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 arc-mcp/arc-1 --skill generate-analytics-star-schemagit clone --depth 1 https://github.com/arc-mcp/arc-1Wrote 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/arc-mcp/arc-1/generate-analytics-star-schema)<a href="https://agentmods.dev/skills/arc-mcp/arc-1/generate-analytics-star-schema"><img src="https://agentmods.dev/badge/skills/arc-mcp/arc-1/generate-analytics-star-schema/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/arc-mcp/arc-1/generate-analytics-star-schema"><img src="https://agentmods.dev/badge/skills/arc-mcp/arc-1/generate-analytics-star-schema.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 | $0.00076 | $0.02770 |
| Opus 5 | $0.00038 | $0.01385 |
| Sonnet 5 | $0.00015 | $0.00554 |
| Haiku 4.5 | $0.00008 | $0.00277 |
Grade A, and why
generate-analytics-star-schema 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 — 239 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Generate CDS Analytics Star Schema
Generate a CDS analytical model — a star schema consisting of a cube view (@Analytics.dataCategory: #CUBE), one or more dimension views (#DIMENSION), and text views (#TEXT) — on top of a RAP business object or a plain DDIC table.
This skill replicates SAP Joule's "CDS Analytical Model Generation" capability (basic + extended scope) by combining ARC-1 (SAP system access) with mcp-sap-docs (documentation & best practices). Basic scope = cube + reuse existing dimensions. Extended scope = also generate new dimensions, and start from a DDIC table (not just a RAP BO).
Prerequisites — read this first
- Requires SAP_BASIS 7.5x with the analytics annotations. Verify with
SAPManage(action="probe")(rap.available). If RAP/CDS isn't available, stop. - The output is a set of interdependent CDS views (cube → dimensions → texts). They must be created as inactive drafts and activated together so SAP's activator resolves the cross-references in one pass. This skill uses
SAPWrite(action="batch_create", activateAtEnd: true)for exactly that.
Smart Defaults (apply silently, do NOT ask)
| Setting | Default | Rationale |
|---|---|---|
| Object type | DDLS |
Cube/dimension/text are all CDS data definitions |
| Package | $TMP |
Fast prototyping; ask before a transportable package |
| Activation | batch_create + activateAtEnd: true |
Cross-references resolve in one terminal pass |
| Authorization | #NOT_REQUIRED (cube/dimension) |
Standard for analytical interface views |
| Naming | ZI_<X>_Cube, ZI_<X>_Dim, ZI_<X>_Txt |
Clear star-schema roles (match the casing the templates use) |
Input
The user provides either:
- A RAP business object root entity / behavior pool (e.g.
ZBP_R_TRAVELorZI_Travel), or - A DDIC table (e.g.
ZTRAVEL), or - An interface CDS view to use as the fact source.
Optionally: which numeric fields are measures, which fields are dimensions, target package, and whether to generate new dimension views or reuse existing ones.
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 · 239 lines · 76 tokens per session scan A b53c0144b578
generate-analytics-star-schema is a skill published in the GitHub repository arc-mcp/arc-1 (183 stars, last pushed today), licensed MIT. It adds 76 tokens to every session and 2,770 once invoked, about $0.0004 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.
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