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-task-grillgit 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-task-grill)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/neqsim-task-grill"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-task-grill/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-task-grill"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/neqsim-task-grill.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 | $0.01146 |
| Opus 5.5 | $0.00042 | $0.00458 |
| Sonnet 5.5 | $0.00021 | $0.00229 |
| Haiku 4.5 | $0.00011 | $0.00115 |
Grade A, and why
neqsim-task-grill 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 4d 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 — 98 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NeqSim Task Grill ("grill me")
It settles the basis so the agents can deliver the best possible result without guessing. It asks and records; the calculations stay with the specialist agents.
When to Use
Run this before a study, report or workflow, when the request is a sentence and the result must be a report people will rely on.
Inputs
The user's request in their own words, plus whatever the user can name: data, earlier reports, standards, tools and people involved.
Engineering Method
- Ask one question at a time. Give a recommended answer and say why the question matters. Wait for the answer.
- If the user does not know, record
OPEN. Never fill in a plausible value. A value without a source is an assumption and is labelled so. - Check each answer against the earlier ones. If two conflict (for example "formal issue" with mock data), say so and ask again.
- Challenge at the end: which three assumptions would change the result if wrong, and how would each be tested?
- Test access instead of asking about it: try each named tool or data source and record the real outcome. Use a hand-off only after a real failure.
- Stop when every question is answered or OPEN, and write the outputs.
Questions
| Area | Ask |
|---|---|
| The decision | What must be decided or answered, by whom, by when? What is the output used for? |
| Quality bar | Screening draft or formal issue? Which earlier report sets the standard? Language, units, templates, who signs? |
| Basis | What data exists (measurements, models, earlier studies, standards)? Where, in what form, how current? |
| Method | Which calculation basis is acceptable (screening, validated, standard-based)? Any required standards? |
| Reports | Which reports are needed (PVT, process, wells, SURF, flow assurance, cost, safety)? Who signs each? |
| Access | Which sources and tools are reachable now? |
| Constraints | Cost, schedule, regulation, host capacity, partner positions. |
| Assumptions | The three that matter most; any with no source. |
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.
- 4d ago First seen · 98 lines · 106 tokens per session scan A aa77a40f2516
neqsim-task-grill is a skill published in the GitHub repository equinor/neqsim-community-skills (4 stars, last pushed today), licensed Apache-2.0. It adds 106 tokens to every session and 1,146 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 2026-11-03.
neqsim-task-grill compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| neqsim-task-grillequinor/neqsim-community-skills | Skill | 4 | today | Apache-2.0 | A | 106 | 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 |