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Agent skill

Cantera Ignition Delay

by K-Dense-AI in K-Dense-AI/scientific-agent-skills

Runs Cantera constant-volume or constant-pressure ignition simulations and reports temperature-based ignition delay with mechanism provenance and checks.

MITAuto-check passedResearch & Science

Install Cantera Ignition Delay

skills CLI
$ npx skills add K-Dense-AI/scientific-agent-skills --skill cantera -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install K-Dense-AI/scientific-agent-skills cantera --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/cantera .claude/skills/cantera && rm -rf skills-src

Use ~/.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/

Facts

Skill name
cantera
GitHub stars
48k
Used in
1 other repo
Token cost
~2.2k tokens
SKILL.md length
951 words
Files
4 (incl. scripts, references, assets)
Skills in repo
153
Repo updated
First seen
Licence
MIT

At a glance

Runs Cantera constant-volume or constant-pressure ignition simulations and reports temperature-based ignition delay with mechanism provenance and checks.

  • Works in 6 steps: Identify the mechanism and its validated… → Choose constant volume or constant… → Copy assets/hydrogen-ignition.json and… → …
  • Computing ignition delay for a fuel and oxidizer mixture at set conditions
  • SKILL.md covers When to use, Workflow, Execute the tested example and Exact delay and refinement…, plus 2 more sections
  • Runs Python scripts from its folder; calls uv and python

What it does

This skill covers one calculation type: a closed, adiabatic, homogeneous ideal-gas reactor with a known kinetic mechanism, initial temperature, pressure and mole composition. A bundled helper, scripts/ignition_delay.py, runs both constant-volume and constant-pressure cases and reports a delay defined from the temperature history. It is not a flame solver or a general reactor-network builder.

The workflow starts by identifying the mechanism, its validated condition range, source, version and any modifications, then supplying kelvin, pascals, seconds and mole amounts explicitly. You copy the hydrogen example in the assets folder, which uses Cantera's bundled h2o2.yaml mechanism, and change its conditions. The agent picks a time horizon and output spacing fine enough to locate the heating-rate peak, runs the helper, inspects all four histories, and refines again if the delay shifts, the peak nears a time boundary or conservation checks fail.

The report is meant to travel with the delay: conditions, mechanism hash, reactor constraint, delay definition and stated scientific limits. A successful run proves only that the numerics executed, not that the mechanism suits your fuel, so a references file covers mechanism choice, experiment comparison and two-stage ignition.

When your agent uses it

  • Computing ignition delay for a fuel and oxidizer mixture at set conditions
  • Comparing ignition behavior across kinetic mechanisms
  • Checking temperature histories for a constant-volume or constant-pressure case

Example prompts

  • “Run the hydrogen ignition example from the skill and report the delay with its mechanism hash.”
  • “Compare constant-pressure and constant-volume ignition delay for the same mixture.”
  • “Check whether my ignition delay result is numerically converged.”

Requirements

  • Python 3.12 to 3.14
  • Cantera 3.2.0 and NumPy
  • Network access for installation
  • Custom mechanisms as Cantera YAML files
  • Compatibility (from SKILL.md): Requires Python 3.12-3.14, Cantera 3.2.0, and NumPy. Installation needs network access; simulations run locally without credentials. Custom mechanisms must be available as Cantera YAML files.

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Identify the mechanism and its validated condition range. Preserve its source, version,
  2. Choose constant volume or constant pressure from the physical experiment. Supply K,
  3. Copy assets/hydrogen-ignition.json and change its conditions.
  4. Set a time horizon long enough to observe the temperature rise and the decline of the
  5. Run the helper and inspect all four histories and the report. Refine again if the delay
  6. Report the condition set, mechanism hash, reactor constraint, delay definition, output

What it can do on your machine

Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv
    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • cantera.org

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires Python 3.12-3.14, Cantera 3.2.0, and NumPy. Installation needs network access; simulations run locally without credentials. Custom mechanisms must be available as Cantera YAML files.

    From compatibility in the SKILL.md frontmatter.

Context cost

Cantera Ignition Delay loads about 2.2k tokens when it runs, and up to ~3k if it reads all its reference files. Until then it costs about 82 tokens; SKILL.md has 951 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~82
When it runs · the whole SKILL.md, loaded when a task matches
~2.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3k

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.

Safety

Auto-check passed

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); the scripts in this folder are not scanned.

SKILL.md

The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its MIT licence (© K-Dense-AI). 951 words, ~2,157 tokens.

Download SKILL.mdSave it as .claude/skills/cantera/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
cantera
description
Runs Cantera homogeneous chemical reactors and evaluates ignition delay with mechanism provenance, conservation checks, and numerical refinement. Use for combustion kinetics, closed adiabatic ideal-gas constant-volume or constant-pressure ignition, temperature histories, or mechanism-specific ignition-delay comparisons.
compatibility
Requires Python 3.12-3.14, Cantera 3.2.0, and NumPy. Installation needs network access; simulations run locally without credentials. Custom mechanisms must be available as Cantera YAML files.
license
MIT
metadata.version
1.1
metadata.skill-author
K-Dense Inc.
metadata.tested-package-version
3.2.0
metadata.last-reviewed
2026-09-30

Cantera: homogeneous ignition calculations

When to use

Use for a closed, adiabatic, homogeneous ideal-gas reactor with a known kinetic mechanism, initial temperature, pressure, and mole composition. The bundled helper runs both constant volume and constant pressure cases and reports a precisely defined temperature-based delay. It is not a flame solver or a general reactor-network builder.

A calculation completing successfully establishes numerical execution, not mechanism validity for the fuel, pressure, temperature, diluent, or measured ignition observable. Read references/interpretation.md when choosing a mechanism, comparing experiments, or interpreting unresolved/two-stage ignition.

Workflow

  1. Identify the mechanism and its validated condition range. Preserve its source, version, citation, and any modifications. Check that its phase is ideal-gas and that every reactant, diluent, and tracked species exists. For custom YAML with imports, retain the original dependency files as well as the generated phase snapshot. Custom Python rate extensions additionally need their original code and environment for replay.
  2. Choose constant volume or constant pressure from the physical experiment. Supply K, Pa, seconds, and mole amounts explicitly. mole_amounts is normalized to mole fractions; it is not a mass-fraction mapping. The report includes the normalized initial composition.
  3. Copy assets/hydrogen-ignition.json and change its conditions. The supplied H2/O2/Ar case uses Cantera's bundled h2o2.yaml for an executable numerical example; it is not a recommendation for every hydrogen experiment.
  4. Set a time horizon long enough to observe the temperature rise and the decline of the heating-rate peak. Choose output spacing fine enough to locate that peak. Set a minimum temperature rise to distinguish ignition from negligible heating or numerical noise.
  5. Run the helper and inspect all four histories and the report. Refine again if the delay changes materially, if the maximum approaches a time boundary, or if conservation fails. Compare the temperature and tracked-species histories with the actual ignition definition.
  6. Report the condition set, mechanism hash, reactor constraint, delay definition, output spacing, numerical changes, and scientific limits together with the delay.

Execute the tested example

From the collection root:

bash
uv run --no-project --python 3.12 --with cantera==3.2.0 --with numpy==2.5.3 \
  python skills/cantera/scripts/ignition_delay.py \
  skills/cantera/assets/hydrogen-ignition.json hydrogen-result

Tested on Python 3.12, Cantera 3.2.0, and NumPy 2.5.3. No external solver executable or credentials are needed. Local relative mechanism paths resolve against the configuration file directory before Cantera's built-in data search. Use a new output directory each run.

The 1000 K, 101325 Pa, H2:O2:Ar = 2:1:7 constant-volume example gives about 0.313 ms using the stated max(dT/dt) definition. At 3 ms its temperature is approximately 2920.67 K and agrees with a separate UV equilibrium calculation. These are package regression values, not experimental validation data.

Exact delay and refinement contract

Delay is the time of the global maximum of numpy.gradient(T, time, edge_order=2) on a uniform output grid. It is reported only if the maximum temperature rise reaches minimum_temperature_rise_k and the maximum is at least two sample indices from each boundary. Otherwise delay_s is null and a status explains why. No delay beyond the simulation horizon is extrapolated.

The helper explicitly uses Cantera 3.2's clone=True and reads evolving properties from reactor.phase. The original Solution retains the initial state; do not read it as the reactor's final state. ReactorNet.advance(t) requests an absolute time, and no advance limits are configured, so the output grid remains uniform.

It runs four independent fresh reactors:

RunChange from configured conditions
baselineOriginal settings
finer_outputHalf output spacing, same horizon and solver controls
tighter_solverBoth solver tolerances divided by ten; maximum internal time step halved
longer_horizonTwice the horizon with the original output spacing

numerically_resolved requires all runs to yield delays, relative delay changes within delay_relative_tolerance, and all conservation checks to pass. Agreement on a discrete grid is not a statistical error bar: also report the output spacing. The baseline samples must be between 11 and 50000, leaving room for refinement. Runtime grows with mechanism size, stiffness, and the chosen horizon; integration failures retain Cantera's error text.

Show full SKILL.md (323 more words)Show less

Outputs and checks

  • report.json: all input settings, package versions, configuration and mechanism hashes, normalized starting composition, four delay estimates, numerical changes, conservation, and mechanism thermodynamic temperature bounds.
  • baseline.csv, finer_output.csv, tighter_solver.csv, longer_horizon.csv: time, temperature, pressure, volume, mass, total internal energy, total enthalpy, and requested species mole fractions.
  • mechanism.yaml: a Cantera-written snapshot of the loaded phase, species, and reactions. The helper requests write_yaml(precision=17) and saves the exact UTF-8 bytes it hashes, without platform newline conversion. The report also hashes the located original mechanism file. Imported source dependencies are not separately hashed; the snapshot captures the loaded model. Its generated header includes a date, so the snapshot hash identifies the saved artifact and need not match between otherwise identical reruns.

Closed reactors conserve mass and elemental mass fractions. The constant-volume case checks total internal energy; the constant-pressure case checks total enthalpy. Energy error is divided by max(abs(initial_energy_J), 1 J). Diagnostic tolerances are mass relative drift <1e-8, elemental absolute drift <1e-8, energy scaled drift <1e-6, species mass-fraction sum error <1e-8, and species mass fractions >-1e-10. These checks expose numerical issues and do not measure kinetic-model uncertainty.

Check within_thermo_temperature_range separately: it checks saved output states, not every internal integration state. Numerical resolution does not mean species thermodynamic fits stayed within their temperature bounds. The helper cannot assess pressure-dependent kinetic validity from these bounds.

Scope and upstream references

The suite covers both reactor constraints, conservation, final-state agreement with independent Cantera equilibrium, nonigniting conditions, unresolved boundary maxima, refinement, snapshot replay, and invalid composition/conditions. It does not validate shock-tube heat loss, real-gas effects, surfaces, flow devices, flames, or multistage experimental ignition definitions. Build those models only with the necessary physics and their own checks; do not relabel this helper's result as one of them.

© K-Dense-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references, assets) in skills/cantera of K-Dense-AI/scientific-agent-skills.

  • SKILL.md
  • assets/hydrogen-ignition.json
  • references/interpretation.md
  • scripts/ignition_delay.py

Open the folder on GitHubat commit 92ace75

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

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Works with

Categories

Questions about Cantera Ignition Delay

What does Cantera Ignition Delay do?

Runs Cantera constant-volume or constant-pressure ignition simulations and reports temperature-based ignition delay with mechanism provenance and checks. This skill covers one calculation type: a closed, adiabatic, homogeneous ideal-gas reactor with a known kinetic mechanism, initial temperature, pressure and mole composition.py, runs both constant-volume and constant-pressure cases and reports a delay defined from the temperature history.

When should I use Cantera Ignition Delay?

Cantera Ignition Delay fits situations like: computing ignition delay for a fuel and oxidizer mixture at set conditions; comparing ignition behavior across kinetic mechanisms; checking temperature histories for a constant-volume or constant-pressure case.

How do I install Cantera Ignition Delay in Claude Code?

Run `npx skills add K-Dense-AI/scientific-agent-skills --skill cantera -a claude-code`. Or copy the skill folder (skills/cantera in K-Dense-AI/scientific-agent-skills) into .claude/skills/cantera in your project. Claude Code loads it when a task matches its description.

How do I install Cantera Ignition Delay in Codex?

Run `npx skills add K-Dense-AI/scientific-agent-skills --skill cantera -a codex`. Or copy the skill folder (skills/cantera in K-Dense-AI/scientific-agent-skills) into .agents/skills/cantera in your project. Codex loads it when a task matches its description.

Can I use Cantera Ignition Delay in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add K-Dense-AI/scientific-agent-skills --skill cantera -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cantera, .gemini/skills/cantera, .github/skills/cantera and .opencode/skills/cantera in your project.

What does Cantera Ignition Delay need to run?

Going by SKILL.md and its folder, Cantera Ignition Delay needs Python for the scripts in its folder and the command-line tools its instructions call (uv and python). Our summary lists: Python 3.12 to 3.14; Cantera 3.2.0 and NumPy; Network access for installation; Custom mechanisms as Cantera YAML files. Compatibility (from SKILL.md): Requires Python 3.12-3.14, Cantera 3.2.0, and NumPy. Installation needs network access; simulations run locally without credentials. Custom mechanisms must be available as Cantera YAML files..

Does Cantera Ignition Delay access the network?

SKILL.md names 1 domain. As links in the text: cantera.org. This is read from the text; nothing was executed.

Is Cantera Ignition Delay safe to install?

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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Cantera Ignition Delay use?

Cantera Ignition Delay is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cantera Ignition Delay use?

About 2.2k tokens (SKILL.md is roughly 8.6k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 819 tokens, read only when the agent opens those files.

What are the alternatives to Cantera Ignition Delay?

Skills that share tags, products or a category with Cantera Ignition Delay: Astropy (zLanqing/codex-claude-academic-skills, 4.7k stars), Climate Ds (Hongjian01/ClimWorkflow, 102 stars), pydicom DICOM Toolkit (davila7/claude-code-templates, 32k stars) and DP-GEN Simplify Workflow (jinzhezenggroup/computational-chemistry-agent-skills, 148 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cantera Ignition Delay?

K-Dense-AI (a GitHub organization) maintains it in K-Dense-AI/scientific-agent-skills, which has 48,095 GitHub stars. The repository holds 153 skills in this directory. The repository was last updated on October 5, 2026.

Source: K-Dense-AI/scientific-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.