness4/5

The tool surface covers the main evidence workflow well: discovering patterns, analyzing analogs, backtesting strategies, checking track records, and producing trading decisions. Minor gaps remain around private dataset management and there is no separate low-level raw candle query tool, but most core user journeys are supported.

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