Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add OpenLAIR/OpenSkill --skill evo-ocr-preprocess-extractgit clone --depth 1 https://github.com/OpenLAIR/OpenSkillWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/openlair/openskill/evo-ocr-preprocess-extract)<a href="https://agentmods.dev/skills/openlair/openskill/evo-ocr-preprocess-extract"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-ocr-preprocess-extract/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/openlair/openskill/evo-ocr-preprocess-extract"><img src="https://agentmods.dev/badge/skills/openlair/openskill/evo-ocr-preprocess-extract.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00029 | $0.00335 |
| Opus 5 | $0.00015 | $0.00168 |
| Sonnet 5 | $0.00006 | $0.00067 |
| Haiku 4.5 | $0.00003 | $0.00034 |
Grade A, and why
evo-ocr-preprocess-extract scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
evo-ocr-preprocess-extract
Preprocesses receipt images using Pillow (grayscale, upscaling, contrast enhancement, binarization) and extracts raw text using pytesseract with optimal PSM configuration for receipt layouts.
Key Functions
get_sorted_image_files(directory_path)- Returns sorted list of (filename, full_path) tuplespreprocess_image(image_path, scale_factor=2, contrast_factor=2.0, threshold=140)- Preprocesses image for OCRextract_text_from_image(image_path, psm=4, oem=3, ...)- Extracts text with preprocessing + Tesseractextract_text_multi_config(image_path)- Tries multiple configs for best result
Usage
import sys
sys.path.insert(0, '/app/environment/skills/evo-ocr-preprocess-extract/scripts')
from utils import get_sorted_image_files, extract_text_from_image
files = get_sorted_image_files('/path/to/images')
for filename, filepath in files:
text = extract_text_from_image(filepath)
Pipeline
- Grayscale conversion (handles RGBA/RGB)
- 2x upscale with LANCZOS resampling
- Contrast enhancement (factor 2.0)
- Median filter denoising
- Binarization (threshold 140)
- Tesseract OCR with PSM 4 (single column)
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 36 lines · 29 tokens per session scan A 3d25c307d10c
evo-ocr-preprocess-extract is a skill published in the GitHub repository OpenLAIR/OpenSkill (90 stars, last pushed 2d ago), licensed Apache-2.0. It adds 29 tokens to every session and 335 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-11.
Other skills, from other repositories
stripe-best-practices
Guides Stripe integration decisions across development and test environment planning (separate sandboxes vs the shared test mode sandbox), API selection (Checkout Sessions vs PaymentIntents), Connect platform setup (Accounts v2, controller properties), billing/subscriptions, tax and registrations (Stripe Tax…
amazon-listing
Amazon listing CRUD via the category flat-file (Add Products via Upload). Create a variation family (parent + colour/size children), update attributes, change parent-child relationships, and delete SKUs — all in one template round trip. Also covers the end-to-end sourcing flow: a supplier link (e.g. 1688) → extract…
amazon-invoice
Generate tax invoices from Amazon Seller Central order data using browser extraction and PDF generation.
shopify-admin-gift-message-extraction
Read-only: extracts gift messages, gift recipients, and gift flags from order custom attributes and notes for fulfillment teams to print on packing slips.
slidecraft
Convert PowerPoint (PPTX) files to HTML and back, analyze PPTX structure, generate slide decks from topics via LLM, pre-cache CDN assets, or launch the interactive review web UI. Use this when the user wants to work with PowerPoint presentations -- convert ppt to html, html to pptx, inspect pptx contents, or generate…
kb-import
Agent-guided procedure to import an existing non-OKF wiki or knowledge base (Obsidian vault, markdown folder, wiki export) into a Cartographer KB, incrementally and without big-bang LLM rewriting.