Candidate Talent Pool
sickn33/agentic-awesome-skills
Candidate and prospect pool: contact details, experience, skills, consent status and date, referral source and last contact.
Quantitative consequence analysis - jet/pool fire, VCE, BLEVE, Gaussian and heavy-gas dispersion, probit fatality, individual and societal risk.
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install equinor/neqsim neqsim-consequence-analysis --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .claude/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .claude/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysisType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install equinor/neqsim neqsim-consequence-analysis --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .agents/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .agents/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install equinor/neqsim neqsim-consequence-analysis --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .cursor/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .cursor/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/equinor/neqsim.git --path .github/skills/neqsim-consequence-analysis--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install equinor/neqsim neqsim-consequence-analysis --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .gemini/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .gemini/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install equinor/neqsim neqsim-consequence-analysisInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .github/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .github/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .github/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install equinor/neqsim neqsim-consequence-analysis --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/equinor/neqsim.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.github/skills/neqsim-consequence-analysis .opencode/skills/neqsim-consequence-analysis && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "neqsim-consequence-analysis" agent skill from https://github.com/equinor/neqsim/tree/master/.github/skills/neqsim-consequence-analysis into .opencode/skills/neqsim-consequence-analysis/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "neqsim-consequence-analysis", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
neqsim-consequence-analysisQuantitative consequence analysis - jet/pool fire, VCE, BLEVE, Gaussian and heavy-gas dispersion, probit fatality, individual and societal risk.
Neqsim Consequence Analysis is an agent skill from equinor/neqsim. Quantitative consequence analysis - jet/pool fire, VCE, BLEVE, Gaussian and heavy-gas dispersion, probit fatality, individual and societal risk. USE WHEN: a task requires fire-radiation contours, dispersion to LFL/IDLH/ERPG, BLEVE thermal/missile assessment, or QRA-style integration of release outcomes. Anchors on neqsim.process.safety.fire, .dispersion and .qra.
Its SKILL.md is about 2.8k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
The repository describes itself as: NeqSim is a library for calculation of fluid behavior, phase equilibrium and process simulation. The licence is Apache-2.0.
Read from SKILL.md and the folder at commit 92261e0. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are java and bash).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Neqsim Consequence Analysis loads about 2.8k tokens when it runs. Until then it costs about 98 tokens; SKILL.md has 663 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from equinor/neqsim at commit 92261e0, republished under its Apache-2.0 licence (© equinor). 663 words, ~2,816 tokens.
.claude/skills/neqsim-consequence-analysis/SKILL.md (or your agent's skills folder).Quantitative consequence modelling that converts a release scenario (mass flow, inventory, ignition probability) into thermal radiation contours, overpressure contours, dispersion footprints, and finally individual / societal fatality risk per ISO 17776, NORSOK Z-013, API 752 and the CCPS Guidelines for Chemical Process Quantitative Risk Analysis.
Distinct from neqsim-process-safety (HAZOP / LOPA / SIL — frequency side) and
neqsim-relief-flare-network (PSV sizing / flare radiation — design side). This
skill is the consequence side of QRA.
import neqsim.process.safety.fire.JetFireModel;
import neqsim.process.safety.dispersion.ProbitModel;
// 30 kg/s gas leak, 50 MJ/kg HoC, 25 % radiative fraction
JetFireModel jet = new JetFireModel(30.0, 50.0e6, 0.25);
double flux50m = jet.radiationFluxAt(50.0); // W/m²
double dist125 = jet.distanceForFlux(12500.0); // m where flux = 12.5 kW/m²Typical thermal radiation criteria (API 521 / NORSOK S-001):
| Flux (kW/m²) | Effect | Use |
|---|---|---|
| 1.6 | No discomfort for long exposure | Public area limit |
| 4.7 | Sufficient for evacuation in 30 s | Escape route |
| 12.5 | Wood ignites, equipment failure (5 min) | Process equipment limit |
| 37.5 | Structural failure of process equipment | Damage to steel structure |
import neqsim.process.safety.fire.PoolFireModel;
// 500 kg liquid, burning rate 0.05 kg/m²·s, dike diameter 8 m, η = 0.30
PoolFireModel pool = new PoolFireModel(0.05, 8.0, 50.0e6, 0.30);
double flux = pool.radiationFluxAt(25.0); // W/m² at 25 mimport neqsim.process.safety.fire.VCEModel;
// 200 kg flammable in cloud, congestion class 7 (heavy)
VCEModel vce = new VCEModel(200.0, 50.0e6, 7);
double overpressure = vce.overpressureAt(60.0); // Pa at 60 m
double safeDist = vce.distanceForOverpressure(20684.0); // m for 3 psiimport neqsim.process.safety.fire.BLEVECalculator;
// 50 t propane vessel
BLEVECalculator bleve = new BLEVECalculator(50000.0, 50.0e6, 0.40);
double fireballDiameter = bleve.fireballDiameter(); // m
double fireballDuration = bleve.fireballDuration(); // s
double thermalDose = bleve.thermalDoseAt(150.0); // (W/m²)^(4/3)·simport neqsim.process.safety.dispersion.GaussianPlume;
// 10 kg/s leak, ground-level source, 4 m/s wind, neutral stability D
GaussianPlume plume = new GaussianPlume(10.0, 0.0, 4.0,
GaussianPlume.Stability.D, GaussianPlume.Terrain.RURAL);
double conc = plume.centerlineGroundConcentration(200.0); // kg/m³
double distLFL = plume.distanceToConcentration(0.044); // m to methane LFLStability classes: A (very unstable) … F (stable). RURAL vs URBAN selects Briggs σ
coefficients per Pasquill-Gifford. Use Stability.F for worst-case dispersion
analysis (calm night, low wind).
For dense releases (CO₂, propane, butane) the Gaussian model under-predicts
near-field concentrations. Use HeavyGasDispersion (Britter-McQuaid screening):
import neqsim.process.safety.dispersion.HeavyGasDispersion;
HeavyGasDispersion hgs = new HeavyGasDispersion(
50.0, // continuous release rate [kg/s]
1.98, // gas density at release [kg/m³]
1.20, // ambient density [kg/m³]
4.0); // wind speed [m/s]
double distLFL = hgs.distanceToConcentration(0.05); // mimport neqsim.process.safety.dispersion.ProbitModel;
// Thermal: Y = a + b·ln(t·F^(4/3)), 60 s exposure at 12.5 kW/m²
double pFatality = ProbitModel.thermalFatality()
.fatalityProbability(60.0, 12500.0);
// Toxic H2S: Y = -31.42 + 3.008·ln(C^1.43·t)
ProbitModel h2s = ProbitModel.h2sFatality();
double pH2S = h2s.fatalityProbability(600.0, 5.0e-4); // 10 min, 500 ppm
// Overpressure (lung haemorrhage): Y = -77.1 + 6.91·ln(P)
ProbitModel ovp = ProbitModel.overpressureFatality();Built-in factories: thermalFatality(), overpressureFatality(),
h2sFatality(), cl2Fatality(), nh3Fatality(), coFatality(). The
ToxicLibrary class centralises probit constants for common toxic gases.
import neqsim.process.safety.qra.ConsequenceAnalysisEngine;
ConsequenceAnalysisEngine e = new ConsequenceAnalysisEngine(
"10 mm gas leak", 1.0e-4); // release frequency [/yr]
e.addJetFire(0.05, jet, ProbitModel.thermalFatality(), 60.0);
e.addJetFire(0.02, pool, ProbitModel.thermalFatality(), 60.0);
e.addToxicCloud(0.01, plume, ProbitModel.h2sFatality(), 600.0);
double IRPA = e.individualFatalityRiskPerYear(50.0); // at 50 m
String text = e.report(50.0);The engine sums:
IRPA(d) = Σ_outcome f_release · f_branch · P_fatality(d, outcome)
Compare against acceptance criteria:
| Criterion | Limit | Source |
|---|---|---|
| Worker IRPA | 1·10⁻³ /yr (intolerable) | UK HSE R2P2 |
| Worker IRPA | 1·10⁻⁶ /yr (broadly acceptable) | UK HSE R2P2 |
| NORSOK FAR | 10 fatalities / 10⁸ h | NORSOK S-001 |
| Public 1 % fatal | 35 m typical for 12.5 kW/m² | API 752 |
import neqsim.process.safety.fire.Api537FlareFlameModel;
Api537FlareFlameModel flame = new Api537FlareFlameModel(
50.0, 50.0e6, 0.20, 200.0) // mDot[kg/s], HoC[J/kg], radiantFrac, vExit[m/s]
.setStackHeightM(40.0)
.setWindSpeedMPerS(10.0);
double r473 = flame.sterileZoneRadiusM(Api537FlareFlameModel.FLUX_4_73_KW); // property line
double q75 = flame.heatFluxAtGroundDistance(75.0); // W/m²
double spl = flame.soundPressureLevelDb(100.0); // dB at 100 mUse this instead of the point-source jet-fire form when the source is an elevated flare tip (it accounts for stack height, wind tilt, and flame geometry).
import neqsim.process.safety.dispersion.HazardousAreaCalculator;
import neqsim.process.safety.dispersion.HazardousAreaCalculator.ReleaseGrade;
HazardousAreaCalculator calc = new HazardousAreaCalculator(
0.1, // release mass flow [kg/s]
6.0, // process pressure [bara]
340.0, // temperature [K]
0.044, // LFL [volume fraction]
0.01604) // molar mass [kg/mol]
.setReleaseGrade(ReleaseGrade.SECONDARY) // CONTINUOUS / PRIMARY / SECONDARY
.setSafetyFactor(0.5);
double dHaz = calc.hazardousDistanceM();
String zone = calc.zoneClassification(); // "Zone 0" / "Zone 1" / "Zone 2"Maps the dispersion result to an Ex zone for electrical-equipment selection. CONTINUOUS → Zone 0, PRIMARY → Zone 1, SECONDARY → Zone 2.
import neqsim.process.safety.fire.PfpDemandCalculator;
import neqsim.process.safety.fire.PfpDemandCalculator.FireType;
import neqsim.process.safety.fire.PfpDemandCalculator.PfpDemandResult;
PfpDemandResult pfp = new PfpDemandCalculator(
100.0e3, // fire heat flux [W/m²] (pool ~100 kW/m², jet ~250+ kW/m²)
0.012) // wall thickness [m]
.setFireType(FireType.POOL) // POOL / JET
.evaluate(3600.0); // required survival time [s]
boolean need = pfp.isPfpRequired();
double thkMm = pfp.getRequiredPfpThicknessMm();
PfpDemandResult.PfpRating rating = pfp.getRating(); // NONE / H60 / J120 ...Determines whether unprotected steel reaches its critical temperature before the required survival time, and if so the intumescent thickness and H/J rating.
ConsequenceAnalysisEngine.exportSourceTerm() writes a JSON block usable by
PHAST, FLACS, KFX or DNV Safeti containing release rate, momentum, density,
duration and chemistry — the standard handoff format described in
neqsim-agent-handoff.
HeavyGasDispersion when density ratio > 1.2.ProbitModel use CCPS values.src/test/java/neqsim/process/safety/{fire,dispersion,qra}/ contain JUnit 5
tests for every model. Run:
./mvnw test -Dtest=FireModelsTest,GaussianPlumeTest,ProbitModelTest,ConsequenceAnalysisEngineTest,Api537FlareFlameModelTest,HazardousAreaCalculatorTest,PfpDemandCalculatorTestneqsim-process-safety — frequency side (HAZOP / LOPA / SIL)neqsim-firewater-deluge-design — the mitigation side: how much fire water the area needs, and whether water is the right barrier for the fire type you just characterisedneqsim-relief-flare-network — PSV sizing and flare radiationneqsim-depressurization-mdmt — emergency depressurization source termsneqsim-agent-handoff — source-term JSON schema© equinor, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in .github/skills/neqsim-consequence-analysis of equinor/neqsim.
Open the folder on GitHubat commit 92261e0
Neqsim Consequence Analysis next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Neqsim Consequence Analysis this skillequinor/neqsim | 156 | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | |
| Candidate Talent Poolsickn33/agentic-awesome-skills | 47k | 1 repos | ~4.2k | Automated safety check: Pass | MIT | |
| Soroban Liquidity Poolsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Web3 Transaction Relayer Poolsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Meteora Dlmm Pool Screeningsickn33/agentic-awesome-skills | 47k | 1 repos | ~1.7k | Automated safety check: Notes | MIT | |
| Account Poolget-bb/bb | 4.2k | — | ~201 | Automated safety check: Pass | MIT |
sickn33/agentic-awesome-skills
Candidate and prospect pool: contact details, experience, skills, consent status and date, referral source and last contact.
sickn33/agentic-awesome-skills
Automated market maker liquidity pool register: constant-product invariant curves, swap fee tiers, and LP token shares for Soroban DeFi.
sickn33/agentic-awesome-skills
Gasless transaction relayer node pool register: fee sponsorship limits, nonce synchronization, and balance replenishment alerts.
sickn33/agentic-awesome-skills
Screen and rank Meteora DLMM pools for LP quality using public Meteora APIs (fee/TVL, bin step, organic score).
get-bb/bb
Configure or diagnose Account Pooler accounts, authentication, quota routing, and failover through bb pool.
LeoYeAI/openclaw-master-skills
Practical fire building, management, and safety skills. An agent skill from LeoYeAI/openclaw-master-skills.
equinor/neqsim
Guides NeqSim agents through acid-gas and contaminant removal with SimpleAmineAbsorber, SimpleAmineRegenerator, SystemKentEisenberg, SystemDesmukhMather, RateBasedAbsorber, MembraneSeparator, and…
equinor/neqsim
Guides agents through ProcessLinkedMPC, ProcessLinearizer, ModelPredictiveController, VirtualFlowMeter, SoftSensor, and DataReconciliationEngine.
equinor/neqsim
Agent-to-agent communication schema for NeqSim. An agent skill from equinor/neqsim.
equinor/neqsim
Autonomous observe-hypothesize-predict-test-discriminate loop for operational anomalies.
equinor/neqsim
Equipment capacity constraints, bottlenecks, utilization snapshots, KPI/response DTOs, validated automation writes and GOR/MPFM rate fitting (CapacityConstraint, BottleneckTracker…
equinor/neqsim
CO2 capture, transport, storage (CCS) and hydrogen systems patterns for NeqSim.
Quantitative consequence analysis - jet/pool fire, VCE, BLEVE, Gaussian and heavy-gas dispersion, probit fatality, individual and societal risk. Neqsim Consequence Analysis is an agent skill from equinor/neqsim. Quantitative consequence analysis - jet/pool fire, VCE, BLEVE, Gaussian and heavy-gas dispersion, probit fatality, individual and societal risk.
Neqsim Consequence Analysis fits situations like: : a task requires fire-radiation contours; dispersion to LFL/IDLH/ERPG; BLEVE thermal/missile assessment; QRA-style integration of release outcomes.
Run `npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a claude-code`. Or copy the skill folder (.github/skills/neqsim-consequence-analysis in equinor/neqsim) into .claude/skills/neqsim-consequence-analysis in your project. Claude Code loads it when a task matches its description.
Run `npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a codex`. Or copy the skill folder (.github/skills/neqsim-consequence-analysis in equinor/neqsim) into .agents/skills/neqsim-consequence-analysis in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add equinor/neqsim --skill neqsim-consequence-analysis -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/neqsim-consequence-analysis, .gemini/skills/neqsim-consequence-analysis, .github/skills/neqsim-consequence-analysis and .opencode/skills/neqsim-consequence-analysis in your project.
SKILL.md names no scripts, command-line tools or credentials: Neqsim Consequence Analysis is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Neqsim Consequence Analysis is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 2.8k tokens (SKILL.md is roughly 11k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Neqsim Consequence Analysis: Candidate Talent Pool (sickn33/agentic-awesome-skills, 47k stars), Soroban Liquidity Pool (sickn33/agentic-awesome-skills, 47k stars), Web3 Transaction Relayer Pool (sickn33/agentic-awesome-skills, 47k stars) and Meteora Dlmm Pool Screening (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
equinor (a GitHub organization) maintains it in equinor/neqsim, which has 156 GitHub stars. The repository holds 66 skills in this directory. The repository was last updated on October 7, 2026.
Source: equinor/neqsim on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.