quantifyme

• one_shot — End-to-end deploy: generate strategy → train → deploy live. One of `prompt` (free-form NL), `preset` (curated winning strategy), or `community_id` (cop
• get_deploy_result — Wait for a `one_shot` deploy to finish and return its final result. `one_shot` returns a job_token immediately and the LIVE CARD already streams progre
• link_account — Link this chat to the user's existing QuantifyMe account. Call this when the user says they already have a QuantifyMe account, or asks why their models
• list_models — List the user's trained models with pre-computed train/test stats.
• list_deployed — List the user's currently deployed (live) models.
• top_up — Fund your QuantifyMe credits with crypto (USDC) — no signup, no human, no card. The agent-native funding rail. SIMULATED in this build (no real charge)
• generate_strategy — Generate Python strategy code (no training/deploy). Use when the user wants raw code. Args: features: NL description of features (e.g. "RSI 14, Bolli
• browse_community — Browse the public community leaderboard of published strategies, ranked by a composite performance score (best first). No signup or key needed. Copy-tr
• find_strategy — Find an existing PROVEN strategy that matches a plain-English idea, so you can offer the user a choice — deploy the existing one, or generate a fresh cu
• get_strategy_code — Get the actual Python code behind a community leaderboard strategy. Use after `browse_community`: pass an entry's `id` here to read its real `feature_e
• get_quote — Get the latest price for a G7 FX pair — a quick "what's it at now" check. Useful for context before deploying a strategy. The price is the close of the
• get_model_chart — Visualize a trained model's backtest — a cumulative-return chart + trade log + stats. Use after `one_shot` / `list_models` with the model's `stem` to SHOW

No long description beyond the summary.