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 aaronnat23/disp8ch --skill ocr-and-documentsgit clone --depth 1 https://github.com/aaronnat23/disp8chWrote 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/aaronnat23/disp8ch/ocr-and-documents)<a href="https://agentmods.dev/skills/aaronnat23/disp8ch/ocr-and-documents"><img src="https://agentmods.dev/badge/skills/aaronnat23/disp8ch/ocr-and-documents/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/aaronnat23/disp8ch/ocr-and-documents"><img src="https://agentmods.dev/badge/skills/aaronnat23/disp8ch/ocr-and-documents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00000 | $0.00166 |
| Opus 5.5 | $0.00000 | $0.00066 |
| Sonnet 5.5 | $0.00000 | $0.00033 |
| Haiku 4.5 | $0.00000 | $0.00017 |
Grade A, and why
ocr-and-documents 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 1mo ago.
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
OCR And Documents
Turn screenshots, scans, and messy files into structured working context.
Use when
- Important information is trapped in images, PDFs, or mixed-format docs.
- A docs or support workflow needs extracted text before analysis.
Workflow
- Identify the source type: screenshot, scanned PDF, exported doc, or mixed notes.
- Extract or retrieve text first before summarizing or making decisions.
- Preserve headings, tables, and named entities when they affect the outcome.
- Flag low-confidence or ambiguous OCR segments instead of inventing detail.
- Feed the cleaned result into the next workflow: docs update, support reply, launch brief, or review.
Deliverable
- Clean extracted summary.
- Important structured fields or action items.
- Any ambiguous text that still needs human confirmation.
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.
- 1mo ago First seen · 20 lines · 0 tokens per session scan A ace93cd33efa
ocr-and-documents is a skill published in the GitHub repository aaronnat23/disp8ch (100 stars, last pushed 1mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 166 tokens. 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 2026-08-30.
Other skills, from other repositories
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docx
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Comprehensive PDF manipulation toolkit for extracting text and tables, creating new PDFs, merging/splitting documents, and handling forms. When GLM needs to fill in a PDF form or programmatically process, generate, or analyze PDF documents at scale.
financial-expense-automation
An expense-receipt workflow that reads PDF and image attachments, extracts their details, checks whether they are valid expense receipts, and records them in Feishu Bitable, a cloud table service.
docx
Comprehensive document creation, editing, and analysis with support for tracked changes, comments, formatting preservation, and text extraction. When GLM needs to work with professional documents (.docx files) for: (1) Creating new documents, (2) Modifying or editing content, (3) Working with tracked changes, (4)…