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Goal

Produce a repeatable, machine-friendly market brief before placing a trade:
  • current market state
  • liquidity and spread context
  • execution impact estimate
  • explicit go/no-go and constraints

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Inputs

  • condition_id (required)
  • optional thesis horizon (intraday, 1d, 1w, event_horizon)
  • planned side (BUY or SELL)
  • intended size in USDC

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1) Pull market and event context

  • get_market with condition_id
  • get_event from the related event id when available
Capture status, outcomes, timing, and event risk windows.

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2) Pull batched market data

Use the canonical pluralized tools:
  • get_order_books
  • get_prices
  • get_midpoints
  • get_spreads
  • get_last_trade_prices
Example: 
{
  "tool": "get_prices",
  "input": {
    "items": [{ "token_id": "<target_token_id>", "side": "BUY" }]
  }
}
Focus on:
  • spread regime (tight/normal/wide)
  • visible depth near midpoint
  • last trade versus current best price

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3) Estimate execution impact

Run calculate_market_price for the intended side and amount. 
{
  "tool": "calculate_market_price",
  "input": {
    "token_id": "<target_token_id>",
    "side": "BUY",
    "amount": "250"
  }
}
Use the result to set max slippage and a candidate limit price.

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4) Gather execution metadata

  • get_fee_rate_bps
  • get_tick_size
  • get_neg_risk
These values should flow directly into downstream order validation and execution policy.

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5) If execution is approved, hand off to trading wrappers

  • prepare_order to locally prepare/sign a draft without posting
  • place_order with confirm: true only at the final execution step
  • cancel_orders if you need an explicit unwind/cancel path

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Suggested output contract

Have the agent return a strict structure like: 
{
  "thesis": "short rationale",
  "confidence": 0.0,
  "market_state": {
    "status": "active|closed|...",
    "best_price": 0.0,
    "midpoint": 0.0,
    "spread": 0.0,
    "last_trade": 0.0
  },
  "execution": {
    "side": "BUY",
    "amount_usdc": "250",
    "estimated_price": 0.0,
    "max_slippage_bps": 0,
    "suggested_limit_price": 0.0
  },
  "risks": ["liquidity", "event timing"],
  "go_no_go": "GO|NO_GO",
  "fallback_plan": "what to do if liquidity degrades"
}

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Optional: use the built-in prompt

You can bootstrap this workflow with prompt market-analysis using:
  • condition_id
  • horizon
  • include_orderbook_depth
  • include_recent_trades
The prompt is registered by the server and already encodes the same analysis sequence.