finance-ocr-pro

# Finance OCR Pro Run this skill only after OCR intent from the user. This skill is especially helpful for financial reports, annual reports, prospectuses, investor presentations, regulatory filings, research reports, and other documents with complicated structure, charts, graphs, tables, and mixed layout elements. ## Security And Privacy Before running OCR, make the operating model clear: - This skill requires three environment variables, all of which must be configured before OCR can run: - `API_KEY` (sensitive) -- the API key for authenticating with the VLM endpoint. - `BASE_URL` -- the base URL of the OpenAI-compatible VLM endpoint. All page images and OCR prompts are transmitted to this URL. - `VLM_MODEL` -- the vision-capable model identifier. Must support image inputs; text-only models will not work. - OCR sends rendered page images and structured prompts to `BASE_URL`. This is the primary data-transmission path. Users must verify that the endpoint is trusted before processing sensitive documents. - If the user wants offline or local-only OCR, `BASE_URL` must point to a local VLM service. Do not run this skill against an external endpoint with sensitive documents unless the provider is trusted. - Never commit a populated `.env` file. Use `.env.example` as a template and keep real credentials local. ## Pre-Run Notice After the user asks for OCR or extraction, give a short notice that includes: - whether `BASE_URL` is local or remote - which `VLM_MODEL` will be used - which execution mode will be used - where results will be written - that page images and prompts will be transmitted to the configured endpoint Proceed automatically unless the user asks to change those defaults. ## Defaults To Announce - Running mode: background job by default - Model: `VLM_MODEL` - Threads: `1` - Result path: - background: `~/.semantic-ocr/jobs/<job_id>/results/` - synchronous: `ocr_output/OCR_<filename>/results/` ## Setup Use the skill-local virtual environment if present. - macOS/Linux: `.venv/bin/python` - Windows: `.venv/Scripts/python.exe` - Fallback: `python` Run: ```bash python scripts/ocr_setup.py --check ``` If setup is incomplete, run: ```bash python scripts/ocr_setup.py ``` ## Preferred Execution By default, start a background worker: ```bash python scripts/ocrctl.py --json start /path/to/document.pdf ``` Then inspect progress and outputs: ```bash python scripts/ocrctl.py --json status <job_id> python scripts/ocrctl.py --json artifacts <job_id> python scripts/ocrctl.py --json tail <job_id> ``` Use synchronous mode only when the user explicitly wants inline execution: ```bash python scripts/ocr_main.py /path/to/document.pdf ``` ## Notes - Inputs: PDF, common office documents, Apple office formats, and images. - Outputs: merged Markdown, HTML review report, DOCX, and Excel. - OCR requires `API_KEY`, `BASE_URL`, and `VLM_MODEL` to be configured before running. - Sensitive document pages are transmitted to the configured endpoint during OCR unless the endpoint is a local service. - Best suited for financial documents and other visually dense materials with tables, charts, graphs, and complex page structure. - Office-document conversion may require LibreOffice. - OCR extraction by the VLM model may be time-consuming; check the status regularly.