fix-sldv-incompatibility
Use when a Simulink model is incompatible with Simulink Design Verifier (sldvcompat returns false, or an SLDV analysis errors out on an unsupported construct) and needs to be made analyzable.
Install / Use
npx skills add matlab/simulink-agentic-toolkit --skill fix-sldv-incompatibilityInstalls into whichever agent you are using.
SKILL.md
Installable skill definition
Quality Score
Category
Customer SupportSupported Platforms
Our assessment of fix-sldv-incompatibility
fix-sldv-incompatibility scores 93/100 on our quality scale, 91st of 331 Customer Support skills we index (top 28%).
Its SKILL.md is 15 KB long, well organised into 13 sections with 4 code examples: a thorough specification that gives an agent plenty to work with.
With 1,148 GitHub stars, it is one of the more widely adopted skills in the catalogue.
Maintenance, license and trust
- The repository was last updated 16 days ago, so fix-sldv-incompatibility is actively maintained.
- No license is declared. By default that means all rights are reserved: you can read it, but reusing or redistributing it is not clearly permitted. Ask the author before building on it commercially.
- Its trust signals score 88/100, with 1 caution from licensing, adoption, age or documentation. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
fix-sldv-incompatibility compared with similar skills
All 4 of these similar skills score higher than fix-sldv-incompatibility; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| fix-sldv-incompatibility (this skill)by matlab | 93 | 1.1k | 16d ago | SKILL.md |
| algorithmic-artby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
| pptxby anthropics | 100 | 177.9k | 11d ago | SKILL.md |
| designby nextlevelbuilder | 100 | 130.2k | 12d ago | SKILL.md |
| ui-ux-pro-maxby nextlevelbuilder | 100 | 130.2k | 12d ago | SKILL.md |
Frequently asked questions
- How do I install fix-sldv-incompatibility?
- Run
npx skills add matlab/simulink-agentic-toolkit --skill fix-sldv-incompatibility. The install tabs above show the steps for each supported agent. - Which AI agents does fix-sldv-incompatibility work with?
- It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
- Is fix-sldv-incompatibility safe to use?
- It declares no license and scores 88/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is fix-sldv-incompatibility still maintained?
- The repository was last updated 16 days ago, so fix-sldv-incompatibility is actively maintained.
Skill content
View source on GitHubname: fix-sldv-incompatibility description: Use when a Simulink model is incompatible with Simulink Design Verifier (sldvcompat returns false, or an SLDV analysis errors out on an unsupported construct) and needs to be made analyzable. Diagnoses the incompatibility, applies the matching fix to a copy, and confirms the copy is compatible; optionally raises confidence the fix preserved behavior via a back-to-back consistency replay (agreement on the generated tests, not a proof of equivalence). Do NOT use for running test generation, design error detection, or requirement verification themselves — only for making a model compatible so those can proceed. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: author: MathWorks version: "1.0"
SLDV Incompatibility Fixer
Fix Simulink Design Verifier incompatibilities by diagnosing the model and applying the matching fix. Block-level fixes go through model_edit; solver/config-level fixes are the one exception that requires setting the parameter directly (see Step 3).
When to Use
- User asks "why is my model incompatible with SLDV?"
- User asks "make this model compatible with SLDV"
- User asks to fix SLDV incompatibility issues
- User runs
sldvcompatand getsfalse - A test-generation or design-error-detection run errors out on an unsupported construct, and the user asks to get past it — make the model analyzable first, then hand back to that workflow
When NOT to Use
- The model is already compatible (
sldvcompatreturnstrue) — there is nothing to fix. - The task is to run an SLDV analysis mode (test generation, design error detection, property proving) on an already-compatible model — use the corresponding analysis skill, not this one.
- The incompatibility is intended and the user wants to keep the unsupported construct — do not silently rewrite the model.
- The request is a general Simulink modeling edit unrelated to SLDV compatibility.
Scope
The core job is diagnose → fix → confirm compatible (Steps 1–4). That is the default endpoint. Running an SLDV analysis mode (test generation, design error detection) and verifying behavior on the original model is optional and only happens when the surrounding intent calls for it (Step 5). A user who just wants compatibility gets the fix and nothing more.
Prerequisites
- Products: Simulink and Simulink Design Verifier, R2023b or later.
- The model must build in a normal Simulink compile, with all its external
dependencies present. SLDV compatibility is a separate question from whether
the model compiles at all. Two non-compat cases also make
sldvcompatreturnfalse: a genuine authoring bug (undefined block parameter, unresolved reference), fixed by repairing the model; and a genuinely missing external dependency — a data-dictionary file, referenced-model file, data file, library, or workspace variable the model needs that is not present / cannot be located — fixed by providing the resource, not by editing the model (see Step 1.5). Neither is fixed with a compatibility rule. (A resource that is present but merely opaque to SLDV — a protected.slxpreference, external custom code, an S-function — is different again: that you do fix, by stubbing.) When a model failssldvcompat, Step 1 also runs a normal-mode compile probe and reportsresult.compiles/result.buildErrorso you can tell these apart before matching a rule. - This skill's functions live in its
scripts/directory. Call them withevaluate_matlab_codeusingproject_pathset to that folder so MATLAB can find them.
Workflow
Step 1: Run the Diagnostic Tool
Call via evaluate_matlab_code:
% project_path = the skill's scripts/ folder (via evaluate_matlab_code)
result = sldv_diagnose_incompatibility('<model_path>');
This will:
- Create a copy named
<model>_sldv_compatible.slxin the same folder - Run
sldvcompaton the copy
It returns a result struct with these top-level fields:
.compatible—true/false, thesldvcompatstatus on the copy.copyPath— full path to the working copy (<model>_sldv_compatible.slx). Later steps pass this tomodel_editand tosldv_verify_consistency.copyName— name of the copy with no extension (use withsldvcompat/save_system/close_system).findings— struct array, one entry per issuesldvcompatitself reports, each with.msgid,.message,.type,.blockPath, and.blockType.compiles— logical, populated only when.compatible == false: the result of a normal-mode Simulink compile probe on the copy. It is a diagnostic aid, not a gate — the findings above stay authoritative and are matched against the catalog regardless. Its purpose is the case where the findings are only generic:truemeans the model builds (a real SLDV limitation),falsemeans it does not compile at all (a plain authoring bug the catalog does not cover — see Prerequisites; fix the model first)..buildError— when.compiles == false, the compile error's.identifierand.message; empty strings otherwise.
sldvcompat is authoritative: each finding already names the offending object.
For a block-level issue, .blockPath is the full block path (nesting
included, e.g. mdl/Sub/White Noise) and .blockType its BlockType. For a
config-level issue (variable-step solver, nonempty InitFcn, concurrent
execution, …), .blockPath is the model name, .blockType is empty, and
.msgid identifies the setting.
The diagnostic does not scan blocks or pre-read config params: use
model_overview / model_read / model_query_params to inspect whatever a
finding points to, and the rule catalog in references/incompatibility-rules.md
to decide the fix.
A config-level finding can MASK block-level findings. A variable-step
solver, for example, stops sldvcompat before it reaches the blocks. So more
issues may surface only after you fix the config-level ones and re-run the
diagnostic — never assume the first pass lists everything (Step 4 loops).
If result.compatible == true, the model is already compatible. Done.
Step 1.5: Triage a Missing External Dependency (ask, don't fix)
Some incompatibilities are not something to fix in the model at all — the
model is fine, but an external resource it depends on is genuinely absent from
the environment: a data dictionary (.sldd) file that is not on disk, a
referenced model file that cannot be located, a From File / From Spreadsheet
data file that does not exist, a library / MATLAB class / workspace variable a
parameter resolves to that is nowhere on the path. SLDV cannot analyze what it
cannot find, so sldvcompat fails — but applying a compatibility rule
(replacing or stubbing the block) would be wrong: it hides a real gap and
discards the model's intended behavior.
Recognize this class before matching a rule: it shows up as result.compiles == false together with a result.buildError (or a result.findings entry) whose
message says a named resource is missing / not found / does not exist / cannot
be located or resolved. The identifiers vary by resource and release (e.g. a
missing data-dictionary file, a not-found referenced-model file, an absent data
file), so match on the meaning — a named external artifact that isn't
there — not on a fixed list of msgids. See "Missing External Dependencies" in
references/incompatibility-rules.md.
This is NOT the present-but-opaque case — do not confuse the two. A resource
that exists but SLDV cannot see inside is a normal stubbing job, not a
missing dependency: a protected (.slxp) referenced model, a
Model block referencing one that is present, external custom code / an
S-function whose source is opaque, a MATLAB Function block calling an
external routine. These are on disk and resolve fine — SLDV just can't analyze
their internals. Fix them (stub the block), do not ask the user for them. If
result.compiles == true (the model builds), it is by definition not a
missing dependency — go straight to Step 2. Only defer to the user when the
named artifact truly cannot be found.
When you hit one, do not fix or rewrite the model. Instead:
- Explain why it is incompatible, in plain terms, quoting the exact resource
named in
result.buildError.message/ the finding message (e.g. "the model references data dictionaryparams.sldd, which SLDV cannot find on the path"). - Ask the user to provide it — supply the missing file / dictionary / referenced model / variable, or point the skill at its location so it is resolvable — and then re-run the diagnostic.
Only once the dependency is resolvable does the normal diagnose → match → fix
flow apply. Two other compiles == false cases are not this and must not be
routed here: a plain authoring bug (undefined parameter, broken expression)
is resolved by repairing the model; a present-but-opaque resource
(protected .slxp reference, external custom code, S-function) is resolved by
stubbing the block per Step 2/3. Ask the user only when the named artifact
genuinely cannot be found — never for a resource that is present but unanalyzable.
Step 2: Match the Rule
The rule catalog is not inlined here — it lives in
references/incompatibility-rules.md. Load and follow that file. For
each entry in result.findings, match .msgid (and, for block-level findings,
the .blockType at .blockPath) against the catalog, then apply the listed
fix. Use model_read on .blockPath to inspect the offending block's
parameters. Use the catalog's Disambiguation Guide when a msgid maps to multiple
rules, and its Stubbing Strategy / Integrator port-matching / block-reduction
sections for the cross-cutting guidance the fixes reference.
Step 2.5: Localize a Generic Finding (only when the finding is not actionable)
Most findings already name the offending object in .blockPath. But some are
generic — the message is vague (e.g. a bare SLDV:Compatibility:Generic)
and .blockPath points at a container (the model root or a SubSystem)
rather than a leaf block. A generic, container-scoped finding does not tell you
what to fix. When (and only when) you hit one, narrow it:
% project_path = the skill's scripts/ folder
loc = sldv_localize_incompatibility('<model_or_atomic_subsystem_path>');
This drills the hierarchy, scoping sldvcompat onto each atomic subsystem,
atomic Stateflow subchart, and referenced model, and keeps descending into
whichever children are individually incompatible. It descends through
virtual subsystems (which sldvcompat cannot scope) to the next atomic
boundary. It returns:
loc.culprits— one entry per deepest responsible scope (the narrowest subsystem/subchart/model that is incompatible while none of its scopable children are), each with that scope's.path,.kind, and.findings.loc.drilled— true if the search narrowed below the scope you passed in.loc.searched— every scope it scopedsldvcompatonto (for transparency).
Then match the rule (Step 2) against each culprit's .findings, which are now
scoped to the responsible subsystem instead of the whole model. If
loc.culprits still points at a scope whose own findings are generic (the
issue is that scope's wiring/config, not a nested block), inspect that scope
directly with model_read / model_query_params.
Do not run localization for findings that already name a leaf block — use those directly. Localization is only for the generic, container-scoped case.
Step 3: Apply the Fix
Based on the matched rule:
- For block-level fixes: use
model_editonresult.copyName. This is the default — all block edits (replacement, stubbing, port matching, rewiring
Truncated for display — read the full file on GitHub.
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From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
