OpenClaw-Medical-Skills simulation-validator
Validate simulations before, during, and after execution. Use for pre-flight checks, runtime monitoring, post-run validation, diagnosing failed simulations, checking convergence, detecting NaN/Inf, or verifying mass/energy conservation.
install
source · Clone the upstream repo
git clone https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/simulation-validator" ~/.claude/skills/freedomintelligence-openclaw-medical-skills-simulation-validator && rm -rf "$T"
OpenClaw · Install into ~/.openclaw/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/simulation-validator" ~/.openclaw/skills/freedomintelligence-openclaw-medical-skills-simulation-validator && rm -rf "$T"
manifest:
skills/simulation-validator/SKILL.mdsource content
Simulation Validator
Goal
Provide a three-stage validation protocol: pre-flight checks, runtime monitoring, and post-flight validation for materials simulations.
Requirements
- Python 3.8+
- No external dependencies (uses Python standard library only)
- Works on Linux, macOS, and Windows
Inputs to Gather
Before running validation scripts, collect from the user:
| Input | Description | Example |
|---|---|---|
| Config file | Simulation configuration (JSON/YAML) | |
| Log file | Runtime output log | |
| Metrics file | Post-run metrics (JSON) | |
| Required params | Parameters that must exist | |
| Valid ranges | Parameter bounds | |
Decision Guidance
When to Run Each Stage
Is simulation about to start? ├── YES → Run Stage 1: preflight_checker.py │ └── BLOCK status? → Fix issues, do NOT run simulation │ └── WARN status? → Review warnings, document if accepted │ └── PASS status? → Proceed to run simulation │ Is simulation running? ├── YES → Run Stage 2: runtime_monitor.py (periodically) │ └── Alerts? → Consider stopping, check parameters │ Has simulation finished? ├── YES → Run Stage 3: result_validator.py │ └── Failed checks? → Do NOT use results │ → Run failure_diagnoser.py │ └── All passed? → Results are valid
Choosing Validation Thresholds
| Metric | Conservative | Standard | Relaxed |
|---|---|---|---|
| Mass tolerance | 1e-6 | 1e-3 | 1e-2 |
| Residual growth | 2x | 10x | 100x |
| dt reduction | 10x | 100x | 1000x |
Script Outputs (JSON Fields)
| Script | Output Fields |
|---|---|
| , , |
| , , |
| , , |
| , |
Three-Stage Validation Protocol
Stage 1: Pre-flight (Before Simulation)
- Run
scripts/preflight_checker.py --config simulation.json - BLOCK status: Stop immediately, fix all blocker issues
- WARN status: Review warnings, document accepted risks
- PASS status: Proceed to simulation
python3 scripts/preflight_checker.py \ --config simulation.json \ --required dt,dx,kappa \ --ranges "dt:1e-6:1e-2,dx:1e-4:1e-1" \ --min-free-gb 1.0 \ --json
Stage 2: Runtime (During Simulation)
- Run
periodicallyscripts/runtime_monitor.py --log simulation.log - Configure alert thresholds based on problem type
- Stop simulation if critical alerts appear
python3 scripts/runtime_monitor.py \ --log simulation.log \ --residual-growth 10.0 \ --dt-drop 100.0 \ --json
Stage 3: Post-flight (After Simulation)
- Run
scripts/result_validator.py --metrics results.json - All checks PASS: Results are valid for analysis
- Any check FAIL: Do NOT use results, diagnose failure
python3 scripts/result_validator.py \ --metrics results.json \ --bound-min 0.0 \ --bound-max 1.0 \ --mass-tol 1e-3 \ --json
Failure Diagnosis
When validation fails:
python3 scripts/failure_diagnoser.py --log simulation.log --json
Conversational Workflow Example
User: My phase field simulation crashed after 1000 steps. Can you help me figure out why?
Agent workflow:
- First, check the log for obvious errors:
python3 scripts/failure_diagnoser.py --log simulation.log --json - If diagnosis suggests numerical blow-up, check runtime stats:
python3 scripts/runtime_monitor.py --log simulation.log --json - Recommend fixes based on findings:
- If residual grew rapidly → reduce time step
- If dt collapsed → check stability conditions
- If NaN detected → check initial conditions
Error Handling
| Error | Cause | Resolution |
|---|---|---|
| File path invalid | Verify config path exists |
| Parameter is not a number | Fix config file format |
| Parameter outside bounds | Adjust parameter or bounds |
| Permission issue | Check directory permissions |
| Disk nearly full | Free up space or reduce output |
Interpretation Guidance
Status Meanings
| Status | Meaning | Action |
|---|---|---|
| PASS | All checks passed | Proceed with confidence |
| WARN | Non-critical issues found | Review and document |
| BLOCK | Critical issues found | Must fix before proceeding |
Confidence Score Interpretation
| Score | Meaning |
|---|---|
| 1.0 | All validation checks passed |
| 0.75+ | Most checks passed, minor issues |
| 0.5-0.75 | Significant issues, review carefully |
| < 0.5 | Major problems, do not trust results |
Common Failure Patterns
| Pattern in Log | Likely Cause | Recommended Fix |
|---|---|---|
| NaN, Inf, overflow | Numerical instability | Reduce dt, increase damping |
| max iterations, did not converge | Solver failure | Tune preconditioner, tolerances |
| out of memory | Memory exhaustion | Reduce mesh, enable out-of-core |
| dt reduced | Adaptive stepping triggered | May be okay if controlled |
Limitations
- Not a real-time monitor: Scripts analyze logs after-the-fact
- Regex-based: Log parsing depends on pattern matching; may miss unusual formats
- No automatic fixes: Scripts diagnose but don't modify simulations
References
- Detailed checklist and criteriareferences/validation_protocol.md
- Common failure signatures and regex patternsreferences/log_patterns.md
Version History
- v1.1.0 (2024-12-24): Enhanced documentation, decision guidance, Windows compatibility
- v1.0.0: Initial release with 4 validation scripts