Install
openclaw skills install fluid-network-sloverSolve and analyze steady incompressible fluid networks from TOML definitions. Use when users ask to design a network template, validate TOML topology data, compute node pressure plus pipe flow/velocity, run named scenarios, and generate reliability reports from pressure and flow thresholds.
openclaw skills install fluid-network-sloverParse a TOML fluid network, apply named scenario overrides, solve hydraulic steady-state variables, and produce reliability analysis outputs. Use the scripts in this skill for deterministic execution instead of rewriting solver logic each time.
references/toml_schema.md when defining or checking input.system, nodes, pipes, and scenarios.scripts/run_fluid_skill.py with one scenario or all scenarios.Use this command from the skill root:
python scripts/run_fluid_skill.py --toml <input.toml> [--scenario <name> | --all-scenarios] [--report-out <report.md>] [--json-out <result.json>] [--print-text]
Supported parameters:
--toml: required input network file.--scenario: single scenario name (default base).--all-scenarios: analyze base plus all named scenarios.--report-template: optional template path, default assets/report_template.md.--report-out: optional markdown report output path.--json-out: optional JSON result output path.--print-text: print readable scenario analysis to stdout.--generate-template: optionally write a starter TOML template and exit.Generate these outputs based on user request:
assets/report_template.md.Use assets/report_template.md placeholders:
{{generated_at_utc}}{{input_file}}{{scenario_mode}}{{scenario_count}}{{summary_table}}{{detail_sections}}scripts/fluid_solver_core.py: compatibility shim that re-exports the maintained root implementation.scripts/run_fluid_skill.py: CLI entry for parameterized execution and report generation.references/toml_schema.md: authoritative schema and sample.assets/report_template.md: default report skeleton.assets/sample_network.toml: runnable demo network.requirements.txt: runtime dependencies for packaging or local execution.Run one scenario:
python scripts/run_fluid_skill.py --toml assets/sample_network.toml --scenario Normal_Operation --print-text
Run all scenarios and export report + JSON:
python scripts/run_fluid_skill.py --toml assets/sample_network.toml --all-scenarios --report-out outputs/report.md --json-out outputs/result.json
Generate a template:
python scripts/run_fluid_skill.py --generate-template outputs/template.toml