Diagnose modelica

Diagnose Modelica Model

This skill generates a comprehensive diagnostic report for a Modelica model. You run the model through the bundled launcher, then turn the artifacts it leaves behind into a report with the bundled report_blocks.py / trace_variable.py scripts. The report covers variable counts, equation structure, block analysis, solver settings, and (if simulated) runtime performance.

Before you run anything

This skill drives WSMKernelX through the shared launcher ../scripts/wsm_run.py. Read the shared-conventions appendix at the end of this file first — launcher resolution, the Windows-vs-Unix shell/Python rules, the temp-dir and cleanup conventions, the JSON-array output gotcha, and the MSL 4.x dialect notes that every step below assumes.

In --mode diagnose the launcher enables the diagnostic options it needs and keeps all intermediate build artifacts for the report scripts (report_blocks.py / trace_variable.py). It works in _wsm_diagnose_temp/ next to the .mo file and leaves all artifacts there. Tell the user: "Working in temporary directory _wsm_diagnose_temp/. This will be deleted after the report is generated."

Workflow

1. Identify the model file and name

Identify the .mo file and extract the model name — see Appendix → Picking the model name. For a directory-form (multi-file) library, point --model at the library folder (not one class file) and pass the full dotted --name — see Appendix → Directory-form (multi-file) libraries.

2. Run the launcher

python3 "<scripts-dir>/wsm_run.py" --mode diagnose \
  --model "<path-to-ModelFile.mo>" --name ModelName --timeout 180

MSL is auto-detected; override with --msl yes|no or --msl-version 4.1.0. If the model uses an installed non-MSL library (e.g. Hydraulic), add --load-library <Name> — see Appendix → Using non-MSL libraries.

For structure only, skip the simulation entirely: add --no-sim (build-only, much faster). The structural report below still works; only the runtime-performance line is omitted.

A Fatal error: exception ...(_) (e.g. ErrorExt.ErrorMessage(_), LError.Errors(_)) is not an opaque crash — it's a normal error (assertion, parameter/init, type, lookup) that +g let escape, since +g keeps build artifacts but disables exception catching. On any failure the launcher prints the recovered message in an === actual kernel diagnostic === block (re-running the same call without +g, so exception catching is back on and the error surfaces at whatever stage it occurred). Read that block first; don't infer a compiler bug from the Fatal error line. Use the staged diagnostics below only if it surfaces nothing readable.

Staged diagnostics (for a genuinely opaque crash)

A full run goes through the whole pipeline (flatten → optimize → build → simulate); a crash partway through gives no clue which stage failed. The launcher's --call option runs a stage-restricted entry point so you can bracket the failure, and --debug adds the compiler's per-stage dumps and execution statistics:

--call	What it does	When to use
instantiate	Flatten only.	First call when a model is failing — confirms whether flattening succeeds.
build	Flatten + translate to simulator (no simulation).	If flatten passes but the full run crashes — isolates optimization/code-gen from the runtime.
sim	Full pipeline including simulation.	Default for healthy models (used when --call is omitted).

Workflow (only when the diagnostic block above surfaced nothing readable):

1. Run with --call instantiate first. If it fails → it's a flatten error (type/connection/balance). Read the === actual kernel diagnostic === block, then diagnose.out.json in the temp dir.
2. If flatten passes, run --call build --debug and capture stdout — the last stage printed before the crash localizes the bug. The --debug output can be large, so redirect it:

   python3 "<scripts-dir>/wsm_run.py" --mode diagnose \
     --model "<path-to-ModelFile.mo>" --name ModelName \
     --call build --debug > debug.log 2>&1
   

3. Only then run the default (--call sim, or omit it) for the full report.

If the log shows ++++ Running or runtime annotation lines, the model already built — the failure is at init/simulation (a model error), not code-gen; a truncated _build.log ("Step 2 of 4") does not mark where it died.

3. Generate the structural report

After a successful run, use the bundled report_blocks.py script to generate a complete report. This is the preferred approach — it parses all the artifacts automatically, so you never need to read them by hand:

python3 "<scripts-dir>/report_blocks.py" \
  "<temp-dir>/ModelName_blockdebug.json" \
  --header "<temp-dir>/ModelName_header.h" \
  --reslog "<temp-dir>/ModelName_res.log"

The script produces a full report covering variable counts, block summaries, non-trivial systems with solvability details, eliminated aliases, and runtime performance.

Prefer --summary (or --json) for a few-line digest — states, algebraic/parameter counts, zero-crossings, coupled-system count + largest block, and runtime — instead of the full multi-screen report. Reach for the full report only when you need block-level detail. With --no-sim the same --summary works from the _blockdebug.json alone; only the runtime-performance line is omitted.

The artifacts report_blocks.py reads all live in the temp dir (ModelName_header.h, ModelName.sim, ModelName_blockdebug.json, ModelName_res.log, ModelName.log, diagnose.out.json). The script understands their formats for you; only open them directly if you need to dig past what the report surfaces.

4. Present the diagnostic report

Present the report to the user in this format:

# Diagnostic Report: ModelName

## Build Status
- Flatten: Pass/Fail
- Build: Pass/Fail
- Simulation: Pass/Fail

## Model Summary
| Metric | Count |
|--------|-------|
| Continuous states (NX) | ... |
| Discrete states (NDX) | ... |
| Algebraic variables (NY) | ... |
| Parameters (NP) | ... |
| Inputs (NI) | ... |
| Outputs (NO) | ... |
| Zero crossings | ... |
| External objects | ... |
| Clocked partitions | ... |

## Solver Settings
- Method: ...
- Time range: ... to ...
- Step size: ...
- Output steps: ...

## Variable Details
| Name | Kind | Type | Unit | Init |
|------|------|------|------|------|
| ... | STATE | Real | m/s | exact |

## Equation Structure

### Initialization (N blocks)
- Block 0: [solved] variable_name ← equation_text
- ...

### ODE (N blocks)
- Block 0: [solved] ...
- ...

### Output (N blocks)
- ...

### Eliminated Variables (N aliases)
- gain.u → sine.y
- ...

## Potential Issues
- [List any nonlinear systems, large blocks, unsolvable equations, etc.]

## Runtime Performance
- Integration time: ... s
- Function evaluations: ...
- Events: ...
- Step events (dynamic state switches): ...

## Compiler
- Version: ...

Tailor the "Potential Issues" section based on what report_blocks.py reports:

• Nonlinear blocks → "Nonlinear system of N equations — may cause convergence issues at initialization or during simulation"
• Large algebraic loops → "Algebraic loop with N equations — consider breaking with Modelica.Blocks.Math.InverseBlockConstraints or adding initial guesses"
• Many zero crossings → "N zero crossings — may cause slow simulation due to frequent event detection"
• No states → "No continuous states — this is a purely algebraic/discrete model"
• Many events at runtime → "N events detected — consider smoothing discontinuities"

5. Trace a specific variable (optional)

If the user asks to trace a variable (e.g. "trace clutch1.w_rel", "what equations solve w_rel"), use the bundled trace_variable.py script to walk the full dependency chain.

The script needs the _blockdebug.json produced in step 2. Run it from the temp directory:

python3 "<scripts-dir>/trace_variable.py" "<temp-dir>/ModelName_blockdebug.json" "variable.name" --section both

Options for --section:

• init — How the variable gets its starting value (initialization phase)
• ode — How the variable is computed each integration step
• both — Show both traces (default)

The script automatically:

• Walks backwards through predecessor blocks from the target variable to all leaf nodes
• Shows each equation, its source file/line, and solvability
• Flags non-trivial solvability (nonlinear, mixed, conditioned, relaxed)
• If the variable isn't found in the ODE section, automatically tries der(variable) (since state variables are integrated, their derivatives are what appears in the ODE blocks)
• Reports eliminated variable aliases

6. Clean up

Remove _wsm_diagnose_temp/ entirely — commands per OS: Appendix → Temporary directories.

Edge cases

• Model fails to flatten: Report errors from diagnose.out.json. Analyze the error messages and suggest fixes (missing components, type mismatches, unbalanced equations).
• Model flattens but fails to build: Still run report_blocks.py on _blockdebug.json if it was generated — it's produced before compilation. Report build errors from ModelName.log.
• Model builds but fails to simulate: Report runtime errors from _res.log. Check for division by zero, assertion failures, or solver convergence issues.
• Fatal error: exception ...(_) (no _blockdebug.json or .sim): a normal error +g let escape, not a compiler bug. Read the launcher's === actual kernel diagnostic === block (it auto-recovers the message by re-running the same call without +g). Only if it surfaces nothing readable, use the staged diagnostics above; report to Wolfram only when the failure lands in a compiler stage with no model-level cause.
• Multiple models in one file: Use the top-level model/package name — see Appendix → Picking the model name.
• WSMKernelX or compiler not found: see Appendix → When the install or compiler isn't found.

---

Appendix: shared conventions for the Modelica skills

Shared by every Modelica skill that drives WSMKernelX through the bundled launcher; inlined here at release time. For the CLI/option reference, environment variables (WSM_HOME, WSM_VSDEVCMD), install discovery, and the analysis scripts, see ../scripts/README.md.

Locating the launcher

<scripts-dir> (used throughout the skills) is the shared scripts/ folder. Some installs symlink the skill directories without it, so resolve it in this order and use the first that exists:

1. $WSM_SKILLS_SCRIPTS (bash) or $env:WSM_SKILLS_SCRIPTS (PowerShell), if set.
2. ../scripts relative to the skill directory — in a normal install ../scripts/wsm_run.py already exists, so use that path directly; do not run a shell probe to "resolve" it.
3. The repo checkout you installed from, e.g. .../agentskills/scripts.
4. Last resort, search the home directory:
   • PowerShell: Get-ChildItem $HOME -Recurse -Filter wsm_run.py -ErrorAction SilentlyContinue | Select-Object -First 1
   • bash/zsh: find ~ -name wsm_run.py -path '*scripts*' 2>/dev/null | head -1

If only #4 finds it, the install is missing the scripts/ link — tell the user to run install.sh (or install.ps1) from the repo, which links scripts/ too.

Shell and Python

On Windows, use PowerShell. The Git-Bash/cygwin layer may be broken (even ls/find can be absent, giving a misleading "exit 127 / command not found"). Run wsm_run.py with python (not python3); those calls are single-line and shell-agnostic. For cleanup use Remove-Item -Recurse -Force, not rm -rf. On macOS/Linux any POSIX shell is fine and python3 is the usual name.

Let the launcher own .mos/.bat and paths

Do not hand-write .mos scripts, .bat files, or hardcode install/compiler paths. The bundled scripts/wsm_run.py handles every OS difference — it finds the System Modeler install and kernel binary (macOS / Windows / Linux), finds and loads the right MSL files, generates the .mos, and runs the kernel with a working compiler environment per platform (system clang/gcc on macOS/Linux; the Visual Studio dev environment via VsDevCmd.bat on Windows). See ../scripts/README.md for WSM_HOME, the Windows compiler prerequisites, and the full option table.

When the install or compiler isn't found

The launcher searches each OS's standard install locations. If it prints ERROR: Could not locate a Wolfram System Modeler installation, the install is in a non-standard place — ask the user for it and re-run with --wsm-home "<path>" (or have them set WSM_HOME).

Building and simulating also need a C++ toolchain:

• Windows: Visual Studio Build Tools. The launcher locates VsDevCmd.bat itself; if it reports the compiler environment is missing, pass --vsdevcmd "<path-to-VsDevCmd.bat>" (or set WSM_VSDEVCMD) and make sure Build Tools are installed.
• macOS: the Xcode command-line tools (xcode-select --install).
• Linux: gcc/g++.

Run python3 "<scripts-dir>/wsm_run.py" --mode info to see what the launcher discovered.

Temporary directories

The launcher works in a _wsm_<mode>_temp/ directory next to the .mo file (_wsm_validate_temp/, _wsm_simulate_temp/, _wsm_diagnose_temp/) and leaves its outputs there. Tell the user, e.g.: "Working in temporary directory _wsm_<mode>_temp/. This will be deleted afterwards." Pass --tempdir to reuse one directory across models in a session.

Clean up by removing the whole directory — use the user's shell:

rm -rf "<model-dir>/_wsm_<mode>_temp"          # macOS / Linux
# PowerShell: Remove-Item -Recurse -Force "<model-dir>\_wsm_<mode>_temp"

Picking the model name

• The user may provide a path to a .mo file, or you may already be working with one in context.
• Extract the model name: the identifier after model on the first non-comment line, e.g. model FooBar → FooBar. The filename does not always match the model name — parse the actual model/package declaration.
• For packages or nested models, use the top-level model name.
• Pick an instantiable model, not a package, for any kernel call. A package cannot be validated or simulated ("Invalid instantiation … is a package") — use a nested model's full dotted name, e.g. Package.Model.
• Pass an absolute path to --model (relative paths break as the working directory shifts between calls).

Directory-form (multi-file) libraries

A directory-form library stores one class per file with a package.mo at each level. You cannot validate such a class by handing the launcher only its own .mo file — the class's within Lib; clause needs the whole package loaded, and loading the single file alone fails with Internal error: ... expandLibNode: Unknown library: Lib. Instead point --model at the library folder (or its top package.mo, or any class file inside it) and pass the full dotted class name via --name:

python3 "<scripts-dir>/wsm_run.py" --mode validate \
  --model "/abs/path/InvertedPendulum" \
  --name InvertedPendulum.Controller

The launcher resolves any of those forms up to the library's root package.mo and loads the entire package (following package.order) before instantiating --name. It prints a NOTE: telling you which package.mo it loaded. Do not try to work around the unknown-library error by --load-ing individual files.

Reading the JSON output

The kernel writes <mode>.out.json into the temp dir. It is a JSON array — take the first element, then read:

• status.flatten: "Pass" / "Fail" (the primary result for validate).
• status.build: "Pass" / "Fail" — C++ compilation/linking (simulate).
• status.result: simulation result status (simulate).
• messages.errors / messages.warnings / messages.notifications: arrays (empty if none).
• flat_model (validate) / simulation.resultFile (simulate): the flattened class / path to the .mat.

See ../scripts/README.md (wsm_run.py section) for the full field reference.

MSL 4.x dialect

This toolchain ships MSL 4.x. When authoring models, use the 4.x names — the 3.2 names flatten with confusing "not found" errors:

• units: Modelica.Units.SI.* (not Modelica.SIunits.*)
• source frequency parameter: f (not freqHz), e.g. SineVoltage(V=.., f=..)
• declare the dependency as annotation(uses(Modelica(version="4.0.0")))

Run python3 "<scripts-dir>/wsm_run.py" --mode info to confirm the exact MSL version. wsm_run.py also warns on stderr if it spots a 3.2 name in the model.

When a flatten fails with Element not found ... in Modelica..., the MSL component path is wrong (a misremembered name, not a missing install). Resolve the correct path with the search-modelica-docs skill — e.g. sine is Modelica.Blocks.Sources.Sine (not Math.Sine), difference is Math.Feedback (not Math.Subtract), and saturation is Nonlinear.Limiter (not Nonlinear.Saturation). Do not grep or walk the System Modeler install tree to hunt for the class.

Using non-MSL libraries (Hydraulic, and other installed libraries)

MSL is automatic (--msl). For any other library a model uses — Hydraulic, or anything the user installed from the Library Store — the launcher can find it for you. Two steps, no guessing at paths:

1. See what is installed (bundled with System Modeler, user-installed archives, and any custom folders configured in Model Center):

   python3 "<scripts-dir>/wsm_run.py" --mode libraries
   # add --json for a machine-readable array; each row has name/version/source/package
   

   To get just one library's package path (e.g. for a manual --load): --mode libraries --library Hydraulic (add --library-version 2.1 to pin a version).

2. Load it into a build by name — add --load-library <Name> to a validate / simulate / diagnose run (repeatable; pin a version with Name==Ver):

   python3 "<scripts-dir>/wsm_run.py" --mode validate \
     --model "<path>/M.mo" --name M --load-library Hydraulic
   

   The launcher resolves the library (bundled → user-installed → Model-Center custom path, newest version wins) and loadFiles it before the model. A library usually pulls in MSL, so keep MSL on (auto, or --msl yes). Override a lookup with $WSM_LIBRARY_<NAME> (e.g. WSM_LIBRARY_HYDRAULIC=/path/to/package.moe), or fall back to an explicit --load <path-to-package.mo|.moe>.