Borrowing it
Nothing to install: this file belongs to equinor/neqsim. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/equinor/neqsim/master/.github/skills/neqsim-exploration-strategy-selection/SKILL.mdgit clone --depth 1 https://github.com/equinor/neqsimWrote 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/neqsim-exploration-strategy-selection)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-exploration-strategy-selection"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-exploration-strategy-selection/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/neqsim-exploration-strategy-selection"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-exploration-strategy-selection.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 | $0.00106 | $0.03100 |
| Opus 5.5 | $0.00042 | $0.01240 |
| Sonnet 5.5 | $0.00021 | $0.00620 |
| Haiku 4.5 | $0.00011 | $0.00310 |
Grade A, and why
neqsim-exploration-strategy-selection 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 7d 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 — 80 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Exploration strategy selection (dedicated well vs PLX)
Second implementation with two zones, host-life gate and flow assurance: the Tyrihans cellar task (tyr_model.py, 07_strategies.py, 13_crossovers.py, 14_build_results.py).
Third implementation, infrastructure-reuse variant with IOGR, tie-back routes and exploration in one Monte Carlo: the Morvin revitalization task (mmodel.py, 20_options.py, 21_sens.py).
Reference implementation: task_solve/2026-10-10_limbus_apbo_exploration_strategy_dedicated_well_vs_plx_from/step2_analysis/scripts (limbus_model.py development economics and volumes, 07_strategies.py strategies, 08_sensitivity.py tornado and maps, 13_crossovers.py). Copy the pattern, not the numbers: every prospect input there is an assumption.
1. Strategies to compare
| Id | Strategy | What differs |
|---|---|---|
| S1 | Dedicated exploration well | Full rig spread and well cost in every outcome, earlier data, long lag from discovery to first oil (appraisal, concept, sanction) |
| S2 | PLX from the planned producer | Cost is a sidetrack or lateral (days, not months) and shared with the producer, data later (tied to the producer schedule), shorter lag because the PLX can be completed as a producer, but a harm term when the planned producer is delayed or lost |
| S2h | S2 with S1 as fall-back | Add a reach probability (trajectory, step-out, torque and drag, ECD); if the PLX cannot reach, the dedicated well is drilled |
| S3 | PLX in a second, later producer | Later data, equal cost, optional gain in chance of success from the earlier wells |
S2h only works when the dedicated well it falls back to has a positive EMV. At Tyrihans (EMV of the dedicated well -13 MUSD) the fall-back made S2h worse than S2; report S2 as "pilot only if reachable, else do nothing" and S2h as the reference, and do not recommend a pre-agreed fall-back until EMV(S1) > 0.
Do nothing is a fifth option with value zero; it is only dominated if the EMV of the best strategy is positive at the honest chance of success.
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.
- 7d ago First seen · 80 lines · 106 tokens per session scan A acdab8978539
neqsim-exploration-strategy-selection is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 106 tokens to every session and 3,100 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 2026-10-11.
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