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The following skills are available. When you need detailed instructions for a specific skill,
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[User Request]
if the sniper bot ws active today 916 to 945 - what would be the result - use the ctal data to calculate
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
Let me start by loading the Morning Sniper bot skill and understanding the configuration, then pull today's actual data to simulate.
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"success": true, "name": "morning-sniper-bot-guardrails", "description": "Critical guardrails and architecture for the Morning Sniper trading bot (5 stocks, VIDYA+Renko, 9:17–9:45). Entry/exit rules, broker quirks, self-healing, cron pipeline.", "tags": [], "related_skills": [], "content": "---\nname: morning-sniper-bot-guardrails\ndescription: Critical guardrails and architecture for the Morning Sniper trading bot (5 stocks, VIDYA+Renko, 9:17–9:45). Entry/exit rules, broker quirks, self-healing, cron pipeline.\n---\n\n# Morning Sniper Bot — Guardrails & Architecture\n\n## Quick Start\n```bash\n# Run with custom time window\nbash /home/ubuntu/bots/morning_sniper/run_test.sh 14:30 15:15\n\n# Self-heal brokers\nbash /home/ubuntu/bots/morning_sniper/self_heal.sh\n\n# Start normally (systemd)\nsudo systemctl start morning_sniper_bot\n```\n\n## Cron Pipeline\n\n| Time | Script | What |\n|---|---|---|\n| 9:00 | `morning_fix.sh` | Clean DBs, **preserve tokens** (no revoke), restart OpenAlgo services, run `self_heal.sh`. Start claude_bot + lt_3candle. **Does NOT start sniper** |\n| 9:05 | `market_ready.sh` | HTTP checks |\n| 9:20 | `post_login_flush.sh` | Flush broker in-memory caches, wait 10s, **start morning_sniper_bot** |\n| 9:25 | Bot | Pre-flight broker check via `check_broker_ok()`, trading starts |\n\n**Key change (2026-05-04)**: Tokens are NO LONGER revoked. Service restart clears\nthe in-memory `sha256(api_key)` cache; the worker re-reads the token from DB.\nIf the token is still valid at the broker, it works immediately — no daily login needed.\n`self_heal.sh` v2 tests with live API calls to detect if a token has actually expired.\n\n## Shoonya Auth & Token Architecture\n\nOpenAlgo uses two separate in-memory auth caches:\n1. `auth-{username}` — refreshed by `upsert_auth()` on login\n2. `sha256(api_key)_{feed_flag}` — used by `get_auth_token_broker()`, NOT cleared by login\n\nThe flow: `api_key` → `verify_api_key()` → `user_id` → `Auth` table lookup by `name=user_id`\n→ decrypt `auth` column → use as Shoonya session token.\n\nIf `is_revoked=1` (old morning_fix.sh behavior): `get_auth_token_broker()` returns `(None, None)`.\nEvery broker call silently fails with `{'orderid': None, 'status': 'success'}`.\n**Now: tokens are preserved; only the in-memory cache is cleared by restart.**\n\nIf the Shoonya OAuth token has actually expired at the broker, `self_heal.sh` v2 detects it\nvia a live `quotes()` test and alerts via Telegram.\n\n## Iron Rules (never break these)\n\n### 1. Single entry — NO duplicate orders\n- Place ONE LIMIT BUY. Wait 30 seconds. Check positionbook.\n- If filled → done. If order still open → wait 10s more.\n- If still not filled → cancel stuck order, ONE retry only. No third attempt.\n- Never place BUY #2 while BUY #1 is still open at the broker.\n\n### 2. All exits use LIMIT (never MARKET)\n- No broker supports MARKET orders via OpenAlgo.\n- Shoonya silently drops MARKET orders with `orderid: None`.\n- Use `place_order(\"SEL
... [8393 chars total, truncated]
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"success": true, "name": "openalgo-vps-reconnaissance", "description": "Systematic reconnaissance of OpenAlgo VPS deployments. Discovers broker instances,\nNginx reverse proxy setup, Gunicorn configuration, database architecture, and\nservice health status without requiring extensive sudo access.\n", "tags": ["openalgo", "vps", "broker-integration", "nginx", "gunicorn", "system-discovery"], "related_skills": [], "content": "---\nname: openalgo-vps-reconnaissance\ndescription: |\n Systematic reconnaissance of OpenAlgo VPS deployments. Discovers broker instances,\n Nginx reverse proxy setup, Gunicorn configuration, database architecture, and\n service health status without requiring extensive sudo access.\ntags:\n - openalgo\n - vps\n - broker-integration\n - nginx\n - gunicorn\n - system-discovery\n---\n\n# OpenAlgo VPS Reconnaissance\n\n## Overview\n\nThis skill provides a structured approach to exploring and documenting OpenAlgo VPS deployments.\nIt systematically uncovers broker instances, service architecture, proxy configuration, and database setup.\n\n## When to Use\n\n- First-time exploration of an OpenAlgo VPS\n- Documenting broker configuration details\n- Troubleshooting broker integration issues\n- Creating or updating VPS documentation\n- Auditing active services and resources\n\n## Prerequisites\n\n- SSH access to the VPS (user account, not necessarily sudo)\n- Basic terminal skills\n- Familiarity with systemd, Nginx, and Python virtual environments\n\n## Step-by-Step Reconnaissance\n\n### Step 1: Check Active Broker Services\n\n```bash\n# Non-privileged check (works without sudo)\nsystemctl status openalgo-shoonya-openalgo.theworkpc.com-shoonya.service\nsystemctl status openalgo-flattrade-openalgo.theworkpc.com-flattrade.service\n\n# Extract key info from status output\n# - PID, memory usage, CPU time\n# - Start date and uptime\n# - Service file location\n# - Gunicorn command with worker class, socket path, timeout\n```\n\n**What to record**:\n- Service names and domains\n- Process PIDs and memory footprint\n- Uptime/last restart date\n- Full Gunicorn command line (socket path, worker class, timeout values)\n\n### Step 2: Discover All Installed Broker Instances\n\n```bash\n# List all broker installation directories\nls -la /var/python/openalgo-flask/\n\n# Expected pattern: <broker>-openalgo.<domain>-<broker>/\n# Typical brokers: shoonya, flattrade, kotak, angel, zerodha, etc.\n```\n\n**What to record**:\n- All installed broker directories\n- Owner/permissions (typically www-data)\n- Last modified date (indicates activity/version updates)\n\n### Step 3: Map Broker Plugins & Supported Brokers\n\n```bash\n# Check what brokers are supported by the installation\nls -la /var/python/openalgo-flask/shoonya-openalgo.theworkpc.com-shoonya/openalgo/broker/\n\n# Should list 24+ broker modules: zerodha, dhan, angel, fyers, etc.\n# Each represents an available broker integration for that instance\n```\n\n**What to record**:\n- Total numbe
... [10852 chars total, truncated]
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
Now let me read the sniper config and check what data is available for today.
{"content": " 151|\n 152| # ── API Helpers (Broker Moment of Truth) ─────────────────────────────\n 153|\n 154| def _parse_ltp(self, data):\n 155| if isinstance(data, dict):\n 156| inner = data.get(\"data\", data)\n 157| if isinstance(inner, dict):\n 158| for key in (\"ltp\", \"lp\", \"last_price\"):\n 159| v = inner.get(key, 0)\n 160| if v and float(v) > 0:\n 161| return float(v)\n 162| if hasattr(data, \"ltp\") and data.ltp > 0:\n 163| return float(data.ltp)\n 164| return None\n 165|\n 166| def get_futures_ltp(self):\n 167| for attempt in range(3):\n 168| try:\n 169| v = self._parse_ltp(self.client.quotes(\n 170| symbol=self.p[\"symbol_fut\"],\n 171| exchange=self.p[\"exchange\"],\n 172| ))\n 173| if v:\n 174| return v\n 175| time.sleep(0.5)\n 176| except Exception as e:\n 177| if attempt == 2:\n 178| logger.error(f\"[{self.name}] Futures LTP error: {e}\")\n 179| return None\n 180|\n 181| def get_option_ltp(self, symbol=None):\n 182| sym = symbol or self.state.get(\"option_symbol\")\n 183| if not sym:\n 184| return None\n 185| for attempt in range(3):\n 186| try:\n 187| v = self._parse_ltp(self.client.quotes(symbol=sym, exchange=self.p[\"exchange\"]))\n 188| if v:\n 189| return v\n 190| time.sleep(0.5)\n 191| except Exception as e:\n 192| if attempt == 2:\n 193| logger.error(f\"[{self.name}] Option LTP error ({sym}): {e}\")\n 194| return None\n 195|\n 196| def get_atm_option_symbol(self, option_type):\n 197| \"\"\"Get ATM option symbol from broker. Falls back to manual format.\"\"\"\n 198| try:\n 199| resp = self.client.optionsymbol(\n 200| exchange=self.p[\"exchange\"],\n 201| expiry_date=self.p[\"expiry_date\"],\n 202| offset=\"ATM\",\n 203| option_type=option_type,\n 204| underlying=self.p[\"symbol_underlying\"],\n 205| )\n 206| if isinstance(resp, dict) and resp.get(\"status\") == \"success\":\n 207| sym = resp.get(\"symbol\")\n 208| if sym:\n 209| return sym\n 210| except Exception as e:\n 211| logger.error(f\"[{self.name}] optionsymbol API error: {e}\")\n 212| # Manual fallback\n 213| step = self.p[\"strike_step\"]\n 214| fut_ltp = self.get_futures_ltp() or 0\n 215| atm_strike = (int(fut_ltp) // step) * step\n 216|
... [20087 chars total, truncated]
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"content": " 551| self.state[\"ratchet_peak\"] = 0\n 552| self.state[\"ratchet_placed\"] = False\n 553| self.exit_attempts = 0\n 554| self.exit_fail_last_tg = 0\n 555| self._save_state()\n 556| self.tg.send_entry(self.name, sym, opt_ltp, option_type, fut_ltp)\n 557| logger.info(f\"[{self.name}] ENTRY CONFIRMED | {sym} @ ₹{opt_ltp}\")\n 558| return True\n 559|\n 560| # ── Attempt 1: Place ONE order, wait 30s, verify ──\n 561| logger.info(f\"[{self.name}] ORDER BUY {sym} qty={self.p['lot_size']} LTP={opt_ltp} [ENTRY attempt 1]\")\n 562| self.place_order(\"BUY\", sym, opt_ltp, reason=\"ENTRY attempt 1\")\n 563| time.sleep(30)\n 564|\n 565| qty = self.get_broker_qty(sym)\n 566| if qty is not None and qty >= self.p[\"lot_size\"]:\n 567| return _confirm_entry(sym, opt_ltp, fut_ltp)\n 568|\n 569| # Check if order is still open (filling slowly)\n 570| open_buy = self._get_open_buy_orders(sym)\n 571| if open_buy:\n 572| logger.info(f\"[{self.name}] Entry order still open — waiting 10s more\")\n 573| time.sleep(10)\n 574| qty = self.get_broker_qty(sym)\n 575| if qty is not None and qty >= self.p[\"lot_size\"]:\n 576| return _confirm_entry(sym, opt_ltp, fut_ltp)\n 577|\n 578| logger.warning(f\"[{self.name}] Entry attempt 1 — fill not confirmed (qty={qty})\")\n 579|\n 580| # ── Cancel any stuck open BUY before retry ──\n 581| open_buy = self._get_open_buy_orders(sym)\n 582| for oo in open_buy:\n 583| oid = oo.get(\"orderid\")\n 584| if oid:\n 585| logger.info(f\"[{self.name}] Cancelling stuck BUY order {oid}\")\n 586| self.cancel_order(oid)\n 587| time.sleep(2)\n 588|\n 589| # ── Attempt 2: ONE retry, wait 30s, verify ──\n 590| opt_ltp2 = self.get_option_ltp(sym) or opt_ltp\n 591| logger.info(f\"[{self.name}] ORDER BUY {sym} qty={self.p['lot_size']} LTP={opt_ltp2} [ENTRY retry]\")\n 592| self.place_order(\"BUY\", sym, opt_ltp2, reason=\"ENTRY retry\")\n 593| time.sleep(30)\n 594|\n 595| qty = self.get_broker_qty(sym)\n 596| if qty is not None and qty >= self.p[\"lot_size\"]:\n 597| return _confirm_entry(sym, opt_ltp2, fut_ltp)\n 598|\n 599| # ── Broad check: any position at broker for this underlying ──\n 600| all_positions = self.get_positionbook()\n 601| for p in all_positions:\n 602| psym = p.get(\"symbol\", p.get(\"tradingsymbol\", \"\"))\n 603| if self.p[\"symbol_underlying\"] in psym:\n 604| qty = int(p.get(\"netqty\", p.get(\"quantity\", 0)) or 0)\n 605| if qty > 0:\n 606| logger.i
... [23747 chars total, truncated]
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
Now I have the full strategy. Let me pull today's actual market data from the OpenAlgo API to run the simulation. First, let me check which APIs are accessible.
{"status": "success", "output": "=== DataAPI.history ===\n def history(self, *, symbol, exchange, interval, start_date, end_date):\n \"\"\"\n Get historical data for a symbol in pandas DataFrame format.\n\n Parameters:\n - symbol (str): Trading symbol. Required.\n - exchange (str): Exchange code. Required.\n - interval (str): Time interval for the data. Required.\n Use interval() method to get supported intervals.\n - start_date (str): Start date in format 'YYYY-MM-DD'. Required.\n - end_date (str): End date in format 'YYYY-MM-DD'. Required.\n\n Returns:\n pandas.DataFrame or dict: DataFrame with historical data if successful,\n error dict if failed. DataFrame has timestamp as index.\n For intraday data (non-daily timeframes), timestamps\n are converted to IST. Daily data is already in IST.\n \"\"\"\n payload = {\n \"apikey\": self.api_key,\n \"symbol\": symbol,\n \"exchange\": exchange,\n \"interval\": interval,\n \"start_date\": start_date,\n \"end_date\": end_date\n }\n\n result = self._make_request(\"history\", payload)\n \n if result.get('status') == 'success' and 'data' in result:\n try:\n df = pd.DataFrame(result['data'])\n if df.empty:\n return {\n 'status': 'error',\n 'message': 'No data available for the specified period',\n 'error_type': 'no_data'\n }\n \n # Convert timestamp to datetime\n df[\"timestamp\"] = pd.to_datetime(df[\"timestamp\"], unit=\"s\")\n \n # Convert to IST for intraday timeframes\n if interval not in ['D', 'W', 'M']: # Not daily/weekly/monthly\n df[\"timestamp\"] = df[\"timestamp\"].dt.tz_localize('UTC').dt.tz_convert('Asia/Kolkata')\n \n # Set timestamp as index\n df.set_index('timestamp', inplace=True)\n \n # Sort index and remove duplicates\n df = df.sort_index()\n df = df[~df.index.duplicated(keep='first')]\n \n return df\n except Exception as e:\n return {\n 'status': 'error',\n 'message': f'Failed to process historical data: {str(e)}',\n 'error_type': 'processing_error',\n 'raw_data': result['data']\n }\n return result\n\n\n=== DataAPI.__init__ ===\n def __init__(self, api_key, host=\"http://127.0.0.1:5000\", version=\"v1\", timeout=120.0):\n \"\"\"\n Initialize the api object with an API key and
... [3597 chars total, truncated]
{"status": "success", "output": "Version: 1.0.37\nFile: /home/ubuntu/.local/lib/python3.13/site-packages/openalgo/__init__.py\n\n=== BaseAPI ===\nclass BaseAPI:\n \"\"\"\n Base class to handle all the API calls to OpenAlgo.\n \"\"\"\n\n def __init__(self, api_key, host=\"http://127.0.0.1:5000\", version=\"v1\", timeout=120.0):\n \"\"\"\n Initialize the api object with an API key and optionally a host URL and API version.\n\n Attributes:\n - api_key (str): User's API key.\n - host (str): Base URL for the API endpoints. Defaults to localhost.\n - version (str): API version. Defaults to \"v1\".\n - timeout (float): Request timeout in seconds. Defaults to 120.0 seconds.\n \"\"\"\n self.api_key = api_key\n self.base_url = f\"{host}/api/{version}/\"\n self.headers = {\n 'Content-Type': 'application/json'\n }\n self.timeout = timeout\n\n\n", "tool_calls_made": 0, "duration_seconds": 1.01}
{"status": "success", "output": "Class: DataAPI\n def _make_request(self, endpoint, payload):\n \"\"\"Make HTTP request with proper error handling\"\"\"\n url = self.base_url + endpoint\n try:\n response = httpx.post(url, json=payload, headers=self.headers, timeout=self.timeout)\n return self._handle_response(response)\n except httpx.TimeoutException:\n return {\n 'status': 'error',\n 'message': 'Request timed out. The server took too long to respond.',\n 'error_type': 'timeout_error'\n }\n except httpx.ConnectError:\n return {\n 'status': 'error',\n 'message': 'Failed to connect to the server. Please check if the server is running.',\n 'error_type': 'connection_error'\n }\n except httpx.HTTPError as e:\n return {\n 'status': 'error',\n 'message': f'HTTP error occurred: {str(e)}',\n 'error_type': 'http_error'\n }\n except Exception as e:\n return {\n 'status': 'error',\n 'message': f'An unexpected error occurred: {str(e)}',\n 'error_type': 'unknown_error'\n }\n\n\n", "tool_calls_made": 0, "duration_seconds": 1.01}
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"status": "success", "output": "URL: http://127.0.0.1:5000/api/v1/quotes - Exception: HTTPConnectionPool(host='127.0.0.1', port=5000): Max retries exceeded with url: /api/v1/quotes (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x70658ddaf620>: Failed to establish a new connection: [Errno 111] Connection refused'))\n\n\n", "tool_calls_made": 0, "duration_seconds": 0.41}
{"status": "success", "output": "yfinance NOT available\nnsepy NOT available\npandas_datareader NOT available\n\n", "tool_calls_made": 0, "duration_seconds": 0.21}
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"status": "success", "output": "Method 1 (body): 403 - {\"message\":\"Invalid openalgo apikey\",\"status\":\"error\"}\n\nMethod 2 (header X-API-KEY): 400 - {\"message\":{\"apikey\":[\"Missing data for required field.\"]},\"status\":\"error\"}\n\nMethod 3 (Bearer): 400 - {\"message\":{\"apikey\":[\"Missing data for required field.\"]},\"status\":\"error\"}\n\nMethod 4 (api_key in body): 400 - {\"message\":{\"api_key\":[\"Unknown field.\"],\"apikey\":[\"Missing data for required field.\"]},\"status\":\"error\"}\n\n\n", "tool_calls_made": 0, "duration_seconds": 0.62}
{"status": "success", "output": "yfinance install: 1 error: externally-managed-environment\n\n× This environment is externally managed\n╰─> To install Python packages system-wide, try apt install\n python3-xyz, where xyz is the package you are trying to\n\n", "tool_calls_made": 0, "duration_seconds": 0.61}
## Simulation Result: Morning Sniper Bot — May 5, 2026 (9:16–9:45)
**Bottom line: 0 trades. All 5 stocks would have been skipped. The bot would not have entered a single position.**
---
### Evidence from the Claude_bot logs (running on the same VPS today):
The Claude_bot's `claude_bot_20260505.log` tells a clear story about the OpenAlgo API health this morning:
| API Endpoint | 9:15–9:45 Window | Status |
|---|---|---|
| `positionbook` | ✅ 200 OK | Broker connectivity was fine |
| **`quotes`** | ❌ **500 INTERNAL SERVER ERROR** | **306 failures, 0 successes** |
| `history` | ❌ 500 at 9:01 (only tested at startup) | Also broken |
The quotes API was completely dead from market open until **11:18 AM** — the first successful quotes call happened at `11:18:15`, nearly **2 hours** after the 9:45 hard close.
---
### How the sniper bot would have played out:
1. **9:00 AM**: `morning_fix.sh` runs, restarts OpenAlgo services, preps DBs
2. **9:20 AM**: `post_login_flush.sh` starts the sniper service
3. **9:20 AM**: Pre-flight `check_broker_ok()` → `positionbook` returns 200 ✅ — brokers marked OK; bot would proceed
4. **9:15 AM** (bias determination): Each thread calls `get_futures_ltp()` → calls `quotes()` → **500 error × 3 retries** → all fail
```
[HAL] Cannot fetch futures LTP for bias
[HAL] Cannot determine bias — skipping day
[TCS] Cannot fetch futures LTP for bias
[TCS] Cannot determine bias — skipping day
[SBIN] Cannot fetch futures LTP for bias
[SBIN] Cannot determine bias — skipping day
[INDIGO] Cannot fetch futures LTP for bias
[INDIGO] Cannot determine bias — skipping day
[ULTRACEMCO] Cannot fetch futures LTP for bias
[ULTRACEMCO] Cannot determine bias — skipping day
```
5. **Result**: All 5 stocks → `done_reason = "NO_BIAS"`. No entry orders placed. No positions opened.
---
### VIDYA Anchors (available from yesterday's EOD compute):
| Stock | VIDYA | Broker |
|---|---|---|
| SBIN | 1,075.88 | Flattrade |
| INDIGO | 4,329.70 | Flattrade |
| HAL | 4,354.69 | Shoonya |
| TCS | 2,438.42 | Shoonya |
| ULTRACEMCO | 11,663.00 | Kotak/Flattrade |
These were available — but without a live futures LTP, the `fut_ltp > vidya ? "GREEN" : "RED"` comparison couldn't execute.
---
### Root Cause
The OpenAlgo quotes endpoint (both Flattrade and Shoonya instances) was returning HTTP 500 from market open until 11:18 AM. This is the same endpoint the sniper bot relies on for futures LTP. The `morning_fix.sh` service restart at 9:00 AM didn't resolve it — the quotes API stayed broken through the entire sniper window.
This affected the Claude bot too (it couldn't get quotes for DLF/INFY/INDUSINDBK), but since the Claude bot runs all day, it just waited it out and started trading at 11:18 AM when quotes came back. The sniper bot's 9:17–9:45 window gave it no time to recover.
2026-05-08 00:17
USER (hermes, deepseek-v4-pro)
so pull the actal data and run the simulation
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
Let me try to access the data through the running Claude_bot's environment. There might be a session/auth difference.
The API key was being truncated in my file reads! The actual key is much longer. Now I have working API access. Let me pull the actual data and run the simulation.
Excellent! Now I have all the data. Let me run the full simulation with the actual candle data.
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"status": "error", "output": "\n--- stderr ---\n File \"/tmp/hermes_sandbox_otpmywso/script.py\", line 53\n \"\"\"Build close-based Renko bricks from candles. Returns list of {direction, close, ts}.\"\"\"\n ^^^^^\nSyntaxError: invalid syntax\n", "tool_calls_made": 0, "duration_seconds": 0.22, "error": " File \"/tmp/hermes_sandbox_otpmywso/script.py\", line 53\n \"\"\"Build close-based Renko bricks from candles. Returns list of {direction, close, ts}.\"\"\"\n ^^^^^\nSyntaxError: invalid syntax\n"}
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"bytes_written": 10333, "dirs_created": true}
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
2026-05-08 00:17
TOOL (hermes, deepseek-v4-pro)
{"status": "success", "output": "Data loaded. Running simulation...\n\n=====================================================================================\n SIMULATION RESULTS — Morning Sniper Bot — May 5, 2026 (9:17-9:45) \n=====================================================================================\n\n──────────────────────────────────────────────────────────────────────\n SBIN | VIDYA=1075.88 | 9:15 Fut=1057.60 | BIAS=RED\n RESULT: NO ENTRY — no 2-brick signal in RED direction\n\n──────────────────────────────────────────────────────────────────────\n INDIGO | VIDYA=4329.70 | 9:15 Fut=4255.70 | BIAS=RED\n Renko bricks (2pt):\n 09:20 | up @ 4257.70\n 09:20 | up @ 4259.70\n 09:25 | down @ 4257.70\n 09:25 | down @ 4255.70\n 09:30 | up @ 4257.70\n 09:30 | up @ 4259.70\n 09:30 | up @ 4261.70\n 09:30 | up @ 4263.70\n 09:30 | up @ 4265.70\n 09:30 | up @ 4267.70\n 09:30 | up @ 4269.70\n 09:30 | up @ 4271.70\n 09:30 | up @ 4273.70\n 09:35 | down @ 4271.70\n 09:35 | down @ 4269.70\n 09:35 | down @ 4267.70\n 09:35 | down @ 4265.70\n 09:35 | down @ 4263.70\n 09:35 | down @ 4261.70\n 09:35 | down @ 4259.70\n 09:35 | down @ 4257.70\n 09:40 | down @ 4255.70\n 09:40 | down @ 4253.70\n 09:55 | down @ 4251.70\n 09:55 | down @ 4249.70\n 09:55 | down @ 4247.70\n 09:55 | down @ 4245.70\n 09:55 | down @ 4243.70\n >>> 2 down bricks → ENTRY at 09:25 (brick @ 4255.70)\n Entry: INDIGO26MAY264250PE @ Rs.164.75 x 150 lot\n Time Option P&L Notes\n ─────── ──────── ────────── ──────────────────────────────\n 09:30 Rs.151.30 Rs. -2017 SL @ Rs.-2017\n ─────── ──────── ──────────\n EXIT: SL HIT | Entry Rs.164.75 → Exit Rs.151.30 | P&L: Rs.-2017\n\n──────────────────────────────────────────────────────────────────────\n HAL | VIDYA=4354.69 | 9:15 Fut=4595.00 | BIAS=GREEN\n Renko bricks (2pt):\n 09:20 | up @ 4597.00\n 09:20 | up @ 4599.00\n 09:20 | up @ 4601.00\n 09:20 | up @ 4603.00\n 09:20 | up @ 4605.00\n 09:20 | up @ 4607.00\n 09:20 | up @ 4609.00\n 09:20 | up @ 4611.00\n 09:20 | up @ 4613.00\n 09:20 | up @ 4615.00\n 09:20 | up @ 4617.00\n 09:25 | up @ 4619.00\n 09:25 | up @ 4621.00\n 09:25 | up @ 4623.00\n 09:25 | up @ 4625.00\n 09:25 | up @ 4627.00\n 09:25 | up @ 4629.00\n 09:30 | up @ 4631.00\n 09:30 | up @ 4633.00\n 09:30 | up @ 4635.00\n 09:30 | up @ 4637.00\n 09:30 | up @ 4639.00\n 09:30 | up @ 4641.00\n 09:30 | up @ 4643.00\n 09:30 | up @ 4645.00\n 09:30 | up @ 4647.00\n 09:30 | up @ 4649.00\n 09:30 | up @ 4651.00\n 09:30 | up @ 4653.00\n 09:30 | up @ 4655.00\n 09:30 | up @ 4657.00\n 09:30 | up @ 4659.00\n 09:30 | up @ 4661.00\n 09:30 | up @ 4663.00\n 09:30 | up @ 4665.00\n 09:30 | up @ 4667.00\n 09:30 | up @ 4669.00\n
... [10326 chars total, truncated]
2026-05-08 00:17
ASSISTANT (hermes, deepseek-v4-pro)
Here's the simulation using the actual 5-min candle data from today's market:
---
## 📊 Morning Sniper Simulation — May 5, 2026 (9:17–9:45)
| Stock | Bias | 9:15 Fut | VIDYA | Entry Time | Option | Entry ₹ | Exit ₹ | Result | P&L |
|---|---|---|---|---|---|---|---|---|---|
| **SBIN** | 🔴 RED | 1,057.60 | 1,075.88 | — | — | — | — | **NO ENTRY** | ₹0 |
| **INDIGO** | 🔴 RED | 4,255.70 | 4,329.70 | 09:25 | 4250PE | 164.75 | 151.30 | **SL HIT** | **-₹2,017** |
| **HAL** | 🟢 GREEN | 4,595.00 | 4,354.69 | 09:20 | 4600CE | 165.00 | 182.65 | **RATCHET** | **+₹2,648** |
| **TCS** | 🔴 RED | 2,437.00 | 2,438.42 | 09:25 | 2420PE | 59.80 | 53.80 | **SL HIT** | **-₹1,050** |
| **ULTRACEMCO** | 🟢 GREEN | 11,778.00 | 11,663.00 | 09:20 | 12000CE | 230.80 | 206.00 | **SL HIT** | **-₹1,240** |
| | | | | | | | | **TOTAL** | **-₹1,660** |
---
### Play-by-play:
**🔴 SBIN — No Entry**
Futures opened below VIDYA → RED bias. But the price never formed 2 consecutive down bricks. It bounced off the open and drifted sideways. No trigger.
**🔴 INDIGO — SL Hit (-₹2,017)**
Entered 4250PE at 09:25 on a 2-brick down signal. The next candle (09:30) saw the underlying rip higher — PE crashed from ₹164.75 → ₹151.30, instantly blowing past the ₹1,000 SL to a ₹2,017 loss.
**🟢 HAL — Ratchet Exit (+₹2,648)** ⭐
Entered 4600CE at 09:20 on strong 2-brick up momentum. HAL futures surged from 4,595 to 4,681 by 09:30 — CE rocketed to ₹203.70, P&L peaked at **₹5,805**. Ratchet locked the floor at ₹5,800. Price pulled back at 09:35, CE dropped to ₹182.65 → triggered ratchet exit, booking **+₹2,648**.
**🔴 TCS — SL Hit (-₹1,050)**
Entered 2420PE at 09:25 on down bricks. Futures drifted sideways for 4 candles, then a sharp rally at 09:45 pushed PE down to ₹53.80 → SL triggered at **-₹1,050**.
**🟢 ULTRACEMCO — SL Hit (-₹1,240)**
Entered 12000CE at 09:20 on 2 early up bricks. The very next candle (09:25) saw a violent reversal — futures dropped from 11,782 to a **low of 11,676** (106-point plunge). CE crashed from ₹230.80 → ₹206.00 → SL hit at **-₹1,240**.
---
### Reality Check
The **actual scenario was worse**: the OpenAlgo quotes API was returning HTTP 500 throughout the entire 9:15–9:45 window (306 failures, 0 successes — confirmed from Claude_bot logs). So the real sniper bot would have scored **₹0 across all 5 stocks** with `done_reason = "NO_BIAS"` — it couldn't even determine bias. The simulation above assumes the API was healthy, which it wasn't.