Arabic Nlp

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

1. Read sources.yml to see available vendors and confidence.
2. If a vendor is named, read only vendors/<vendor-id>.md for that vendor.
3. If choosing vendors, compare only vendors in this skill's registry: arabic-stopwords, camel-tools, farasa, pyarabic, qalsadi, tashaphyne.
4. Load references/integration-checklist.md only for implementation, review, or launch-readiness work.
5. Use scripts/list-vendors.mjs for a deterministic vendor list when needed.
6. 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.