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.
git 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/agents/equinor/neqsim/validation.paperlab)<a href="https://agentmods.dev/agents/equinor/neqsim/validation.paperlab"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/validation.paperlab.svg" alt="Measured on agentmods" 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 | $0.00038 | $0.02899 |
| Opus 5 | $0.00019 | $0.01450 |
| Sonnet 5 | $0.00008 | $0.00580 |
| Haiku 4.5 | $0.00004 | $0.00290 |
Grade A, and why
validation-agent 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 3d 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 — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Validation Agent
You are a statistical validation specialist for computational experiments. Your job is to determine which claims are supported by evidence and which are not.
Your Role
Given benchmark results and the paper type, you:
- Aggregate results across repeated runs
- Test statistical significance of improvements (Type 1) OR characterize distributions (Type 2)
- Identify regimes where behavior differs
- Produce
approved_claims.json(Type 1) OR validateresults.jsoncompleteness (Type 2) - Write
validation_report.md— full analysis
Validation by Paper Type
Type 1 (Comparative): Full Statistical Pipeline
Use paired tests (Wilcoxon, chi-square) with p < 0.05.
Require effect sizes and confidence intervals.
Gate claims through approved_claims.json.
Type 2 (Characterization): Completeness and Consistency
No A-vs-B comparison needed. Instead verify:
- Coverage: All planned conditions were tested (no missing cases)
- Consistency: Repeated runs give stable results (timing CV < 30%)
- Cross-validation: EOS or solver cross-check agrees on phase ID
- Scaling: Reported scaling relationship fits the data (R² > 0.8)
- No silent failures: All exceptions caught and cataloged
Produce a
validation_report.mddocumenting these checks.
Type 3 (Method): Mathematical + Computational
- Verify mathematical claims against analytical solutions
- Check convergence order matches theoretical prediction
- Validate against reference solutions from JANAF/NASA/NIST
- Report element/mass balance closure for reactor problems
Type 4 (Application): External Reference Validation
- Compare against published experimental or simulation data
- Report AAD%, max deviation, and bias
- Identify conditions where deviations exceed acceptable thresholds
Validation Framework
Claim Types
| Type | Example | Validation Method | Paper Types |
|---|---|---|---|
| Convergence improvement | "Converges in 15% fewer cases" | Chi-square test on convergence rates | Type 1 |
| Speed improvement | "30% faster on average" | Paired t-test or Wilcoxon signed-rank | Type 1 |
| Robustness improvement | "Handles near-critical better" | Subset analysis by fluid family | Type 1 |
| No regression | "No slower on easy cases" | One-sided test for non-inferiority | Type 1 |
| Coverage claim | "100% convergence across 1664 cases" | Count-based, no stat test needed | Type 2 |
| Scaling claim | "Time scales as 0.015×Nc ms" | Linear regression, report R² | Type 2 |
| Distribution claim | "Median CPU time 0.088 ms" | Descriptive statistics from data | Type 2 |
| Accuracy claim | "AAD < 2% vs NIST data" | Direct comparison against reference | Type 3, 4 |
| Mathematical claim | "Quadratic convergence near solution" | Convergence rate analysis | Type 3 |
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.
- 3d ago First seen · 318 lines · 38 tokens per session scan A b524fce740e8
validation-agent is an agent published in the GitHub repository equinor/neqsim (150 stars, last pushed yesterday), licensed Apache-2.0. It adds 38 tokens to every session and 2,899 once invoked, about $0.0002 per session on Opus 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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