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 agentmods add skills/squadcodercom/squadcoder/israeli-arnona-optimizernpx skills add squadcodercom/squadcoder --skill israeli-arnona-optimizergit clone --depth 1 https://github.com/squadcodercom/squadcoderWhat 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 | $0.00195 | $0.03741 |
| Opus 5 | $0.00097 | $0.01870 |
| Sonnet 5 | $0.00039 | $0.00748 |
| Haiku 4.5 | $0.00019 | $0.00374 |
Grade A, and why
israeli-arnona-optimizer 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 2d 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.
How it starts
The opening of the file, as written. The whole thing — 199 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Israeli Arnona Optimizer
Instructions
Step 1: Gather Property Details
Before performing any arnona calculation, collect the following information from the user:
- Municipality (iriya): Which city or local council the property is located in (e.g., Tel Aviv-Yafo, Jerusalem, Haifa, Beer Sheva, Netanya, Rishon LeZion).
- Property area: Total area in square meters (sqm). Distinguish between main area and auxiliary areas (storage rooms, balconies, parking) as these are billed at different rates.
- Zone classification: The arnona zone within the municipality. Each city divides into zones (azor) with different rate tiers. Ask the user for their zone or help them determine it from their address.
- Usage type: Residential (megurim), commercial (mishari), office (misrad), industrial (taasia), or other special uses. Rates differ significantly by usage.
- Billing period: Arnona is billed bimonthly (every two months) in most municipalities. The annual rate is divided into 6 payment periods.
Step 2: Calculate Base Arnona
Use the arnona calculator script to compute the base annual arnona:
python scripts/arnona-calculator.py --municipality "tel-aviv" --area 80 --zone 2 --usage residential
The calculator applies the correct rate per sqm based on the municipality's published rate tables. Key rate structures:
- Tel Aviv-Yafo: Rates range from approximately 75 to 130 NIS/sqm/year for residential depending on zone (zones 1-4). Commercial rates are 2-4x higher.
- Jerusalem: Rates range from approximately 55 to 95 NIS/sqm/year for residential. Divided into 5 zones using Hebrew letters alef through heh (א through ה).
- Haifa: Rates range from approximately 50 to 90 NIS/sqm/year for residential. Lower overall compared to Tel Aviv.
- Beer Sheva: Rates range from approximately 35 to 60 NIS/sqm/year for residential. Among the lowest for major cities.
Consult references/arnona-rates-guide.md for detailed rate tables and zone classification rules.
What ships with it
8 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.
- 2d ago First seen · 199 lines · 195 tokens per session scan A cc2bfffab780
israeli-arnona-optimizer is a skill published in the GitHub repository squadcodercom/squadcoder (11 stars, last pushed 2mo ago), licensed MIT. It adds 195 tokens to every session and 3,741 once invoked, about $0.0010 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 2026-08-30.
Other skills, from other repositories
kyc-doc-parse
Parse an investor or client onboarding packet into structured KYC fields — identity, ownership, control, source of funds, and document inventory. Use as the first step of KYC screening; output feeds the rules engine.
kanchi-dividend-us-tax-accounting
Provide US dividend tax and account-location workflow for Kanchi-style income portfolios. Use when users ask about qualified vs ordinary dividends, 1099-DIV interpretation, REIT/BDC distribution treatment, holding-period checks, or taxable-vs-IRA account placement decisions for dividend assets.
fiscaliste
Fiscaliste IA pour la fiscalité personnelle des particuliers français : optimisation et déclaration de l'impôt sur le revenu, IFI, revenus du capital, revenus fonciers, equity salarial, crypto-actifs et PER. Couvre le calcul de l'IR (barème, quotient familial, décote, PAS, CEHR, revenus exceptionnels), la déclaration…
agb-in-kapitalanlagen-effektenhandel
Für AGB in Kapitalanlagen Effektenhandel: ordnet Norm, Beweislast und Gegenargument; Ergebnis: Prüfprodukt mit Risiko und nächstem Schritt.
dora
Expert DORA (Regulation (EU) 2022/2554 — Digital Operational Resilience Act) compliance advisor for EU financial entities. Use this skill whenever a user asks about DORA compliance, ICT risk management frameworks, ICT incident classification or reporting, threat-led penetration testing (TLPT), ICT third-party risk…
regulatory-analysis
Analyzes documents and processes against FINRA, SEC, Federal Reserve, and CFPB regulatory frameworks. Identifies compliance gaps, classifies findings by severity, and recommends remediation. Use when performing compliance audits, regulatory reviews, gap analyses, or verifying policy adherence to financial regulations.