Add log-work-expense skill to skill index

log-work-expense/SKILL.md

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+---
+name: log-work-expense
+description: Log work expenses into MongoDB. Use when the user sends receipt images or odometer photos along with context, or says things like "log this expense", "record this receipt", "mileage for XYZ", "meals for XYZ", or provides any expense details for work reimbursement tracking. Triggers on any message that includes expense context (account, type, images of receipts or odometers).
+---
+
+# Log Work Expense
+
+Log work expenses into `wip.work_expenses` via `scripts/log_expense.py`.
+
+## Trigger Phrases
+
+- "log this expense", "record this receipt", "add this to my work expenses"
+- "mileage for XYZ", "meals for XYZ"
+
+## Steps
+
+1. **Classify images** — Run each image through `scripts/classify_image.py <path>` to determine if it is a `receipt` or `odometer`. The script outputs exactly one word.
+
+2. **Determine type and account** — The user provides the expense type and account (e.g. "meals and mileage for LTISD"). Ask if unclear.
+
+3. **Upload images to S2** — Upload all images to S2 and collect the URLs.
+
+4. **Insert via script** — Run the script once **per entry**:
+
+```bash
+uv run --with pymongo ~/notes/skills/log-work-expense/scripts/log_expense.py <type> <account> <date> "<note>" <s2_url_1> [s2_url_2]
+```
+
+- **Meal receipts**: Run once per receipt (1 file each).
+- **Mileage**: Run once with both odometer URLs (2 files).
+
+The script enforces file counts and rejects invalid input.
+
+5. **Confirm** — Brief summary of what was logged.
+
+## Notes
+- Use `classify_image.py` for image classification — it calls the vision model and returns only "receipt" or "odometer".
+- Use the S2 upload endpoint from TOOLS.md for file uploads.
+- The log script hardcodes MongoDB connection details — do not pass credentials.

log-work-expense/scripts/classify_image.py

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+#!/usr/bin/env python3
+"""Classify an image as 'receipt' or 'odometer'.
+
+Usage:
+    python classify_image.py <image_path>
+
+Prints exactly one word: "receipt" or "odometer"
+"""
+
+import sys
+import base64
+import requests
+
+API_KEY = "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"
+MODEL = "google/gemini-2.5-flash-lite"
+
+def main():
+    if len(sys.argv) != 2:
+        print("Usage: classify_image.py <image_path>", file=sys.stderr)
+        sys.exit(1)
+
+    path = sys.argv[1]
+    with open(path, "rb") as f:
+        b64 = base64.b64encode(f.read()).decode()
+
+    ext = path.rsplit(".", 1)[-1].lower()
+    mime = "image/jpeg" if ext in ("jpg", "jpeg") else "image/png"
+
+    resp = requests.post(
+        "https://openrouter.ai/api/v1/chat/completions",
+        headers={"Authorization": f"Bearer {API_KEY}", "Content-Type": "application/json"},
+        json={
+            "model": MODEL,
+            "messages": [{"role": "user", "content": [
+                {"type": "text", "text": "Classify this image. Reply with exactly one word: receipt or odometer. Nothing else."},
+                {"type": "image_url", "image_url": {"url": f"data:{mime};base64,{b64}"}}
+            ]}],
+            "max_tokens": 10
+        },
+        timeout=30,
+    )
+
+    text = resp.json()["choices"][0]["message"]["content"].strip().lower()
+    if "receipt" in text:
+        print("receipt")
+    elif "odometer" in text:
+        print("odometer")
+    else:
+        print(f"unknown: {text}", file=sys.stderr)
+        sys.exit(1)
+
+if __name__ == "__main__":
+    main()

log-work-expense/scripts/log_expense.py

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+#!/usr/bin/env python3
+"""Log work expenses to MongoDB (wip.work_expenses).
+
+Usage:
+    python log_expense.py <type> <account> <date> <note> <s2_url_1> [s2_url_2]
+
+    type:    "meal" or "mileage"
+    account: e.g. "LTISD"
+    date:    YYYY-MM-DD
+    note:    free-text context (quote if it has spaces)
+    s2_url:  one or more S2 URLs of uploaded files
+
+Rules enforced:
+    - meal:    exactly 1 file per invocation
+    - mileage: exactly 2 files per invocation (start + end odometer)
+"""
+
+import sys
+from pymongo import MongoClient
+
+def main():
+    args = sys.argv[1:]
+    if len(args) < 5:
+        print("Usage: log_expense.py <type> <account> <date> <note> <s2_url_1> [s2_url_2]")
+        sys.exit(1)
+
+    exp_type = args[0]
+    account = args[1]
+    date = args[2]
+    note = args[3]
+    files = args[4:]
+
+    if exp_type not in ("meal", "mileage"):
+        print(f"Error: type must be 'meal' or 'mileage', got '{exp_type}'")
+        sys.exit(1)
+
+    if exp_type == "meal" and len(files) != 1:
+        print(f"Error: meal entries must have exactly 1 file, got {len(files)}")
+        sys.exit(1)
+
+    if exp_type == "mileage" and len(files) != 2:
+        print(f"Error: mileage entries must have exactly 2 files (start + end odometer), got {len(files)}")
+        sys.exit(1)
+
+    client = MongoClient("mongodb://root:3wwfoUjyk2E2zWELXFlLuHqfw1ALlOp4pb2H5Vq3TImbMIHL2h1u8Jej2mjzCPl@docdb.connorrhodes.com:35563")
+    db = client["wip"]
+    col = db["work_expenses"]
+
+    doc = {
+        "files": files,
+        "date": date,
+        "type": exp_type,
+        "account": account,
+        "note": note,
+        "status": "todo"
+    }
+
+    result = col.insert_one(doc)
+    print(f"Inserted {exp_type} for {account} on {date}: {result.inserted_id}")
+
+if __name__ == "__main__":
+    main()