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-performance-optimizergit 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-performance-optimizer)<a href="https://agentmods.dev/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-performance-optimizer"><img src="https://agentmods.dev/badge/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-performance-optimizer/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-performance-optimizer"><img src="https://agentmods.dev/badge/skills/mariodefelipe/sap-datasphere-plugin-for-claude-cowork/datasphere-performance-optimizer.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 | $0.00065 | $0.04389 |
| Opus 5 | $0.00032 | $0.02194 |
| Sonnet 5 | $0.00013 | $0.00878 |
| Haiku 4.5 | $0.00006 | $0.00439 |
Grade A, and why
Performance 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 10d 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 — 607 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Performance Optimizer Skill
Overview
The Performance Optimizer skill helps you identify and resolve performance issues in SAP Datasphere. Whether your views are running slowly, queries are timing out, or data flows are consuming excessive resources, this skill provides a systematic approach to diagnose and fix performance problems at every layer: views, queries, data flows, and storage.
When to Use This Skill
Trigger this skill when you encounter:
- Views or queries running slower than expected
- Query timeouts or cancellations
- High memory or CPU consumption
- Data flow execution taking excessive time
- Replication flows with poor delta performance
- Need to optimize storage usage
- Capacity warnings or resource contention alerts
- Performance regression after schema changes
- Need to benchmark performance improvements
Performance Analysis Approach
1. Identify the Bottleneck
Start by pinpointing where performance degradation occurs:
View Performance Issues:
- Access the View Analyzer tool in your view's details
- Check execution time trends over the last 7-30 days
- Compare execution times across different consumer queries
- Identify which views are called most frequently
- Note views with long initialization times
Query Performance Issues:
- Review query execution statistics in task logs
- Use Explain Plan to understand query execution strategy
- Check statement logs for query duration and resource usage
- Identify queries with full table scans or inefficient joins
- Monitor query frequency and timing patterns
Data Flow Performance Issues:
- Check data flow execution logs for step-level timing
- Monitor initial load duration vs. delta load duration
- Review parallelism settings and actual utilization
- Check for data quality issues causing processing overhead
- Analyze memory allocation and spill events
2. Measure Current Performance
Establish baseline metrics before optimization:
Key Metrics to Capture:
- Query execution time (wall-clock and CPU time)
- Memory usage (peak and average)
- Data volume processed (rows and bytes)
- I/O operations and throughput
- Number of disk accesses vs. in-memory operations
- Index usage patterns
- Cache hit rates
- Parallelism level achieved
- Storage tier distribution
What ships with it
2 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.
- 10d ago First seen · 607 lines · 65 tokens per session scan A cfdacc017fff
Performance Optimizer is a skill published in the GitHub repository MarioDeFelipe/sap-datasphere-plugin-for-claude-cowork (25 stars, last pushed 4mo ago), licensed MIT. It adds 65 tokens to every session and 4,389 once invoked, about $0.0003 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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