options-brainstorm

Clarifies options strategy intent and produces a validated OptionsSpec draft.

Updated Jun 27, 2026
One-click install
npx skills add https://github.com/HKUST-QUANT-SOCIETY/quantcode --skill options-brainstorm-hkust-quant-society
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: options-brainstorm
Source: https://github.com/HKUST-QUANT-SOCIETY/quantcode/tree/main/.opencode/groups/options/skills/options-brainstorm
Command: npx skills add https://github.com/HKUST-QUANT-SOCIETY/quantcode --skill options-brainstorm-hkust-quant-society

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pydantic.

What problem does it solve? When options researchers have a new idea (hedging, volatility trading, spreads, covered calls) but the strategy elements are not yet structured, this Skill turns natural-language descriptions into a validated OptionsSpec draft that downstream tools can consume. ## Core Features & Use Cases - Strategy Clarification: Identifies strategy type (directional, volatility, arbitrage, hedge, covered call) and locks in underlying, expiry, strike range, and call/put preference. - Constraint Confirmation: Captures risk limits such as max Delta/Gamma, margin caps, and whether short options are allowed. - Structured Output: Produces an OptionsSpec draft validated against the Pydantic schema schemas.options.OptionsSpec, ready to trigger build_vol_surface or the options-vol-surface skill. - Use Case: A researcher says "GC near-month put protection, delta neutral" and receives a validated OptionsSpec with underlying, as-of date, data path, and research questions. ## Quick Start Ask the agent to turn my options idea about GC near-month put protection with delta neutrality into a validated OptionsSpec draft.

Frequently Asked Questions about options-brainstorm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I turn an options strategy idea into a structured spec?▼

Describe the idea in natural language, such as "GC near-month put protection, delta neutral". The skill clarifies strategy type, underlying, expiry, strike range, and risk constraints, then outputs a Pydantic-validated OptionsSpec draft.

What options strategy types does the brainstorming workflow support?▼

It supports directional, volatility, arbitrage, hedging, and covered call strategies. The workflow first classifies the idea into one of these types before locking in underlying, expiry month, strike range, and call/put preference.

What is an OptionsSpec and how is it validated?▼

An OptionsSpec is a Pydantic model defined in schemas.options.OptionsSpec containing fields like strategy_name, underlying, as_of_date, data_path, data_source, and research_questions. The draft must pass Pydantic validation with non-empty underlying, as_of_date, and data_path.

Does the skill work with real market options data?▼

It checks data availability against sample fixtures in data/sample_options/, such as gc_options_merged_sample.csv. Sample CSVs are explicitly not treated as production data, and only published surface components are called downstream.

What happens after the OptionsSpec draft is produced?▼

The validated spec triggers downstream components, either the build_vol_surface tool or the options-vol-surface skill. Downstream consumers must be able to parse the spec and invoke the volatility surface construction.