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 --skill neqsim-professional-reportinggit 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-professional-reporting)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-professional-reporting"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-professional-reporting/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-professional-reporting"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-professional-reporting.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00092 | $0.08944 |
| Opus 5.5 | $0.00037 | $0.03578 |
| Sonnet 5.5 | $0.00018 | $0.01789 |
| Haiku 4.5 | $0.00009 | $0.00894 |
Grade A, and why
neqsim-professional-reporting 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 today.
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 — 645 lines — stays where its author put it; the contents beside it link to each section on GitHub.
NeqSim Professional Reporting Skill
What separates "an answer" from a professional deliverable: traceability,
unit hygiene, citation discipline, structured results.json, and a report
narrative that matches the way senior engineers communicate.
When to Use
- Finalizing any task report under
task_solve/ - Building Jupyter notebook deliverables (study-grade, not exploratory)
- Producing FEED-quality memos, technical notes, or design basis documents
- Any output that will be read by a reviewer, client, or auditor
Principle 0 — Analytical depth (what makes a report worth reading)
Principles 1–10 are hygiene: they stop a report being wrong or unreadable. They do not make it useful. A hygienic report that restates the originating memo, lists contributors without ranking them, and ends in "further study is recommended" passes every checklist below and tells the reader nothing they did not already know.
The depth of a report is set in the study, not in the write-up. Plan for these moves while the analysis is still running — most of them cannot be added afterwards.
The nine depth moves
Aim for ≥ 6 of 9 on a Standard report and all 9 on a Comprehensive or
root-cause/problem-solving report. Record the score in results.json
(depth_score) and name the moves that were not achievable and why.
| # | Move | What it looks like | Anti-pattern it replaces |
|---|---|---|---|
| 1 | Rank the contributors on one common basis | A single table of every candidate cause with an improvement factor or utilisation number, computed the same way, so they are directly comparable | An unranked bullet list of "contributing factors" |
| 2 | Adjudicate the source document's own conclusions | A verdict table over each recommendation of the originating memo/PEPR/notification: Supported / Supported with a correction / Challenged, each with the number that decides it | Silently agreeing with the source, or silently ignoring it |
| 3 | Rule things out, quantitatively | "Thermal cycling does not explain this, by three orders of magnitude" — a competing explanation eliminated with a number and a stated margin | Leaving every hypothesis nominally alive |
| 4 | Find what the source document missed | A contributor, coupling, or second-order consequence absent from the originating document, established from evidence — and stated as such | Answering only the question as posed |
| 5 | Test the conclusion's robustness and say where it flips | A sensitivity table over the one or two genuinely uncertain modelling parameters, plus the explicit crossover point: "the top two swap around a slope of ~0.7, but the headline does not depend on it" | A single-point answer with an unquantified caveat |
| 6 | State the direction of every conservatism | Each screening value, default, and correlation labelled as an upper or lower bound on the reported quantity, so the reader knows which way the number can move | Undirected "this is approximate" |
| 7 | Name the cheapest discriminating test | The single measurement or inspection that would confirm or refute the diagnosis, why it discriminates, and what each outcome would mean | A generic "further investigation is recommended" |
| 8 | Report what does not fit | The observation that disagrees with the model, reported as a disagreement rather than smoothed over or omitted | Presenting only corroborating evidence |
| 9 | Convert qualitative asks into specifications | "Effective oxygen exclusion" → a purity table with the consequence of each grade; "improve filtration" → a micron rating with the mechanism that sets it | Repeating the source's qualitative wording back |
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.
- today Changed ebd74adc2c3a
- 8d ago Changed · +23 lines 509a8d01156b
- 9d ago Changed · +25 lines d9954562873b
- 10d ago Changed · +17 lines 82d8b1dae167
- 20d ago Changed · +14 lines · -54 tokens per session 3f707edb59e8
- 22d ago Changed 1aa013bf7060
- 23d ago Changed · +13 lines efa3de80a9d2
- 1mo ago Changed · +61 lines 7bdc46fadc8c
- 1mo ago Changed · +29 lines 6c7dbfae8548
- 1mo ago First seen · 463 lines · 146 tokens per session scan A 9003ebb6cfeb
neqsim-professional-reporting is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 92 tokens to every session and 8,944 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 2026-09-03.
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