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/kucherenko/petropowers/refiningnpx skills add kucherenko/petropowers --skill refininggit clone --depth 1 https://github.com/kucherenko/petropowersWrote 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/kucherenko/petropowers/refining)<a href="https://agentmods.dev/skills/kucherenko/petropowers/refining"><img src="https://agentmods.dev/badge/skills/kucherenko/petropowers/refining.svg" alt="Measured on agentmods" 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 | $0.00013 | $0.02763 |
| Opus 5 | $0.00006 | $0.01381 |
| Sonnet 5 | $0.00003 | $0.00553 |
| Haiku 4.5 | $0.00001 | $0.00276 |
Grade A, and why
refining 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 5d 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 — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Refining Pipeline
Guide AI agents through refinery operations and process optimization.
Purpose
Support process and chemical engineers in refinery operations, optimization, and product quality control.
Roles
- Process Engineer - Unit operations, optimization, troubleshooting
- Chemical Engineer - Reaction engineering, catalysts, chemistry
- Plant Operator - Daily operations, monitoring, adjustments
- Lab Technician - Product quality testing, sampling
Data Types
| Data | Source | Frequency |
|---|---|---|
| Crude assay | Lab/Supplier | Batch |
| Temperature/pressure | DCS | Real-time (1-sec) |
| Flow rates | DCS | Real-time (1-sec) |
| Product qualities | Lab | 4-8 hours |
| Catalyst activity | Lab | Weekly |
| Energy consumption | Meters | Hourly |
Workflow
Phase 1: Crude Selection & Blending
- Receive crude assays (composition, properties)
- Optimize crude blend for:
- Target product slate
- Unit constraints
- Margin maximization
- Plan crude deliveries
- Monitor crude tank quality
Phase 2: Process Operations
- Monitor unit operations (DCS)
- Optimize cut points (distillation)
- Adjust operating conditions
- Monitor yields and quality
- Troubleshoot upsets
Phase 3: Product Quality
- Sample products (gasoline, diesel, jet, fuel oil)
- Test in lab (ASTM methods)
- Blend components to meet specs
- Certify products for release
- Track product inventory
Phase 4: Energy & Yield Optimization
- Monitor energy consumption
- Optimize heat integration
- Maximize yield of high-value products
- Minimize fuel gas, steam consumption
- Reduce CO2 emissions
Domain Tasks
These tasks are handled by this skill:
- Crude oil assay analysis
- Distillation optimization
- Product blending calculations
- Energy balance analysis
- Yield accounting
Software Tasks
These tasks invoke petropowers:oil-gas-delegation:
- Process monitoring dashboard
- Laboratory information system (LIMS)
- Blending optimization tool
- Production accounting system
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.
- 5d ago First seen · 354 lines · 13 tokens per session scan A 32fb9b449e20
refining is a skill published in the GitHub repository kucherenko/petropowers (11 stars, last pushed 5mo ago), licensed MIT. It adds 13 tokens to every session and 2,763 once invoked, about $0.0001 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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