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-community-skills --skill co2-emissions-screeninggit clone --depth 1 https://github.com/equinor/neqsim-community-skillsWrote 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-community-skills/co2-emissions-screening)<a href="https://agentmods.dev/skills/equinor/neqsim-community-skills/co2-emissions-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/co2-emissions-screening/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-community-skills/co2-emissions-screening"><img src="https://agentmods.dev/badge/skills/equinor/neqsim-community-skills/co2-emissions-screening.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 | $0.00083 | $0.01182 |
| Opus 5 | $0.00042 | $0.00591 |
| Sonnet 5 | $0.00017 | $0.00236 |
| Haiku 4.5 | $0.00008 | $0.00118 |
Grade A, and why
neqsim-co2-emissions-screening 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 11d 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 — 107 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CO2 Emissions Screening
Use this skill for public, educational combustion-CO2 emission screening. It estimates the CO2 mass rate from full combustion of a fuel-gas stream using public per-component carbon counts, so an agent can scope an emission rate before detailed combustion modelling or certified emission-factor reporting.
When to Use
- When a user asks roughly how much CO2 a fuel-gas stream produces when burned.
- When an agent needs a quick emission rate for turbine, heater, or flare fuel.
- When examples must run without confidential metering or certified emission factors.
Inputs
composition: dict of component name to mole fraction (normalized internally).molar_flow: fuel-gas molar flow in mol/s (provide this ormass_flow).mass_flow: fuel-gas mass flow in kg/s (provide this ormolar_flow).co2_limit_t_per_day: optional CO2 limit in tonnes/day for the flag.
Supported components: methane, ethane, propane, n/i-butane, n/i-pentane, hexane, CO2, CO, nitrogen, hydrogen, water, oxygen, H2S, helium.
Outputs
mixture_molecular_weight_g_mol: composition-weighted molecular weight.carbon_per_mole_fuel: carbon atoms per mole of fuel mixture.co2_mass_rate_kg_s: CO2 mass rate.co2_mass_rate_t_per_day: CO2 rate in tonnes/day.specific_co2_kg_per_kg_fuel: CO2 mass per unit fuel mass.emission_warning:ok,over-limit, orno-limit.assumptions: public assumptions used by the placeholder model.
Engineering Method
The Python class CombustionCO2Model uses public combustion stoichiometry:
- the carbon per mole of fuel uses
C = sum(y_i * carbon_number_i). - the CO2 mass rate uses
m_CO2 = n_fuel * C * M_CO2withM_CO2 = 44.01 g/mol. - complete combustion is assumed, so every fuel carbon atom becomes one CO2; feed CO2 is carried through and counted.
- mass-flow input is converted to molar flow with the composition-weighted molecular weight.
This is educational and screening-only logic. It assumes complete combustion with no combustion efficiency, unburned-carbon slip, flaring loss, or capture credit. It is not a replacement for validated combustion modelling, ISO 6976 calculations, certified emission factors, and qualified reporting.
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 11d ago First seen · 107 lines · 83 tokens per session scan A d7129c7c900f
neqsim-co2-emissions-screening is a skill published in the GitHub repository equinor/neqsim-community-skills (2 stars, last pushed yesterday), licensed Apache-2.0. It adds 83 tokens to every session and 1,182 once invoked, about $0.0004 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 2026-08-31.
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