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.svg" alt="Measured on agentmods" 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 | $0.00000 | $0.00083 |
| Sonnet 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 8d 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.
- 8d 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 (99 stars, last pushed 5d 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.
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