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 MarioDeFelipe/sap-datasphere-plugin-for-claude-cowork --skill datasphere-catalog-stewardgit clone --depth 1 https://github.com/MarioDeFelipe/sap-datasphere-plugin-for-claude-coworkWrote 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/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-catalog-steward)<a href="https://agentmods.dev/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-catalog-steward"><img src="https://agentmods.dev/badge/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-catalog-steward/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/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-catalog-steward"><img src="https://agentmods.dev/badge/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-catalog-steward.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00101 | $0.12128 |
| Opus 5 | $0.00051 | $0.06064 |
| Sonnet 5 | $0.00020 | $0.02426 |
| Haiku 4.5 | $0.00010 | $0.01213 |
Grade A, and why
Catalog Steward 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 12d 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 — 1,351 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Catalog Steward Skill
Overview
The Catalog Steward skill empowers you to take control of your SAP Datasphere's internal data governance. This skill focuses on enriching metadata, managing business glossaries, defining KPIs, controlling tag taxonomies, and performing lineage-based impact analysis—all essential for enabling self-service analytics and preventing governance chaos.
Unlike the Data Product Publisher skill (which publishes external marketplace products), the Catalog Steward skill is about making your internal Datasphere repository discoverable, understandable, and trustworthy. When users search your catalog, they should find well-named assets with clear descriptions, consistent business terminology, quality metrics, and transparent lineage.
Why Catalog Governance Matters
- Self-Service Analytics: Business users can find and trust data without submitting tickets
- Compliance & Auditability: Clear lineage and ownership trails support regulatory requirements
- Impact Analysis: Understand change ripple effects before modifying critical assets
- Terminology Alignment: Glossaries ensure "Revenue" means the same thing across teams
- Data Quality Transparency: Quality scores help users select the right datasets
- Governance at Scale: Consistent metadata reduces technical debt and tribal knowledge
Core Workflows
1. Metadata Enrichment
Metadata enrichment transforms technical asset names and sparse descriptions into discoverable, business-friendly documentation.
Workflow: Analyze and Suggest Business-Friendly Names
When to use: During onboarding, after importing source system tables, or during catalog cleanup sprints.
Steps:
-
Search for undernamed assets:
- Use
search_catalogto find tables/views with missing or cryptic names (e.g., "T_SALES_001") - Filter by asset type (Dimension, Fact, View, Model)
- Identify candidates for enrichment
- Use
-
Analyze content with column inspection:
- Use
get_asset_detailsto inspect table/view structure - Review key columns to infer business meaning
- Identify primary dimensions and measures
- Example: "T_SALES_001" contains
CUST_ID,ORDER_DT,AMOUNT→ suggests "Customer Orders Fact"
- Use
What ships with it
1 file 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.
- 12d ago First seen · 1,351 lines · 101 tokens per session scan A 110d567d7c10
Catalog Steward is a skill published in the GitHub repository MarioDeFelipe/sap-datasphere-plugin-for-claude-cowork (26 stars, last pushed 4mo ago), licensed MIT. It adds 101 tokens to every session and 12,128 once invoked, about $0.0005 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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