HKUDS/Vibe-Trading · error · ValueError

{name} is required

Error message

{name} is required

What it means

Thrown by _required_float when a mandatory numeric kwarg (e.g. entry_spot, entry_iv) is absent, null, or empty string. These parameters anchor all payoff/greeks math so the tool refuses to default them.

Source

Thrown at agent/src/tools/options_payoff_tool.py:261

            qty_number = float(raw_qty)
        except (KeyError, TypeError, ValueError, OverflowError) as exc:
            raise ValueError(f"legs[{index}] has invalid strike or qty: {exc}") from exc
        if isinstance(raw_qty, bool) or not qty_number.is_integer():
            raise ValueError(f"legs[{index}].qty must be a non-zero integer")
        qty = int(qty_number)
        raw_premium = item.get("premium")
        try:
            premium = None if raw_premium is None else float(raw_premium)
        except (TypeError, ValueError, OverflowError) as exc:
            raise ValueError(f"legs[{index}].premium must be numeric or null") from exc
        legs.append(OptionLeg(option_type, strike, qty, premium))
    return legs


def _required_float(kwargs: dict[str, Any], name: str) -> float:
    """Read a required finite float."""
    if name not in kwargs or kwargs[name] is None or kwargs[name] == "":
        raise ValueError(f"{name} is required")
    try:
        value = float(kwargs[name])
    except (TypeError, ValueError, OverflowError) as exc:
        raise ValueError(f"{name} must be numeric") from exc
    if not math.isfinite(value):
        raise ValueError(f"{name} must be finite")
    return value


def _optional_float(kwargs: dict[str, Any], name: str, default: float) -> float:
    """Read an optional finite float, treating null and empty text as omitted."""
    raw = kwargs.get(name)
    if raw is None or raw == "":
        return default
    try:
        value = float(raw)
    except (TypeError, ValueError, OverflowError) as exc:
        raise ValueError(f"{name} must be numeric") from exc

View on GitHub (pinned to 80ffdda44c)

Solutions

1. Supply the required parameter with a numeric value (check the tool's arg spec for which names _required_float guards)
2. Fix key names/casing to exactly match the tool schema
3. If the value is genuinely unknown, have the caller compute/fetch it before invoking

Example fix

// before
execute({"legs": legs})  # missing entry_spot
// after
execute({"legs": legs, "entry_spot": 100.0})

REQUIRED = ("entry_spot", "entry_iv")  # per tool spec
missing = [k for k in REQUIRED if kwargs.get(k) in (None, "")]
if missing:
    raise ValueError(f"missing required params: {missing}")

def has_required_numeric_kwargs(kwargs: dict, names: tuple) -> bool:
    return all(kwargs.get(n) not in (None, "") for n in names)

try:
    execute(kwargs)
except ValueError as e:
    if "is required" in str(e):
        prompt_user_for(str(e).split()[0])

When it happens

Trigger: Calling execute without entry_spot; passing entry_spot=None or ""; kwargs keys with different casing (entrySpot) so the expected key is effectively missing.

Common situations: LLM tool calls omitting required params; clients forwarding optional-only forms; schema drift between caller and tool versions renaming parameters.

Understand the failure class

Background: Missing required parameter errors: what 'X is required' and 'the required X param is missing' mean, and how to fix them — this error's family across 27 libraries.

Related errors

• title is required
• thesis is required
• memory name must not be empty or whitespace-only
• T must be > 0 to imply a volatility, got {T}
• {model}: name is required and cannot be blank, got {name!r}

AI-assisted analysis of HKUDS/Vibe-Trading@80ffdda44c (2026-08-28). Data as JSON: /api/errors/0358fb64e311195d. Report an issue: GitHub.