{"record":{"id":"48d28b4ce9f2de12","repo":"HKUDS/Vibe-Trading","slug":"scenario-iv-values-must-contain-positive-finite-va","errorCode":null,"errorMessage":"scenario_iv_values must contain positive finite values","messagePattern":"scenario_iv_values must contain positive finite values","errorType":"validation","errorClass":"ValueError","httpStatus":null,"severity":"error","filePath":"agent/src/tools/options_payoff_tool.py","lineNumber":338,"sourceCode":"        values = [\n            entry_iv * 0.5,\n            entry_iv * 0.75,\n            entry_iv,\n            entry_iv * 1.25,\n            entry_iv * 1.5,\n        ]\n    else:\n        if not isinstance(raw, list) or not raw:\n            raise ValueError(\"scenario_iv_values must be a non-empty array\")\n        if len(raw) > _MAX_IV_SCENARIOS:\n            raise ValueError(f\"scenario_iv_values may contain at most {_MAX_IV_SCENARIOS} entries\")\n        try:\n            values = [float(value) for value in raw]\n        except (TypeError, ValueError, OverflowError) as exc:\n            raise ValueError(\"scenario_iv_values must contain numbers\") from exc\n    array = np.asarray(values, dtype=float)\n    if not np.isfinite(array).all() or (array <= 0).any():\n        raise ValueError(\"scenario_iv_values must contain positive finite values\")\n    return array\n\n\ndef _rounded(value: float) -> float:\n    \"\"\"Round a finite scalar for stable, compact JSON.\"\"\"\n    return round(float(value), 6)\n\n\ndef _rounded_array(values: np.ndarray) -> list[float]:\n    \"\"\"Round a numeric array for stable, compact JSON.\"\"\"\n    return [round(float(value), 6) for value in np.asarray(values).tolist()]\n\n\ndef _error(message: str) -> str:\n    \"\"\"Build a stable error envelope.\"\"\"\n    return json.dumps(\n        {\"status\": \"error\", \"tool\": \"options_payoff\", \"error\": message},\n        ensure_ascii=False,","sourceCodeStart":320,"sourceCodeEnd":356,"githubUrl":"https://github.com/HKUDS/Vibe-Trading/blob/80ffdda44c5c4db0dd84d70e051cca591cea67df/agent/src/tools/options_payoff_tool.py#L320-L356","documentation":"After numeric coercion succeeds, _scenario_ivs converts the list to a numpy float array and requires all values finite and strictly positive (IVs are sqrt-of-time multipliers, so zero/negative/NaN/inf vol is mathematically invalid). Failing np.isfinite().all() or (array <= 0).any() raises this error.","triggerScenarios":"scenario_iv_values containing 0, a negative number, NaN, or inf (e.g. [0.0, 0.2], [-0.2], [float('nan')]).","commonSituations":"Passing volatilities as percentages mixed with decimals, defaults of 0 leaking from config, or arithmetic upstream producing NaN/inf.","solutions":["Use strictly positive decimal volatilities like [0.15, 0.20, 0.30]","Guard computed IVs with math.isfinite(v) and v > 0 before calling","Check for accidental 0 default values in configuration"],"exampleFix":"// before\nscenario_iv_values=[0, 0.2]\n// after\nscenario_iv_values=[0.01, 0.2]","handlingStrategy":"validation","validationCode":"import math\nivs = [float(v) for v in ivs]\nassert all(math.isfinite(v) and v > 0 for v in ivs), \"IVs must be positive finite\"","typeGuard":"def valid_ivs(v: object) -> bool:\n    return isinstance(v, list) and bool(v) and all(\n        isinstance(x, (int, float)) and math.isfinite(x) and x > 0 for x in v\n    )","tryCatchPattern":"try:\n    tool.execute(**kwargs)\nexcept ValueError as e:\n    if \"positive finite\" in str(e):\n        ivs = [max(v, 1e-4) for v in ivs]  # floor tiny/zero vols","preventionTips":["Never mix percent and decimal conventions","Floor computed vols at a small epsilon","Assert finiteness after any upstream arithmetic"],"tags":["options-payoff","input-validation","volatility"],"backgroundTag":"argument-range-validation-failed","analyzedSha":"80ffdda44c5c4db0dd84d70e051cca591cea67df","analyzedAt":"2026-08-28T12:46:38.989Z","schemaVersion":2},"datasetVersion":"2026-08-28T16:17:29.566Z"}