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 equinor/neqsim-community-skills --skill neqsim-norwegian-continental-shelf-datagit clone --depth 1 https://github.com/equinor/neqsim-community-skillsWrote 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/equinor/neqsim-community-skills/neqsim-norwegian-continental-shelf-data)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-norwegian-continental-shelf-data"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-norwegian-continental-shelf-data/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/equinor/neqsim-community-skills/neqsim-norwegian-continental-shelf-data"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-norwegian-continental-shelf-data.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 | $0.00098 | $0.05029 |
| Opus 5.5 | $0.00039 | $0.02012 |
| Sonnet 5.5 | $0.00020 | $0.01006 |
| Haiku 4.5 | $0.00010 | $0.00503 |
Grade A, and why
neqsim-norwegian-continental-shelf-data 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 — 344 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Norwegian Continental Shelf Reference Data
Use this skill to load a bundled, source-attributed snapshot of public Norwegian Continental Shelf (NCS) facts and run screening-level analysis of production, resources, and the field inventory. The data is sourced from norskpetroleum.no (Norwegian Petroleum, run by the Norwegian Ministry of Energy and the Norwegian Offshore Directorate) and the Norwegian Offshore Directorate (Sodir, formerly NPD) FactPages, which publish open, reusable-with-attribution data about NCS activity.
The skill ships a curated public seed (headline national KPIs, a resource
accounting split, sea areas, and a qualitative inventory of major fields) plus a
tolerant ingestion path for the official Sodir yearly saleable-production CSV
exports, so a full production time series and per-field figures can be refreshed
without changing any code. All content is public; no proprietary or confidential
data is included. It is a data and screening-analysis skill, not a reservoir
simulator — quantitative production forecasting must use the validated NeqSim
SimpleReservoir / runReservoir workflows.
When to Use
- When a task needs quick, offline, source-attributed NCS facts (production, resources, exports, field counts) to frame an analysis.
- When building a production, resource-accounting, or field-inventory study of the Norwegian shelf and you want a normalized schema plus an ingestion path for the official Sodir/norskpetroleum.no tables.
- When an agent needs an upstream "NCS context" feed before a validated NeqSim reservoir-depletion, production-routing, or asset-economics screening.
- When a task needs the public Norwegian carbon-cost basis (CO2 Tax Act rates, EU ETS allowance cost, NOx Fund contribution) or a first-pass economic screening of an emission-abatement measure (power-from-shore, waste-heat recovery, compressor upgrade, flaring reduction) before a validated NeqSim energy/combustion model and a qualified commercial review.
- When a task needs a screening production forecast: fit an Arps decline (exponential/hyperbolic/harmonic) to a produced-rate series and project a forward rate profile, remaining volume, and EUR to an economic-limit rate, before a validated NeqSim reservoir forecast.
What ships with it
16 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.
- examples/basic_ncs_data.py 2.7 KB runs code
- pyproject.toml 723 B
- README.md 1.7 KB
- src/norwegian_continental_shelf_data/__init__.py 2.1 KB runs code
- src/norwegian_continental_shelf_data/analysis.py 7.4 KB runs code
- src/norwegian_continental_shelf_data/carbon.py 16 KB runs code
- src/norwegian_continental_shelf_data/data/__init__.py 47 B runs code
- src/norwegian_continental_shelf_data/data/ncs_reference.json 9.4 KB
- src/norwegian_continental_shelf_data/dataset.py 20 KB runs code
- src/norwegian_continental_shelf_data/decline.py 9.6 KB runs code
- src/norwegian_continental_shelf_data/sources.py 4.2 KB runs code
- tests/test_analysis.py 2.7 KB runs code
- tests/test_carbon.py 4.6 KB runs code
- tests/test_dataset.py 4.3 KB runs code
- tests/test_decline.py 3.5 KB runs code
- tests/test_reserves_and_sources.py 3.5 KB runs code
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 Changed · +6 lines c7332a205175
- 11d ago Changed · +3 lines c9963934b018
- 19d ago Changed · -187 lines 997316a3e06b
- 27d ago Changed · +214 lines de81e726faa5
- 1mo ago Changed · +4 lines · -17 tokens per session 7bc16ca816e4
- 1mo ago First seen · 304 lines · 115 tokens per session scan A f7defce7129e
neqsim-norwegian-continental-shelf-data is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed 4d ago), licensed Apache-2.0. It adds 98 tokens to every session and 5,029 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-19.
neqsim-norwegian-continental-shelf-data compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neqsim-norwegian-continental-shelf-dataequinor/neqsim-community-skills | Skill | 4 | 4d ago | Apache-2.0 | A | 98 | Claude Code, Codex |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |