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_exercise_difficulty_rampgit 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_exercise_difficulty_ramp)<a href="https://agentmods.dev/skills/equinor/neqsim/paperlab_exercise_difficulty_ramp"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_exercise_difficulty_ramp/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_exercise_difficulty_ramp"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/paperlab_exercise_difficulty_ramp.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00036 | $0.00464 |
| Opus 5.5 | $0.00014 | $0.00186 |
| Sonnet 5.5 | $0.00007 | $0.00093 |
| Haiku 4.5 | $0.00004 | $0.00046 |
Grade A, and why
paperlab_exercise_difficulty_ramp 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 1mo 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- paperlab-exercise-difficulty-ramp — 100% identical, 8 lines differ
What it actually says
PaperLab Exercise Difficulty Ramp
When to Use
USE WHEN: preparing a book for teaching, revising exercises, or checking that learning objectives are assessed with an appropriate difficulty progression.
Pair with:
paperlab_learning_objective_matrixfor objective coverage,paperlab_exam_alignmentfor assessment fit,paperlab_student_readabilityfor student-facing wording.
Exercise Types
| Type | Student Action |
|---|---|
| concept-check | explain, define, compare |
| calculation | compute a value with stated inputs |
| interpretation | explain what a result means physically |
| sensitivity | vary one or more inputs and compare outputs |
| design-decision | choose between alternatives using constraints |
| uncertainty-risk | use P10/P50/P90, risk matrix, or scenario range |
| capstone | integrate multiple chapters or recurring cases |
Difficulty Levels
L1: recall or identify.L2: explain or classify.L3: calculate with provided method.L4: diagnose, compare, or justify.L5: design, optimize, or evaluate uncertainty.
Pass Criteria
- Each chapter has at least one concept-check exercise.
- Quantitative chapters have at least one calculation or notebook-linked task.
- Design chapters include at least one decision exercise.
- Late-book chapters include integration or capstone tasks.
- Objectives with verbs such as calculate, design, evaluate, or diagnose are assessed by matching exercise types.
Output Schema
{
"chapter": "ch23_co2_field_development",
"exercise_mix": {"concept-check": 2, "calculation": 1, "design-decision": 2},
"missing_types": ["uncertainty-risk"],
"recommended_exercise": "Estimate dense-phase transport margin under low-temperature uncertainty."
}
Safety Rules
- Do not require private data for public exercises.
- Keep solutions and grading rubrics separate from student-facing chapters.
- Match difficulty to prerequisite coverage.
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.
- 1mo ago First seen · 65 lines · 36 tokens per session scan A bb64e7968f37
paperlab_exercise_difficulty_ramp is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 36 tokens to every session and 464 once invoked, about $0.0001 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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