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 kucherenko/petropowers --skill reservoir-productiongit 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/reservoir-production)<a href="https://agentmods.dev/skills/kucherenko/petropowers/reservoir-production"><img src="https://agentmods.dev/badge/skills/kucherenko/petropowers/reservoir-production/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/kucherenko/petropowers/reservoir-production"><img src="https://agentmods.dev/badge/skills/kucherenko/petropowers/reservoir-production.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 | $0.00014 | $0.01777 |
| Opus 5 | $0.00007 | $0.00889 |
| Sonnet 5 | $0.00003 | $0.00355 |
| Haiku 4.5 | $0.00001 | $0.00178 |
Grade A, and why
reservoir-production 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 — 234 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Reservoir & Production Pipeline
Guide AI agents through reservoir management and production optimization.
Purpose
Support reservoir and production engineers in managing hydrocarbon extraction and optimizing well performance.
Roles
- Reservoir Engineer - Reservoir modeling, forecasting, depletion strategy
- Production Engineer - Well performance, artificial lift, well intervention
- Well Intervention Engineer - Workovers, stimulation, completions
Data Types
| Data | Source | Frequency |
|---|---|---|
| Oil/gas/water rates | SCADA/Metering | Daily/Real-time |
| Pressure (BHP, THP) | Downhole gauges | Real-time |
| Temperature | Downhole gauges | Real-time |
| Reservoir models | Eclipse, CMG, tNavigator | Updated annually |
| Well tests | Separators/MPFM | Monthly |
Workflow
Phase 1: Reservoir Characterization
- Integrate seismic, logs, core data
- Build geological model
- Upscale to simulation model
- History match to production data
- Validate model
Phase 2: Production Forecasting
- Define development scenarios
- Run reservoir simulation
- Generate production forecast
- Estimate reserves (P10/P50/P90)
- Economic evaluation
Phase 3: Well Optimization
- Analyze well performance (inflow performance, vertical lift)
- Identify production bottlenecks
- Optimize artificial lift (gas lift, ESP, rod pump)
- Plan well interventions
- Monitor results
Phase 4: Reservoir Monitoring
- Track production vs. forecast
- Monitor pressure trends
- Analyze well interference
- Update model as needed
- Optimize depletion strategy
Domain Tasks
These tasks are handled by this skill:
- Decline curve analysis
- Inflow performance relationship (IPR)
- Nodal analysis
- Material balance
- Reserves estimation
Software Tasks
These tasks invoke petropowers:oil-gas-delegation:
- Production allocation system
- Reservoir monitoring dashboard
- Automated well testing workflow
- Production database
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 · 234 lines · 14 tokens per session scan A 659b91b5480d
reservoir-production is a skill published in the GitHub repository kucherenko/petropowers (11 stars, last pushed 5mo ago), licensed MIT. It adds 14 tokens to every session and 1,777 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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