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 squadcodercom/squadcoder --skill hebrew-ocr-formsgit clone --depth 1 https://github.com/squadcodercom/squadcoderWrote 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/squadcodercom/squadcoder/hebrew-ocr-forms)<a href="https://agentmods.dev/skills/squadcodercom/squadcoder/hebrew-ocr-forms"><img src="https://agentmods.dev/badge/skills/squadcodercom/squadcoder/hebrew-ocr-forms/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/squadcodercom/squadcoder/hebrew-ocr-forms"><img src="https://agentmods.dev/badge/skills/squadcodercom/squadcoder/hebrew-ocr-forms.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 | $0.00183 | $0.03117 |
| Opus 5.5 | $0.00073 | $0.01247 |
| Sonnet 5.5 | $0.00037 | $0.00623 |
| Haiku 4.5 | $0.00018 | $0.00312 |
Grade B, and why
hebrew-ocr-forms scanned grade B with 1 finding 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.
Asks for rootmediumPrivilege escalation
A mod that escalates privileges can change anything on the machine, not only the project.
Solution: Install with `sudo apt-get install tesseract-ocr-heb` (Ubuntu) or `brew install tesseract-lang` (macOS). Verify with `tesseract --list-langs`. How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Hebrew OCR Forms
Instructions
Step 1: Identify the Form Type
| Form Type | Source | Key Identifiers | Common Fields |
|---|---|---|---|
| Nesach Tabu | Land Registry | "נסח טאבו", "לשכת רישום המקרקעין" | Gush, Chelka, Owner, Liens |
| Tofes 106 | Tax Authority | "טופס 106", "דו״ח שנתי למעביד" | Salary, Tax, Employer |
| Ishur Nikui | Tax Authority | "אישור ניכוי מס במקור" | Tax rate, Validity, TZ |
| Tofes 857 | Tax Authority | "טופס 857", "רווח הון" | Transaction, Gain, Tax |
| Ishur Zkauyot | Bituach Leumi | "אישור זכאויות", "ביטוח לאומי" | Benefit type, Amount |
| Tofes 100 | Bituach Leumi | "טופס 100", "דין וחשבון" | Employees, Wages |
| Rishayon Rechev | Vehicle Licensing | "רישיון רכב" | Plate, Owner, Expiry |
Step 2: Preprocess the Scanned Image
See scripts/preprocess_image.py for the full preprocessing pipeline. Key steps:
- Convert to grayscale
- Deskew -- Israeli forms are often slightly rotated from scanning
- Binarize with adaptive threshold -- handles uneven lighting from scanners
- Remove noise with morphological operations
Step 3: Run Hebrew OCR with Tesseract
See scripts/extract_form_fields.py for the full extraction pipeline.
Tesseract configuration for Hebrew forms:
config = (
'--oem 1 ' # LSTM neural net (best for Hebrew)
'--psm 6 ' # Assume uniform block of text
'-l heb+eng ' # Hebrew + English (forms have both)
'-c preserve_interword_spaces=1' # Keep spacing for field alignment
)
- For tabular forms (Tabu, Tofes 106), use PSM 4 instead of PSM 6
- Always use LSTM mode (--oem 1) for best Hebrew accuracy
- Include both heb and eng languages since forms mix Hebrew and English/numbers
Step 4: Extract Fields by Form Type
Tabu Extract (Nesach Tabu) key fields:
- Gush (block) number: look for "גוש" followed by digits
- Chelka (parcel) number: look for "חלקה" followed by digits
- Owner name: follows "בעלים" or "שם הבעלים"
- ID number (TZ): follows "ת.ז." or "מספר זהות", 9 digits
What ships with it
6 files 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.
- 1mo ago First seen · 186 lines · 183 tokens per session scan B 72ae1825e18e
hebrew-ocr-forms is a skill published in the GitHub repository squadcodercom/squadcoder (12 stars, last pushed 3mo ago), licensed MIT. It adds 183 tokens to every session and 3,117 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it B with 1 finding (asks for root). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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