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.
git clone --depth 1 https://github.com/jamon8888/hacienda-privateWrote 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/agents/jamon8888/hacienda-private/ocr-engineer)<a href="https://agentmods.dev/agents/jamon8888/hacienda-private/ocr-engineer"><img src="https://agentmods.dev/badge/agents/jamon8888/hacienda-private/ocr-engineer.svg" alt="Measured on agentmods" 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 | $0.00014 | $0.00267 |
| Opus 5 | $0.00007 | $0.00133 |
| Sonnet 5 | $0.00003 | $0.00053 |
| Haiku 4.5 | $0.00001 | $0.00027 |
Grade A, and why
ocr-engineer 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 7d 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
When working on OCR code:
- Key source paths: crates/xberg/src/ocr/ (processor.rs, tesseract_backend.rs, hocr.rs, cache.rs, language_registry.rs, table/)
- The OCR pipeline: Image Detection -> Preprocessing (denoise, deskew, binarize) -> Backend Selection -> OCR Execution -> hOCR Parsing -> Table Reconstruction -> Caching -> Return
- Backends: Tesseract (default, native C FFI via leptess), PaddleOCR (ONNX via ort), Candle OCR, VLM OCR, and custom plugin backends
- For plugin or external-process backends: use tokio::task::spawn_blocking for blocking work, minimize FFI/runtime lock hold time, cache backend data in Rust fields
- For table detection: detect via line/cell boundary detection, validate grid structure, OCR each cell, output as markdown
- For language management: validate against LanguageRegistry, check tessdata availability
- Cache OCR results with key = hash(image_bytes + language + config)
- hOCR parsing: use the hocr module to extract word-level bounding boxes and confidence scores
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.
- 7d ago First seen · 17 lines · 14 tokens per session scan A 0b7182081dad
ocr-engineer is an agent published in the GitHub repository jamon8888/hacienda-private (0 stars, last pushed 1mo ago), licensed MIT. It adds 14 tokens to every session and 267 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 2026-08-31.
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