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 paperlab-multireviewer-simulationgit 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/paperlab-multireviewer-simulation)<a href="https://agentmods.dev/skills/equinor/neqsim/paperlab-multireviewer-simulation"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab-multireviewer-simulation/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/paperlab-multireviewer-simulation"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab-multireviewer-simulation.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 | $0.00040 | $0.00276 |
| Opus 5.5 | $0.00016 | $0.00110 |
| Sonnet 5.5 | $0.00008 | $0.00055 |
| Haiku 4.5 | $0.00004 | $0.00028 |
Grade A, and why
paperlab-multireviewer-simulation 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 27d 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.
This is a copy
92% identical to paperlab_multireviewer_simulation — 3 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
PaperLab Multi-Reviewer Simulation
When to Use
USE WHEN: preparing a manuscript, revision, or book release for serious external review.
Reviewer Roles
- handling editor,
- thermodynamics or process-simulation expert,
- numerical methods reviewer,
- reproducibility reviewer,
- application/domain reviewer,
- figure and table reviewer.
Rubric
Score 1 to 5 for:
- novelty,
- evidence strength,
- method clarity,
- statistical validity,
- reproducibility,
- limitations disclosure,
- figure narrative,
- journal or publisher fit.
Output Pattern
## Reviewer 2: Numerical Methods
Major comments:
- ...
Minor comments:
- ...
Decision tendency: major revision
Pass Criteria
- All blocker comments map to fixable evidence or prose actions.
- Editorial risk is explicit.
- The recommended decision is justified by the manuscript, not by taste alone.
Safety Rules
- Do not fabricate external peer-review outcomes.
- Keep review comments anchored to manuscript sections and artifacts.
- Separate required fixes from optional polish.
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.
- 27d ago First seen · 62 lines · 40 tokens per session scan A dcc1d70179a7
paperlab-multireviewer-simulation is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 40 tokens to every session and 276 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 92% identical to paperlab_multireviewer_simulation, differing in 3 lines, and is treated as a copy.
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