feat: add untracked aerodrome tools and todo analysis documents

todo/EXTENDED_SHADOW_TIMEOUT.md

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+# Analysis Request: Extended Timeout for Shadow Orders
+
+**Status:** Completed
+**Date:** 2025-12-20
+**Priority:** Medium
+
+---
+
+## 1. User Description & Query
+**Goal:** Extend the Shadow Order timeout to **10 minutes (600s)** to capture the "Mean Time to Execution" across different market conditions.
+**Reasoning:** Instead of failing fast (which assumes Maker is bad if not instant), we want to gather data on *how long* it actually takes to fill. This helps optimize the timeout later.
+
+## 2. Agent Summary
+*   **Objective:** Modify `clp_hedger.py` to use a long fixed timeout (or much longer dynamic timeout) for shadow orders.
+*   **Risk:** "Success" at 9 minutes is effectively a "Failure" for hedging (Delta Drift).
+*   **Mitigation:** We are collecting *data*, not executing trades. A 9-minute fill log is valuable data point (it tells us "Maker is impossible here").
+
+## 3. Main Analysis
+
+### 3.1 Data Value vs. Hedging Reality
+*   **Hedging Reality:** If a hedge takes > 30s to fill, the price has likely moved significantly. The "Hedge" is no longer hedging the original risk.
+*   **Data Value:** By waiting 10 minutes, we can generate a distribution curve:
+    *   *50% fill in < 5s* (Great!)
+    *   *30% fill in 5s-60s* (Okay for stable markets)
+    *   *20% fill in > 60s* (Terrible)
+    *   *If we used a 60s timeout, we would just see "20% Failed", losing the nuance.*
+
+### 3.2 Implementation Strategy
+Instead of a complex dynamic timeout for now, let's set a **Fixed Long Timeout (600s)** for the Shadow Simulator.
+*   **Why?** We want to see the *actual* fill time for every order, not cut it off artificially.
+*   **Logging:** The log `filled in X.Xs` becomes the primary metric.
+
+### 3.3 Memory Impact
+*   Even with 1 trade per minute, 10 minutes = 10 items in the list.
+*   Memory usage is negligible (<1KB).
+
+## 4. Conclusion
+**Recommendation:** Switch the Shadow Order logic to use a **Fixed 600s Timeout**.
+*   This turns the simulator into a "Fill Time Data Collector".
+*   We can analyze the logs later to find the "Optimal Timeout" (e.g., "95% of fills happen within 45s, so set timeout to 45s").
+
+## 5. Implementation Plan
+- [ ] **Step 1:** In `clp_hedger.py`, replace the dynamic timeout calculation with `timeout = 600`.
+- [ ] **Step 2:** Update logging to ensure `fill_time` is prominent.