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 khalilbenaz/claude-skills-collection --skill sql-advanced-analyticsgit clone --depth 1 https://github.com/khalilbenaz/claude-skills-collectionWrote 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/khalilbenaz/claude-skills-collection/sql-advanced-analytics)<a href="https://agentmods.dev/skills/khalilbenaz/claude-skills-collection/sql-advanced-analytics"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/sql-advanced-analytics/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/khalilbenaz/claude-skills-collection/sql-advanced-analytics"><img src="https://agentmods.dev/badge/skills/khalilbenaz/claude-skills-collection/sql-advanced-analytics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00126 | $0.02295 |
| Opus 5 | $0.00063 | $0.01148 |
| Sonnet 5 | $0.00025 | $0.00459 |
| Haiku 4.5 | $0.00013 | $0.00230 |
Grade A, and why
sql-advanced-analytics 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 9d 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 — 240 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SQL Avancé pour l'Analytique
Workflow
- Identifier le besoin : classement, comparaison temporelle, agrégation cumulative, hiérarchie, pivot.
- Choisir la construction :
- Classement/comparaison dans une partition → window function
- Hiérarchie ou récursion → CTE récursive
- Rotation lignes/colonnes → PIVOT / CASE WHEN
- Calcul réutilisé plusieurs fois → CTE non-récursive ou vue matérialisée
- Écrire la requête : CTEs avant la requête principale, window functions dans le SELECT.
- Valider le plan d'exécution :
EXPLAIN ANALYZE(PG) /SET STATISTICS IO ON(SQL Server). - Optimiser : index couvrants, matérialisation, partitionnement.
Window Functions
Critères de choix
| Besoin | Fonction |
|---|---|
| Rang sans ex-aequo | ROW_NUMBER() |
| Rang avec ex-aequo, sauts | RANK() |
| Rang avec ex-aequo, continu | DENSE_RANK() |
| Découper en N groupes égaux | NTILE(N) |
| Valeur N lignes avant/après | LAG(col, N) / LEAD(col, N) |
| Cumul depuis le début | SUM() OVER (ORDER BY ... ROWS UNBOUNDED PRECEDING) |
| Moyenne mobile | AVG() OVER (ROWS BETWEEN N PRECEDING AND CURRENT ROW) |
| Premier/dernier de la partition | FIRST_VALUE() / LAST_VALUE() + frame explicite |
Classement dans une partition
SELECT
product_name,
category,
total_sales,
ROW_NUMBER() OVER (PARTITION BY category ORDER BY total_sales DESC) AS rn,
RANK() OVER (PARTITION BY category ORDER BY total_sales DESC) AS rnk,
DENSE_RANK() OVER (PARTITION BY category ORDER BY total_sales DESC) AS dense_rnk,
NTILE(4) OVER (PARTITION BY category ORDER BY total_sales DESC) AS quartile
FROM products;
Comparaison temporelle et cumul
SELECT
month,
revenue,
LAG(revenue, 1) OVER (ORDER BY month) AS prev_month,
revenue - LAG(revenue, 1) OVER (ORDER BY month) AS mom_delta,
LEAD(revenue, 1) OVER (ORDER BY month) AS next_month,
AVG(revenue) OVER (ORDER BY month ROWS BETWEEN 2 PRECEDING AND CURRENT ROW) AS ma_3m,
SUM(revenue) OVER (ORDER BY month ROWS UNBOUNDED PRECEDING) AS cumul
FROM monthly_sales;
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.
- 9d ago First seen · 240 lines · 126 tokens per session scan A 4d6170501688
sql-advanced-analytics is a skill published in the GitHub repository khalilbenaz/claude-skills-collection (22 stars, last pushed 19d ago), licensed MIT. It adds 126 tokens to every session and 2,295 once invoked, about $0.0006 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 2026-09-03.
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