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get_candle_market_snapshot

Return the same full-OHLC candle-pattern context used by the /candles chart: exact chart-supported presets, latest query candles, shape codes, historical analogues, magnitude bands, the analogue overlay ledger (resolved coverage and live-only Winkler vs trivial), data freshness, and an explicit signal-integrity gate. Candle similarity is research evidence, not a directional probability.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fNoForward horizon in bars. Only the chart presets 5, 10, 30, and 50 are supported
qNoCandles in the matched pattern. Only the chart presets 3, 5, 8, and 12 are supported
limitNoNumber of closest candle analogues to return (1-20)
symbolNoSupported chart symbol: BTCUSDT, ETHUSDT, or SOLUSDTBTCUSDT
anchorTsNoOptional historical replay anchor in Unix milliseconds. Omit for the latest chart candle
intervalNoSupported chart timeframe: 5m, 15m, 1h, 4h, or 1d5m
token_idNoOptional 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.
includeAnalogueCandlesNoInclude OHLC arrays for every analogue and its continuation. False keeps the response agent-sized

TDQS

A3.6/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It discloses that similarity is 'research evidence, not a directional probability' and mentions an 'explicit signal-integrity gate,' which is helpful. However, it does not mention side effects, permissions, or the token-based payment mechanism beyond the parameter description.

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 a single, information-dense sentence that lists all key elements without redundancy. It is slightly long but well-organized and easy to parse, with no unnecessary fluff.

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?

It thoroughly lists the content of the response (e.g., presets, analogues, magnitude bands) but does not specify the output structure or format. Given the absence of an output schema, the description could be more explicit about the response shape, though referencing the /candles chart provides some context.

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 schema provides 100% coverage with detailed descriptions for all eight parameters, including enums and defaults. The tool description does not add extra meaning beyond the schema, so it stays at the baseline for high schema coverage.

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 names a specific resource (candle-pattern context), a specific action (return), and lists the exact components (OHLC, presets, analogues, magnitudes, ledger, freshness, gate). It clearly distinguishes from sibling tools like find_market_analogs or get_pattern_metrics by framing it as the chart's context.

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 description states what it returns but does not explicitly say when to use it versus alternatives. It mentions it mirrors the /candles chart, implying use when chart context is needed, but lacks direct guidance on when this tool is preferable over similar ones like find_market_analogs.

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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