| name | arabic-nlp |
| description | Use this skill when selecting or applying Arabic NLP, tokenization, stemming, diacritization, morphological analysis, stopword, OCR, speech, or language-model tools including CAMeL Tools, Farasa, PyArabic, Tashaphyne, Qalsadi, and Arabic corpora. |
Arabic NLP
When To Use
Use this skill for arabic-nlp work in Arab/MENA contexts, especially when the prompt includes: Arabic NLP, tokenization, stemming, diacritization, morphology, Farasa, CAMeL, PyArabic.
When Not To Use
- Do not claim model accuracy without benchmark sources.
- Do not send private text to third-party APIs without approval.
Required Inputs
- Country or market.
- Target vendor, if already selected.
- Desired flow: identify, prefer, separate, return.
- Sandbox vs production state.
- Whether live customer, payment, tax, identity, bank, or payroll data is involved.
Default Workflow
- Read
sources.yml to see available vendors and confidence.
- If a vendor is named, read only
vendors/<vendor-id>.md for that vendor.
- If choosing vendors, compare only vendors in this skill's registry: arabic-stopwords, camel-tools, farasa, pyarabic, qalsadi, tashaphyne.
- Load
references/integration-checklist.md only for implementation, review, or launch-readiness work.
- Use
scripts/list-vendors.mjs for a deterministic vendor list when needed.
- Answer with source-backed facts, explicit unknowns, and validation steps.
Decision Tree
- Named vendor: read that vendor file, then answer narrowly.
- Vendor selection: filter by country, docs access, maturity, and source quality before recommending.
- Implementation: include auth, sandbox, webhook/callback, retries, idempotency, logging, and error handling only where source-backed.
- Missing docs: say
Needs vendor access or Unknown from public docs.
Files To Read
- Routing and process:
SKILL.md.
- Vendor facts:
vendors/*.md.
- Source map:
sources.yml.
- Implementation review:
references/integration-checklist.md.
- Example response style:
examples/source-backed-answer.md.
Safety Rules
- Check license and data handling before production use.
- Avoid sending sensitive Arabic text to external APIs by default.
- Benchmark on the target dialect and domain.
- Document tokenizer/stemmer limitations.
Validation Checklist
- Vendor facts map back to
source_urls.
- Unknowns are labeled instead of guessed.
- Sandbox and production are separated.
- Secrets are not printed or committed.
- High-risk live actions require explicit human approval.
- Evals in
evals/prompts.yml still cover the changed workflow.
Done Criteria
- The answer names the files read or source-backed references used.
- The implementation plan includes tests and rollback/verification steps.
- No unsupported regional, API, compliance, pricing, or endpoint claims are included.
