scdenney/open-science-skills · codex/vlm-ocr/SKILL.md

vlm-ocr skillA

OCR scanned or image-only corpora with vision-language models, in three phases. Use `evaluate` to compare candidate OCR systems against stratified human ground truth and pick one on measured CER/WER, `run` to build the production pipeline (model selection, image handling, prompts, architecture, batching, accuracy evaluation, reproducibility), and `clean` to correct raw OCR text with LLM and rule-based passes, quality diagnostics, multilingual handling, and span-level provenance. Not for born-dig

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Versions

version	committed	commit	size	audit
git:20260902.da5a263 latest	2026-09-02	da5a263	49,042 B	A	view

Audit of the latest version

A 17 of 17 checks passed. Deterministic, no model, same answer every run.

pass: Frontmatter block present
pass: Frontmatter declares a name
pass: Frontmatter declares a description
pass: Size between 200 bytes and 200 KB (49042 bytes)
pass: No zero-width or bidi control characters
pass: No instruction hidden inside an HTML comment
pass: No link to an exfiltration or paste host
pass: No credential-shaped string
pass: No instruction to send local credentials anywhere
pass: No text hidden with inline styles
pass: No prompt-injection phrasing
pass: No curl or wget piped into a shell
pass: No recursive delete of root, home or parent
pass: No instruction to read or print local credentials
pass: No base64 blob over 200 characters
pass: No link to a raw IP address
pass: No script tag

Source

GitHub

scdenney/open-science-skills · 54 stars · license NOASSERTION · pushed 2026-09-05 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_zsnnj5kn4i67xp4d
GET https://markdownregistry.com/api/v1/resolve?ref=scdenney/open-science-skills/vlm-ocr
GET https://markdownregistry.com/api/v1/blob/26c0b8595f4f3cfdd62cca64519bfb3a736963dbdf9ffc3fd08a50578a837a65