From 39912cc0efce47af350523a1bb8644fb2375e609 Mon Sep 17 00:00:00 2001
From: Olivier Cots <olivier.cots@irit.fr>
Date: Tue, 21 Apr 2026 13:34:16 +0200
Subject: [PATCH 1/2] Update for CTModels v0.9.15-beta API changes

- Rename dim_*_constraints_box to dim_dual_*_constraints_box
- Add new predicates: has_variable, is_variable, has_control, is_control_free,
  has_abstract_definition, is_abstractly_defined, is_nonautonomous, is_nonvariable
- Add expression() function to extract Expr from AbstractDefinition
- Update manual-model.md: definition changes, new Model predicates section,
  box constraint tuple structure (added aliases field)
- Update manual-abstract.md: document box constraint intersection/deduplication
- Update manual-solution.md: document signed multiplier convention,
  add dim_dual_*_constraints_box and dim_{path,boundary}_constraints_nl
- Update api/public.md: function list
- Update test/README.md and .windsurf/rules/testing.md: add jtest convenience
  command and tee pattern for test output capture
---
 Project.toml                         |   2 +-
 docs/Project.toml                    |   4 +-
 docs/make.jl                         |   2 +-
 docs/src/api/public.md               |  15 +++-
 docs/src/assets/Manifest.toml        | 100 +++++++++++++--------------
 docs/src/assets/Project.toml         |   4 +-
 docs/src/manual-abstract.md          |  45 ++++++++++++
 docs/src/manual-model.md             |  84 ++++++++++++++++++++--
 docs/src/manual-solution.md          |  75 +++++++++++++++++---
 src/imports/ctmodels.jl              |  15 +++-
 test/README.md                       |  29 ++++++--
 test/suite/reexport/test_ctmodels.jl |  15 +++-
 12 files changed, 304 insertions(+), 86 deletions(-)

diff --git a/Project.toml b/Project.toml
index f6a85f750..8b75d1343 100644
--- a/Project.toml
+++ b/Project.toml
@@ -27,7 +27,7 @@ BenchmarkTools = "1"
 CTBase = "0.18"
 CTDirect = "1"
 CTFlows = "0.8"
-CTModels = "0.9, 0.10"
+CTModels = "0.10"
 CTParser = "0.8"
 CTSolvers = "0.4"
 CUDA = "5"
diff --git a/docs/Project.toml b/docs/Project.toml
index 21edf0f91..0310baf65 100644
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -31,7 +31,7 @@ ADNLPModels = "0.8"
 CTBase = "0.18"
 CTDirect = "1"
 CTFlows = "0.8"
-CTModels = "0.9"
+CTModels = "0.10"
 CTParser = "0.8"
 CTSolvers = "0.4"
 CUDA = "5"
@@ -53,4 +53,4 @@ NonlinearSolve = "4"
 OrdinaryDiffEq = "6"
 Plots = "1"
 UnoSolver = "0.3"
-julia = "1.10"
\ No newline at end of file
+julia = "1.10"
diff --git a/docs/make.jl b/docs/make.jl
index b26d47cbd..764bcac33 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -153,7 +153,7 @@ cp(
 Draft = false
 ```
 =#
-draft = false  # Draft mode: if true, @example blocks in markdown are not executed
+draft = true  # Draft mode: if true, @example blocks in markdown are not executed
 
 # ═══════════════════════════════════════════════════════════════════════════════
 # Load extensions
diff --git a/docs/src/api/public.md b/docs/src/api/public.md
index 85709239f..50d35ed6f 100644
--- a/docs/src/api/public.md
+++ b/docs/src/api/public.md
@@ -55,12 +55,13 @@ costate
 criterion
 @def
 definition
+expression
 describe
 dim_boundary_constraints_nl
-dim_control_constraints_box
+dim_dual_control_constraints_box
+dim_dual_state_constraints_box
+dim_dual_variable_constraints_box
 dim_path_constraints_nl
-dim_state_constraints_box
-dim_variable_constraints_box
 dimension
 discretize
 dual
@@ -76,6 +77,11 @@ has_free_initial_time
 has_lagrange_cost
 has_mayer_cost
 has_option
+has_variable
+is_variable
+has_control
+is_control_free
+has_abstract_definition
 id
 import_ocp_solution
 index
@@ -86,6 +92,9 @@ initial_time_name
 is_autonomous
 is_computed
 is_default
+is_abstractly_defined
+is_nonautonomous
+is_nonvariable
 is_empty
 is_empty_time_grid
 is_final_time_fixed
diff --git a/docs/src/assets/Manifest.toml b/docs/src/assets/Manifest.toml
index a727d2292..b74944f0c 100644
--- a/docs/src/assets/Manifest.toml
+++ b/docs/src/assets/Manifest.toml
@@ -2,7 +2,7 @@
 
 julia_version = "1.12.5"
 manifest_format = "2.0"
-project_hash = "b0d8b73e668b2a300e75cec748fa7e05cad42a09"
+project_hash = "505b0cb4420cde5e120adb378ac9d10f3e75d872"
 
 [[deps.ADNLPModels]]
 deps = ["ADTypes", "ForwardDiff", "LinearAlgebra", "NLPModels", "Requires", "ReverseDiff", "SparseArrays", "SparseConnectivityTracer", "SparseMatrixColorings"]
@@ -101,9 +101,9 @@ version = "1.1.2"
 
 [[deps.ArrayInterface]]
 deps = ["Adapt", "LinearAlgebra"]
-git-tree-sha1 = "78b3a7a536b4b0a747a0f296ea77091ca0a9f9a3"
+git-tree-sha1 = "54f895554d05c83e3dd59f6a396671dae8999573"
 uuid = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
-version = "7.23.0"
+version = "7.24.0"
 
     [deps.ArrayInterface.extensions]
     ArrayInterfaceAMDGPUExt = "AMDGPU"
@@ -226,15 +226,15 @@ version = "0.18.7"
 
 [[deps.CTDirect]]
 deps = ["ADNLPModels", "CTModels", "CTSolvers", "DocStringExtensions", "ExaModels", "SolverCore", "SparseArrays", "SparseConnectivityTracer"]
-git-tree-sha1 = "a4d812f60412f47bf29e685a921d0d675f581d55"
+git-tree-sha1 = "21b9ea456769176849cdcbd20f04a017526daa76"
 uuid = "790bbbee-bee9-49ee-8912-a9de031322d5"
-version = "1.0.7-beta"
+version = "1.0.10"
 
 [[deps.CTFlows]]
 deps = ["CTBase", "CTModels", "DocStringExtensions", "ForwardDiff", "LinearAlgebra", "MLStyle", "MacroTools"]
-git-tree-sha1 = "919b47b3c8a9c2fc2c8606ee8fce826bef6d36b2"
+git-tree-sha1 = "b555d36b668dc149334a50b835df91a301bad8ac"
 uuid = "1c39547c-7794-42f7-af83-d98194f657c2"
-version = "0.8.23"
+version = "0.8.25"
 weakdeps = ["OrdinaryDiffEq"]
 
     [deps.CTFlows.extensions]
@@ -242,9 +242,9 @@ weakdeps = ["OrdinaryDiffEq"]
 
 [[deps.CTModels]]
 deps = ["CTBase", "DocStringExtensions", "LinearAlgebra", "MLStyle", "MacroTools", "OrderedCollections", "Parameters", "RecipesBase"]
-git-tree-sha1 = "6f8db9437164a844f3dde8f239a82b087d6b6336"
+git-tree-sha1 = "a183ce43a9f912a4b62a8af88ba1415c6e2b1521"
 uuid = "34c4fa32-2049-4079-8329-de33c2a22e2d"
-version = "0.9.14"
+version = "0.10.0"
 weakdeps = ["JLD2", "JSON3", "Plots"]
 
     [deps.CTModels.extensions]
@@ -254,15 +254,15 @@ weakdeps = ["JLD2", "JSON3", "Plots"]
 
 [[deps.CTParser]]
 deps = ["CTBase", "DocStringExtensions", "MLStyle", "OrderedCollections", "Parameters", "Unicode"]
-git-tree-sha1 = "0a57111b2d95d6272bb76f4f6f7c4fee1e40ce82"
+git-tree-sha1 = "67c193f4f1e5167123b917bbbdb26947757ed4b0"
 uuid = "32681960-a1b1-40db-9bff-a1ca817385d1"
-version = "0.8.13"
+version = "0.8.14"
 
 [[deps.CTSolvers]]
 deps = ["ADNLPModels", "CTBase", "CTModels", "CommonSolve", "DocStringExtensions", "ExaModels", "KernelAbstractions", "NLPModels", "SolverCore"]
-git-tree-sha1 = "22c283a24bd1b51cf2795074a6ec3fe0bff78adb"
+git-tree-sha1 = "cc69a7ad7e18ca089e0168c6b361ee1e50a3cfc2"
 uuid = "d3e8d392-8e4b-4d9b-8e92-d7d4e3650ef6"
-version = "0.4.15"
+version = "0.4.16"
 
     [deps.CTSolvers.extensions]
     CTSolversCUDA = "CUDA"
@@ -306,15 +306,15 @@ version = "5.11.0"
 
 [[deps.CUDA_Compiler_jll]]
 deps = ["Artifacts", "CUDA_Driver_jll", "CUDA_Runtime_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"]
-git-tree-sha1 = "8c19e97de5b7574672e4a7a3abd55714ad66d59a"
+git-tree-sha1 = "b977706846cb0a75d3842a1fed810ab2e6ab2f94"
 uuid = "d1e2174e-dfdc-576e-b43e-73b79eb1aca8"
-version = "0.4.2+0"
+version = "0.4.3+0"
 
 [[deps.CUDA_Driver_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "TOML"]
-git-tree-sha1 = "061f39cc84e99928830aa1005d79f7e99097ba28"
+git-tree-sha1 = "3b759ec65ac87ad192c2925114fa5c126657a5bd"
 uuid = "4ee394cb-3365-5eb0-8335-949819d2adfc"
-version = "13.2.0+0"
+version = "13.2.1+0"
 
 [[deps.CUDA_Runtime_Discovery]]
 deps = ["Libdl"]
@@ -324,9 +324,9 @@ version = "1.0.0"
 
 [[deps.CUDA_Runtime_jll]]
 deps = ["Artifacts", "CUDA_Driver_jll", "JLLWrappers", "LazyArtifacts", "Libdl", "TOML"]
-git-tree-sha1 = "af17d37b5b8b4d7525f8902eba1ef6141a9a7d3b"
+git-tree-sha1 = "c0314d9fb0ebd00e404feba4c3fbc04c9975abc1"
 uuid = "76a88914-d11a-5bdc-97e0-2f5a05c973a2"
-version = "0.21.0+0"
+version = "0.21.0+1"
 
 [[deps.CUDSS]]
 deps = ["CEnum", "CUDA", "CUDA_Runtime_Discovery", "CUDSS_jll", "GPUToolbox", "LinearAlgebra", "SparseArrays"]
@@ -539,10 +539,10 @@ uuid = "8bb1440f-4735-579b-a4ab-409b98df4dab"
 version = "1.9.1"
 
 [[deps.DiffEqBase]]
-deps = ["ArrayInterface", "BracketingNonlinearSolve", "ConcreteStructs", "DocStringExtensions", "FastBroadcast", "FastClosures", "FastPower", "FunctionWrappers", "FunctionWrappersWrappers", "LinearAlgebra", "Logging", "Markdown", "MuladdMacro", "PrecompileTools", "Printf", "RecursiveArrayTools", "Reexport", "SciMLBase", "SciMLOperators", "SciMLStructures", "Setfield", "Static", "StaticArraysCore", "SymbolicIndexingInterface", "TruncatedStacktraces"]
-git-tree-sha1 = "87e2ad6d4ae98505218e2f97cafcfa296dc97d37"
+deps = ["ArrayInterface", "BracketingNonlinearSolve", "ConcreteStructs", "DocStringExtensions", "FastBroadcast", "FastClosures", "FastPower", "FunctionWrappers", "FunctionWrappersWrappers", "LinearAlgebra", "Logging", "Markdown", "MuladdMacro", "PrecompileTools", "Printf", "RecursiveArrayTools", "Reexport", "SciMLBase", "SciMLLogging", "SciMLOperators", "SciMLStructures", "Setfield", "Static", "StaticArraysCore", "SymbolicIndexingInterface", "TruncatedStacktraces"]
+git-tree-sha1 = "9d333db14895e8c7d4857ed228eb1e72d3b302ec"
 uuid = "2b5f629d-d688-5b77-993f-72d75c75574e"
-version = "6.216.0"
+version = "6.218.0"
 
     [deps.DiffEqBase.extensions]
     DiffEqBaseCUDAExt = "CUDA"
@@ -859,9 +859,9 @@ version = "1.16.0"
 
 [[deps.FiniteDiff]]
 deps = ["ArrayInterface", "LinearAlgebra", "Setfield"]
-git-tree-sha1 = "9340ca07ca27093ff68418b7558ca37b05f8aeb1"
+git-tree-sha1 = "73e879af0e767bd6dfade7c5b09d7b05657a8284"
 uuid = "6a86dc24-6348-571c-b903-95158fe2bd41"
-version = "2.29.0"
+version = "2.30.0"
 
     [deps.FiniteDiff.extensions]
     FiniteDiffBandedMatricesExt = "BandedMatrices"
@@ -921,9 +921,9 @@ version = "1.1.3"
 
 [[deps.FunctionWrappersWrappers]]
 deps = ["FunctionWrappers", "PrecompileTools", "TruncatedStacktraces"]
-git-tree-sha1 = "3e13d0b39d117a03d3fb5c88a039e94787a37fcb"
+git-tree-sha1 = "ce6762f8f0e7542534f01523ae051e625cbf0468"
 uuid = "77dc65aa-8811-40c2-897b-53d922fa7daf"
-version = "1.4.0"
+version = "1.5.0"
 
     [deps.FunctionWrappersWrappers.extensions]
     FunctionWrappersWrappersEnzymeExt = ["Enzyme", "EnzymeCore"]
@@ -947,9 +947,9 @@ version = "3.4.1+1"
 
 [[deps.GPUArrays]]
 deps = ["Adapt", "GPUArraysCore", "KernelAbstractions", "LLVM", "LinearAlgebra", "Printf", "Random", "Reexport", "ScopedValues", "Serialization", "SparseArrays", "Statistics"]
-git-tree-sha1 = "6487601563e4a1d1dab796e88b4548bf5544209e"
+git-tree-sha1 = "99ebe50e3b6537de14d43f1c88963a2e13eff3b7"
 uuid = "0c68f7d7-f131-5f86-a1c3-88cf8149b2d7"
-version = "11.4.1"
+version = "11.5.1"
 weakdeps = ["JLD2"]
 
     [deps.GPUArrays.extensions]
@@ -1419,9 +1419,9 @@ version = "2.42.0+0"
 
 [[deps.LineSearch]]
 deps = ["ADTypes", "CommonSolve", "ConcreteStructs", "FastClosures", "LinearAlgebra", "MaybeInplace", "PrecompileTools", "SciMLBase", "SciMLJacobianOperators", "StaticArraysCore"]
-git-tree-sha1 = "69da095e4c24ed3c4a168bb76dc9c620a6d7239c"
+git-tree-sha1 = "25454bc65c3eec4656cbe201c3d9336af49178c7"
 uuid = "87fe0de2-c867-4266-b59a-2f0a94fc965b"
-version = "0.1.7"
+version = "0.1.8"
 weakdeps = ["LineSearches"]
 
     [deps.LineSearch.extensions]
@@ -1587,9 +1587,9 @@ version = "0.5.16"
 
 [[deps.MadNCL]]
 deps = ["Atomix", "KernelAbstractions", "LinearAlgebra", "MadNLP", "NLPModels", "Printf", "Random", "SparseArrays"]
-git-tree-sha1 = "8cdb50494fa73f9af44aabadfac51d39413a707e"
+git-tree-sha1 = "cbb996d397b63f551bfbeaabfae4af5640326ab2"
 uuid = "434a0bcb-5a7c-42b2-a9d3-9e3f760e7af0"
-version = "0.2.1"
+version = "0.2.2"
 weakdeps = ["MadNLPGPU"]
 
     [deps.MadNCL.extensions]
@@ -1761,9 +1761,9 @@ version = "1.3.0"
 
 [[deps.NonlinearSolve]]
 deps = ["ADTypes", "ArrayInterface", "BracketingNonlinearSolve", "CommonSolve", "ConcreteStructs", "DifferentiationInterface", "FastClosures", "FiniteDiff", "ForwardDiff", "LineSearch", "LinearAlgebra", "LinearSolve", "NonlinearSolveBase", "NonlinearSolveFirstOrder", "NonlinearSolveQuasiNewton", "NonlinearSolveSpectralMethods", "PrecompileTools", "Preferences", "Reexport", "SciMLBase", "SciMLLogging", "Setfield", "SimpleNonlinearSolve", "StaticArraysCore", "SymbolicIndexingInterface"]
-git-tree-sha1 = "e88921859836899abe94d08ea0fd42137067280e"
+git-tree-sha1 = "a2db21951cd1cd46a3ef8ba4bbfc84ddc9a5b3fb"
 uuid = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
-version = "4.17.1"
+version = "4.18.0"
 
     [deps.NonlinearSolve.extensions]
     NonlinearSolveFastLevenbergMarquardtExt = "FastLevenbergMarquardt"
@@ -1794,9 +1794,9 @@ version = "4.17.1"
 
 [[deps.NonlinearSolveBase]]
 deps = ["ADTypes", "Adapt", "ArrayInterface", "CommonSolve", "Compat", "ConcreteStructs", "DifferentiationInterface", "EnzymeCore", "FastClosures", "FunctionWrappers", "FunctionWrappersWrappers", "LinearAlgebra", "LogExpFunctions", "Markdown", "MaybeInplace", "PreallocationTools", "PrecompileTools", "Preferences", "Printf", "RecursiveArrayTools", "SciMLBase", "SciMLJacobianOperators", "SciMLLogging", "SciMLOperators", "SciMLStructures", "Setfield", "StaticArraysCore", "SymbolicIndexingInterface", "TimerOutputs"]
-git-tree-sha1 = "5bd437a82d7e5eee049a1b488dedc726f0b84bd4"
+git-tree-sha1 = "a19a5df29ef2b197499fc631fa1a59385ae15262"
 uuid = "be0214bd-f91f-a760-ac4e-3421ce2b2da0"
-version = "2.24.0"
+version = "2.25.0"
 
     [deps.NonlinearSolveBase.extensions]
     NonlinearSolveBaseBandedMatricesExt = "BandedMatrices"
@@ -1895,12 +1895,6 @@ git-tree-sha1 = "1346c9208249809840c91b26703912dff463d335"
 uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
 version = "0.5.6+0"
 
-[[deps.OptimalControl]]
-deps = ["ADNLPModels", "CTBase", "CTDirect", "CTFlows", "CTModels", "CTParser", "CTSolvers", "CommonSolve", "DocStringExtensions", "Documenter", "ExaModels", "LinearAlgebra", "NLPModels", "RecipesBase", "Reexport", "SolverCore"]
-git-tree-sha1 = "8490d74ca7e2dbff82210d08b1cf557168d497e4"
-uuid = "5f98b655-cc9a-415a-b60e-744165666948"
-version = "2.0.1"
-
 [[deps.Opus_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
 git-tree-sha1 = "e2bb57a313a74b8104064b7efd01406c0a50d2ff"
@@ -1931,10 +1925,10 @@ uuid = "6ad6398a-0878-4a85-9266-38940aa047c8"
 version = "1.26.0"
 
 [[deps.OrdinaryDiffEqCore]]
-deps = ["ADTypes", "Accessors", "Adapt", "ArrayInterface", "ConcreteStructs", "DataStructures", "DiffEqBase", "DocStringExtensions", "EnumX", "EnzymeCore", "FastBroadcast", "FastClosures", "FastPower", "FunctionWrappersWrappers", "InteractiveUtils", "LinearAlgebra", "Logging", "MacroTools", "MuladdMacro", "Polyester", "PrecompileTools", "Preferences", "Random", "RecursiveArrayTools", "Reexport", "SciMLBase", "SciMLLogging", "SciMLOperators", "SciMLStructures", "Static", "StaticArraysCore", "SymbolicIndexingInterface", "TruncatedStacktraces"]
-git-tree-sha1 = "e81202ab680b4649ea2cb63560b9e57833540cfa"
+deps = ["ADTypes", "Accessors", "Adapt", "ArrayInterface", "ConcreteStructs", "DataStructures", "DiffEqBase", "DocStringExtensions", "EnumX", "EnzymeCore", "FastBroadcast", "FastClosures", "FastPower", "FunctionWrappersWrappers", "InteractiveUtils", "LinearAlgebra", "Logging", "MacroTools", "MuladdMacro", "Polyester", "PrecompileTools", "Preferences", "Random", "RecursiveArrayTools", "Reexport", "SciMLBase", "SciMLLogging", "SciMLOperators", "SciMLStructures", "Static", "SymbolicIndexingInterface", "TruncatedStacktraces"]
+git-tree-sha1 = "2b55a12e68d2e9eb9f06c00cde116356c2d3823d"
 uuid = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
-version = "3.31.0"
+version = "3.33.0"
 
     [deps.OrdinaryDiffEqCore.extensions]
     OrdinaryDiffEqCoreMooncakeExt = "Mooncake"
@@ -2088,9 +2082,9 @@ version = "1.14.0"
 
 [[deps.OrdinaryDiffEqStabilizedRK]]
 deps = ["DiffEqBase", "FastBroadcast", "MuladdMacro", "OrdinaryDiffEqCore", "RecursiveArrayTools", "Reexport", "SciMLBase", "StaticArraysCore"]
-git-tree-sha1 = "bb33a312858b1e6663099f231323a78b7bb00eb3"
+git-tree-sha1 = "764e11fb6a26ee8f2d2d10778d531fd708f35d28"
 uuid = "358294b1-0aab-51c3-aafe-ad5ab194a2ad"
-version = "1.11.0"
+version = "1.11.1"
 
 [[deps.OrdinaryDiffEqSymplecticRK]]
 deps = ["DiffEqBase", "FastBroadcast", "MuladdMacro", "OrdinaryDiffEqCore", "Polyester", "RecursiveArrayTools", "Reexport", "SciMLBase"]
@@ -2117,9 +2111,9 @@ version = "10.44.0+1"
 
 [[deps.Pango_jll]]
 deps = ["Artifacts", "Cairo_jll", "Fontconfig_jll", "FreeType2_jll", "FriBidi_jll", "Glib_jll", "HarfBuzz_jll", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "0662b083e11420952f2e62e17eddae7fc07d5997"
+git-tree-sha1 = "58e5ed5e386e156bd93e86b305ebd21ac63d2d04"
 uuid = "36c8627f-9965-5494-a995-c6b170f724f3"
-version = "1.57.0+0"
+version = "1.57.1+0"
 
 [[deps.Parameters]]
 deps = ["OrderedCollections", "UnPack"]
@@ -3059,9 +3053,9 @@ version = "0.61.1+0"
 
 [[deps.libaom_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl"]
-git-tree-sha1 = "371cc681c00a3ccc3fbc5c0fb91f58ba9bec1ecf"
+git-tree-sha1 = "850b06095ee71f0135d644ffd8a52850699581ed"
 uuid = "a4ae2306-e953-59d6-aa16-d00cac43593b"
-version = "3.13.1+0"
+version = "3.13.3+0"
 
 [[deps.libass_jll]]
 deps = ["Artifacts", "Bzip2_jll", "FreeType2_jll", "FriBidi_jll", "HarfBuzz_jll", "JLLWrappers", "Libdl", "Zlib_jll"]
@@ -3106,9 +3100,9 @@ version = "1.28.1+0"
 
 [[deps.libpng_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Zlib_jll"]
-git-tree-sha1 = "45a20bd63e4fafc84ed9e4ac4ba15c8a7deff803"
+git-tree-sha1 = "e51150d5ab85cee6fc36726850f0e627ad2e4aba"
 uuid = "b53b4c65-9356-5827-b1ea-8c7a1a84506f"
-version = "1.6.57+0"
+version = "1.6.58+0"
 
 [[deps.libva_jll]]
 deps = ["Artifacts", "JLLWrappers", "Libdl", "Xorg_libX11_jll", "Xorg_libXext_jll", "Xorg_libXfixes_jll", "libdrm_jll"]
diff --git a/docs/src/assets/Project.toml b/docs/src/assets/Project.toml
index 21edf0f91..0310baf65 100644
--- a/docs/src/assets/Project.toml
+++ b/docs/src/assets/Project.toml
@@ -31,7 +31,7 @@ ADNLPModels = "0.8"
 CTBase = "0.18"
 CTDirect = "1"
 CTFlows = "0.8"
-CTModels = "0.9"
+CTModels = "0.10"
 CTParser = "0.8"
 CTSolvers = "0.4"
 CUDA = "5"
@@ -53,4 +53,4 @@ NonlinearSolve = "4"
 OrdinaryDiffEq = "6"
 Plots = "1"
 UnoSolver = "0.3"
-julia = "1.10"
\ No newline at end of file
+julia = "1.10"
diff --git a/docs/src/manual-abstract.md b/docs/src/manual-abstract.md
index 93454693a..2df6b9e64 100644
--- a/docs/src/manual-abstract.md
+++ b/docs/src/manual-abstract.md
@@ -311,6 +311,9 @@ In the example below, there are
 end
 ```
 
+!!! note "Duplicate box constraints"
+    If the same scalar component of the state, control or variable appears in several **box** constraints (linear range constraints), the effective bounds are the **intersection** of all declared bounds: the effective lower bound is the maximum of declared lower bounds, and the effective upper bound is the minimum of declared upper bounds. A warning is emitted, and an error is thrown if the resulting interval is empty. See [Duplicate box constraints](@ref manual-abstract-box-dedup) below.
+
 !!! note
     Symbols like `<=` or `>=` are also authorised:
 
@@ -386,6 +389,48 @@ end
     end
     ```
 
+### [Duplicate box constraints](@id manual-abstract-box-dedup)
+
+**Box constraints** are linear range constraints on a single scalar component of the state, control or variable — that is, constraints of the form `lb ≤ x_i(t) ≤ ub`, `u_i(t) ≤ ub`, `v_i ≥ lb`, etc. (nonlinear path constraints are *not* concerned by this section).
+
+When the **same scalar component** is targeted by several box-constraint declarations, OptimalControl does **not** keep them as separate constraints. Instead, it merges them by taking the **intersection** of all declared bounds:
+
+- the effective lower bound is `max` of all declared lower bounds,
+- the effective upper bound is `min` of all declared upper bounds,
+- a single `@warn` is emitted per duplicated component, listing every contributing label,
+- all labels that declared the component are preserved as **aliases** (accessible via the `aliases` field of [`state_constraints_box`](@ref), [`control_constraints_box`](@ref) and [`variable_constraints_box`](@ref); see the [manual on the OCP object](@ref manual-model)),
+- if the intersection is empty (`max(lbs) > min(ubs)`), an `IncorrectArgument` exception is thrown.
+
+For instance,
+
+```julia
+@def begin
+    t ∈ [0, 1], time
+    x = (q, v) ∈ R², state
+    u ∈ R, control
+    0 ≤ q(t) ≤ 2, (q_wide)
+    1 ≤ q(t) ≤ 3, (q_tight)
+    ẋ(t) == [v(t), u(t)]
+    ...
+end
+```
+
+yields the effective constraint `1 ≤ q(t) ≤ 2`, with `aliases = [:q_wide, :q_tight]` for that component, and a warning reporting both labels.
+
+Conversely, the following declares an empty feasible set and raises an error at build time:
+
+```julia
+@def begin
+    t ∈ [0, 1], time
+    x = (q, v) ∈ R², state
+    u ∈ R, control
+    0 ≤ q(t) ≤ 1, (low)
+    2 ≤ q(t) ≤ 3, (high) # max(lbs)=2 > min(ubs)=1 ⇒ IncorrectArgument
+    ẋ(t) == [v(t), u(t)]
+    ...
+end
+```
+
 ## [Mayer cost](@id manual-abstract-mayer)
 
 ```julia
diff --git a/docs/src/manual-model.md b/docs/src/manual-model.md
index 43eb3173d..d7a428651 100644
--- a/docs/src/manual-model.md
+++ b/docs/src/manual-model.md
@@ -1,5 +1,9 @@
 # [The optimal control problem object: structure and usage](@id manual-model)
 
+```@meta
+Draft = false
+```
+
 In this manual, we'll first recall the **main functionalities** you can use when working with an optimal control problem (OCP). This includes essential operations like:
 
 * **Solving an OCP**: How to find the optimal solution for your defined problem.
@@ -281,11 +285,12 @@ state_constraints_box(ocp)  # returns box constraints if any
 ```
 
 !!! note "Tuple structure"
-    The returned tuple has the structure `(lb, indices, ub, labels)` where:
+    The returned tuple has the structure `(lb, indices, ub, labels, aliases)` where:
     - `lb`: vector of lower bounds
     - `indices`: vector of component indices (1-based)
     - `ub`: vector of upper bounds
     - `labels`: vector of constraint labels
+    - `aliases`: vector of vectors containing all labels that declared each component
 
 Get the dimension of state box constraints:
 
@@ -332,11 +337,12 @@ control_constraints_box(ocp)  # returns box constraints if any
 ```
 
 !!! note "Tuple structure"
-    The returned tuple has the structure `(lb, indices, ub, labels)` where:
+    The returned tuple has the structure `(lb, indices, ub, labels, aliases)` where:
     - `lb`: vector of lower bounds
     - `indices`: vector of component indices (1-based)
     - `ub`: vector of upper bounds
     - `labels`: vector of constraint labels
+    - `aliases`: vector of vectors containing all labels that declared each component
 
 Get the dimension of control box constraints:
 
@@ -383,11 +389,12 @@ variable_constraints_box(ocp)  # returns box constraints if any
 ```
 
 !!! note "Tuple structure"
-    The returned tuple has the structure `(lb, indices, ub, labels)` where:
+    The returned tuple has the structure `(lb, indices, ub, labels, aliases)` where:
     - `lb`: vector of lower bounds
     - `indices`: vector of component indices (1-based)
     - `ub`: vector of upper bounds
     - `labels`: vector of constraint labels
+    - `aliases`: vector of vectors containing all labels that declared each component
 
 Get the dimension of variable box constraints:
 
@@ -613,9 +620,20 @@ dim_boundary_constraints_nl(ocp)  # number of nonlinear boundary constraints
 Get the problem definition as a string:
 
 ```@example main
-definition(ocp)  # returns the OCP definition
+definition(ocp)  # returns the OCP definition as AbstractDefinition
 ```
 
+To extract the expression from the definition, use:
+
+```@example main
+expr = expression(ocp)  # returns the Expr from the definition
+nothing # hide
+```
+
+!!! note
+
+    The definition is optional and can be `EmptyDefinition`. Use `has_abstract_definition(ocp)` to check if a definition is present.
+
 ### [Time dependence](@id manual-model-time-dependence)
 
 Optimal control problems can be **autonomous** or **non-autonomous**. In an autonomous problem, neither the dynamics nor the Lagrange cost explicitly depends on the time variable.
@@ -658,3 +676,61 @@ ocp = @def begin
 end
 is_autonomous(ocp)
 ```
+
+### Model predicates
+
+Check various properties of the optimal control problem model.
+
+#### Variable and control presence
+
+Check if the problem has optimization variables or control input:
+
+```@example main
+has_variable(ocp)  # true if problem has optimization variables
+```
+
+```@example main
+has_control(ocp)  # true if problem has control input
+```
+
+!!! note "Variant methods"
+
+    Alternative methods are also available:
+    - `is_variable(ocp)` ≡ `has_variable(ocp)`
+    - `is_nonvariable(ocp)` ≡ `!has_variable(ocp)`
+    - `is_control_free(ocp)` ≡ `!has_control(ocp)`
+
+#### Definition presence
+
+Check if the problem has an abstract definition:
+
+```@example main
+has_abstract_definition(ocp)  # true if definition is present (not EmptyDefinition)
+```
+
+!!! note "Variant methods"
+
+    - `is_abstractly_defined(ocp)` ≡ `has_abstract_definition(ocp)`
+
+#### Time dependence
+
+Check if the problem is non-autonomous (time-dependent):
+
+```@example main
+is_nonautonomous(ocp)  # true if dynamics or cost depend on time
+```
+
+!!! note "Variant methods"
+
+    - `is_nonautonomous(ocp)` ≡ `!is_autonomous(ocp)`
+
+#### [Summary table](@id manual-model-summary-predicates)
+
+| Method | Returns | Description |
+| -------- | --------- | ------------- |
+| `has_variable(ocp)` | `Bool` | True if problem has optimization variables |
+| `has_control(ocp)` | `Bool` | True if problem has control input |
+| `has_abstract_definition(ocp)` | `Bool` | True if definition is present |
+| `is_abstractly_defined(ocp)` | `Bool` | Alias for has_abstract_definition |
+| `is_nonautonomous(ocp)` | `Bool` | True if time-dependent |
+| `is_nonvariable(ocp)` | `Bool` | True if no optimization variables |
diff --git a/docs/src/manual-solution.md b/docs/src/manual-solution.md
index 2714f562d..e537b463b 100644
--- a/docs/src/manual-solution.md
+++ b/docs/src/manual-solution.md
@@ -1,5 +1,9 @@
 # [The optimal control solution object: structure and usage](@id manual-solution)
 
+```@meta
+Draft = false
+```
+
 In this manual, we'll first recall the **main functionalities** you can use when working with a solution of an optimal control problem. This includes essential operations like:
 
 * **Plotting a solution**: How to plot the optimal solution for your defined problem.
@@ -273,6 +277,28 @@ plot(time_grid(sol), μ_u)
 plot(time_grid(sol), μ_v)
 ```
 
+!!! note "Signed multiplier convention"
+
+    In all cases, `dual(sol, ocp, :label)` returns a **signed multiplier** `μ` (scalar, vector, or function of time, depending on the constraint type). The sign convention is, component-wise:
+
+    - `μ > 0` ⇒ the lower-side constraint is active (e.g. `lb ≤ ...`),
+    - `μ < 0` ⇒ the upper-side constraint is active (e.g. `... ≤ ub`),
+    - `μ = 0` ⇒ the constraint is inactive (or the component is never constrained).
+
+    For **nonlinear path and boundary constraints**, the solver already returns a signed multiplier natively; CTModels simply forwards it via `path_constraints_dual(sol)` / `boundary_constraints_dual(sol)`.
+
+    For **box constraints** (state/control/variable components), the solver stores lower- and upper-bound multipliers *separately as non-negative quantities*. CTModels combines them into the signed multiplier explicitly:
+
+    ```
+    μ = μ_lb − μ_ub
+    ```
+
+    computed per targeted primal component. This is the value returned by `dual(sol, ocp, :label)` for a box-constraint label.
+
+    Rationale for box constraints: after intersection of duplicate box declarations, the solver only sees a single effective bound per component, hence a single signed multiplier per component. If several labels target the same component, each label returns the **same** per-component multiplier (via the `aliases` mechanism; see the [OCP manual](@ref manual-model) and [Duplicate box constraints](@ref manual-abstract-box-dedup)).
+
+    The raw non-negative `*_lb_dual(sol)` / `*_ub_dual(sol)` accessors (see below) remain available if the unsigned components are needed separately.
+
 #### Box constraint duals
 
 Get dual variables for box constraints on state, control, and variable:
@@ -301,6 +327,22 @@ variable_constraints_lb_dual(sol)  # lower bound duals for variable
 variable_constraints_ub_dual(sol)  # upper bound duals for variable
 ```
 
+#### Box constraint dual dimensions
+
+Get the dimensions of the box-constraint dual vectors (one entry per primal component that is box-constrained):
+
+```@example main
+dim_dual_state_constraints_box(sol)  # dimension of state box constraint duals
+```
+
+```@example main
+dim_dual_control_constraints_box(sol)  # dimension of control box constraint duals
+```
+
+```@example main
+dim_dual_variable_constraints_box(sol)  # dimension of variable box constraint duals
+```
+
 #### Nonlinear constraint duals
 
 Get dual variables for nonlinear path and boundary constraints:
@@ -313,19 +355,34 @@ path_constraints_dual(sol)  # duals for nonlinear path constraints
 boundary_constraints_dual(sol)  # duals for nonlinear boundary constraints
 ```
 
+Get the dimensions of the nonlinear constraints:
+
+```@example main
+dim_path_constraints_nl(sol)  # number of nonlinear path constraints
+```
+
+```@example main
+dim_boundary_constraints_nl(sol)  # number of nonlinear boundary constraints
+```
+
 #### Summary table
 
 | Method | Returns | Description |
 | -------- | --------- | ------------- |
-| `dual(sol, ocp, label)` | `Real` or `Function` | Dual for labeled constraint |
-| `state_constraints_lb_dual(sol)` | Dual values | State lower bound duals |
-| `state_constraints_ub_dual(sol)` | Dual values | State upper bound duals |
-| `control_constraints_lb_dual(sol)` | Dual values | Control lower bound duals |
-| `control_constraints_ub_dual(sol)` | Dual values | Control upper bound duals |
-| `variable_constraints_lb_dual(sol)` | Dual values | Variable lower bound duals |
-| `variable_constraints_ub_dual(sol)` | Dual values | Variable upper bound duals |
-| `path_constraints_dual(sol)` | Dual values | Nonlinear path constraint duals |
-| `boundary_constraints_dual(sol)` | Dual values | Nonlinear boundary constraint duals |
+| `dual(sol, ocp, label)` | `Real` or `Function` | Signed dual for labeled constraint |
+| `state_constraints_lb_dual(sol)` | Dual values | State lower bound duals (non-negative) |
+| `state_constraints_ub_dual(sol)` | Dual values | State upper bound duals (non-negative) |
+| `control_constraints_lb_dual(sol)` | Dual values | Control lower bound duals (non-negative) |
+| `control_constraints_ub_dual(sol)` | Dual values | Control upper bound duals (non-negative) |
+| `variable_constraints_lb_dual(sol)` | Dual values | Variable lower bound duals (non-negative) |
+| `variable_constraints_ub_dual(sol)` | Dual values | Variable upper bound duals (non-negative) |
+| `dim_dual_state_constraints_box(sol)` | `Int` | Dimension of state box constraint duals |
+| `dim_dual_control_constraints_box(sol)` | `Int` | Dimension of control box constraint duals |
+| `dim_dual_variable_constraints_box(sol)` | `Int` | Dimension of variable box constraint duals |
+| `path_constraints_dual(sol)` | Dual values | Nonlinear path constraint duals (signed) |
+| `boundary_constraints_dual(sol)` | Dual values | Nonlinear boundary constraint duals (signed) |
+| `dim_path_constraints_nl(sol)` | `Int` | Number of nonlinear path constraints |
+| `dim_boundary_constraints_nl(sol)` | `Int` | Number of nonlinear boundary constraints |
 
 ### Solution metadata
 
diff --git a/src/imports/ctmodels.jl b/src/imports/ctmodels.jl
index 60d4029cc..10d250bc5 100644
--- a/src/imports/ctmodels.jl
+++ b/src/imports/ctmodels.jl
@@ -54,6 +54,14 @@ import CTModels:
     is_initial_time_free,
     is_final_time_fixed,
     is_final_time_free,
+    has_variable,
+    is_variable,
+    has_control,
+    is_control_free,
+    has_abstract_definition,
+    is_abstractly_defined,
+    is_nonautonomous,
+    is_nonvariable,
     state_dimension,
     control_dimension,
     variable_dimension,
@@ -72,9 +80,9 @@ import CTModels:
     variable_constraints_box,
     dim_path_constraints_nl,
     dim_boundary_constraints_nl,
-    dim_state_constraints_box,
-    dim_control_constraints_box,
-    dim_variable_constraints_box,
+    dim_dual_state_constraints_box,
+    dim_dual_control_constraints_box,
+    dim_dual_variable_constraints_box,
     state,
     control,
     variable,
@@ -84,6 +92,7 @@ import CTModels:
     mayer,
     lagrange,
     definition,
+    expression,
     dual,
     iterations,
     status,
diff --git a/test/README.md b/test/README.md
index 670610017..d1427dcaa 100644
--- a/test/README.md
+++ b/test/README.md
@@ -14,30 +14,49 @@ For detailed guidelines on testing and coverage, please refer to:
 
 Tests are executed using the standard Julia Test interface, enhanced by `CTBase.TestRunner`.
 
+### Convenience Command: `jtest`
+
+If the `jtest` command is available (custom script), you can use it for quick test execution:
+
+```bash
+# Run all tests
+jtest
+
+# Run specific test file(s)
+jtest test_ctbase test_ctmodels
+
+# Run test directory
+jtest reexport
+```
+
+If `jtest` is not available, use the manual commands below.
+
 ### Default Run (All Enabled Tests)
 
 ```bash
-julia --project=@. -e 'using Pkg; Pkg.test()'
+julia --project=@. -e 'using Pkg; Pkg.test()' 2>&1 | tee /tmp/test_output.txt
 ```
 
+**Note:** Always use `tee` to capture output to `/tmp/test_output.txt` for later inspection with `grep`.
+
 ### Running Specific Test Groups
 
 To run only specific test groups (e.g., `reexport`):
 
 ```bash
-julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["suite/reexport/*"])'
+julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["suite/reexport/*"])' 2>&1 | tee /tmp/test_output.txt
 ```
 
 Multiple groups can be specified:
 
 ```bash
-julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["suite/reexport/*", "suite/other/*"])'
+julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["suite/reexport/*", "suite/other/*"])' 2>&1 | tee /tmp/test_output.txt
 ```
 
 ### Running All Tests (Including Optional/Long Tests)
 
 ```bash
-julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["all"])'
+julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["all"])' 2>&1 | tee /tmp/test_output.txt
 ```
 
 ---
@@ -47,7 +66,7 @@ julia --project=@. -e 'using Pkg; Pkg.test(; test_args=["all"])'
 To run tests with coverage and generate a report:
 
 ```bash
-julia --project=@. -e 'using Pkg; Pkg.test("OptimalControl"; coverage=true); include("test/coverage.jl")'
+julia --project=@. -e 'using Pkg; Pkg.test("OptimalControl"; coverage=true); include("test/coverage.jl")' 2>&1 | tee /tmp/test_coverage_output.txt
 ```
 
 This will:
diff --git a/test/suite/reexport/test_ctmodels.jl b/test/suite/reexport/test_ctmodels.jl
index 21d120094..e71466a5e 100644
--- a/test/suite/reexport/test_ctmodels.jl
+++ b/test/suite/reexport/test_ctmodels.jl
@@ -107,6 +107,14 @@ function test_ctmodels()
                 :is_initial_time_free,
                 :is_final_time_fixed,
                 :is_final_time_free,
+                :has_variable,
+                :is_variable,
+                :has_control,
+                :is_control_free,
+                :has_abstract_definition,
+                :is_abstractly_defined,
+                :is_nonautonomous,
+                :is_nonvariable,
                 :state_dimension,
                 :control_dimension,
                 :variable_dimension,
@@ -134,9 +142,9 @@ function test_ctmodels()
                 :variable_constraints_box,
                 :dim_path_constraints_nl,
                 :dim_boundary_constraints_nl,
-                :dim_state_constraints_box,
-                :dim_control_constraints_box,
-                :dim_variable_constraints_box,
+                :dim_dual_state_constraints_box,
+                :dim_dual_control_constraints_box,
+                :dim_dual_variable_constraints_box,
                 :state,
                 :control,
                 :variable,
@@ -146,6 +154,7 @@ function test_ctmodels()
                 :mayer,
                 :lagrange,
                 :definition,
+                :expression,
                 :dual,
                 :iterations,
                 :status,

From b39ee75a4527aed15a537d43ff557bcf2fba6807 Mon Sep 17 00:00:00 2001
From: Olivier Cots <olivier.cots@irit.fr>
Date: Tue, 21 Apr 2026 14:04:34 +0200
Subject: [PATCH 2/2] Restructure documentation TOC and fix constraint
 dimension functions
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

- Flatten manual-model.md and manual-solution.md TOC: promote component sections
  from ### to ## level for better sidebar navigation
- Replace static Content lists with Documenter @contents blocks (Depth = 2)
- Redistribute Model predicates across logical sections:
  - has_variable/is_variable/is_nonvariable → Variable section
  - has_control/is_control_free → Control section
  - has_abstract_definition/is_abstractly_defined → Problem definition
  - is_nonautonomous → Time dependence
- Remove standalone Model predicates section
- Fix constraint dimension functions:
  - Restore dim_state_constraints_box, dim_control_constraints_box,
    dim_variable_constraints_box for Model (constraint counts)
  - Keep dim_dual_*_constraints_box for Solution (dual dimensions)
- Update imports, tests, and API documentation to include both families
- Remove Draft = false meta blocks from markdown files (use make.jl draft mode)
- Enable
- Flatten manual-model.md and manual-solution.md TOC: promo
---
 docs/make.jl                         |   2 +-
 docs/src/api/public.md               |   3 +
 docs/src/manual-model.md             | 181 ++++++++++++---------------
 docs/src/manual-solution.md          |  61 ++++-----
 src/imports/ctmodels.jl              |   3 +
 test/suite/reexport/test_ctmodels.jl |   3 +
 6 files changed, 120 insertions(+), 133 deletions(-)

diff --git a/docs/make.jl b/docs/make.jl
index 764bcac33..b26d47cbd 100644
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -153,7 +153,7 @@ cp(
 Draft = false
 ```
 =#
-draft = true  # Draft mode: if true, @example blocks in markdown are not executed
+draft = false  # Draft mode: if true, @example blocks in markdown are not executed
 
 # ═══════════════════════════════════════════════════════════════════════════════
 # Load extensions
diff --git a/docs/src/api/public.md b/docs/src/api/public.md
index 50d35ed6f..dcbdc4166 100644
--- a/docs/src/api/public.md
+++ b/docs/src/api/public.md
@@ -58,10 +58,13 @@ definition
 expression
 describe
 dim_boundary_constraints_nl
+dim_control_constraints_box
 dim_dual_control_constraints_box
 dim_dual_state_constraints_box
 dim_dual_variable_constraints_box
 dim_path_constraints_nl
+dim_state_constraints_box
+dim_variable_constraints_box
 dimension
 discretize
 dual
diff --git a/docs/src/manual-model.md b/docs/src/manual-model.md
index d7a428651..633e06ccf 100644
--- a/docs/src/manual-model.md
+++ b/docs/src/manual-model.md
@@ -1,9 +1,5 @@
 # [The optimal control problem object: structure and usage](@id manual-model)
 
-```@meta
-Draft = false
-```
-
 In this manual, we'll first recall the **main functionalities** you can use when working with an optimal control problem (OCP). This includes essential operations like:
 
 * **Solving an OCP**: How to find the optimal solution for your defined problem.
@@ -19,9 +15,10 @@ After covering these core functionalities, we'll delve into the **structure of a
 
 **Content**
 
-* [Main functionalities](@ref manual-model-main-functionalities)
-* [Model struct](@ref manual-model-struct)
-* [API Reference by Component](@ref manual-model-api)
+```@contents
+Pages = ["manual-model.md"]
+Depth = 2
+```
 
 ---
 
@@ -124,11 +121,7 @@ definition(ocp)
 
     We refer to the CTModels documentation for more details about this struct and its fields.
 
-## [API Reference by Component](@id manual-model-api)
-
-This section provides a comprehensive reference of all methods available for inspecting and querying optimal control problems. Methods are organized by component for easy navigation.
-
-To illustrate the various methods, we define a more complex optimal control problem with free final time, variables, and various types of constraints:
+To illustrate the various methods in the sections below, we define a more complex optimal control problem with free final time, variables, and various types of constraints:
 
 ```@example main
 ocp = @def begin
@@ -149,11 +142,11 @@ end
 nothing # hide
 ```
 
-### Times
+## Times
 
 The time component defines the temporal domain of the optimal control problem.
 
-#### Times model
+### Times model
 
 Get the times model:
 
@@ -180,7 +173,7 @@ If you try to get the final time without providing the variable when it's free,
 final_time(ocp)  # error: tf is free, need variable
 ```
 
-#### Time variable names
+### Time variable names
 
 Get the names of the time variable and time bounds:
 
@@ -196,7 +189,7 @@ initial_time_name(ocp)  # returns "0" (initial time is fixed at 0)
 final_time_name(ocp)  # returns "tf" (final time is a variable)
 ```
 
-#### Time fixedness predicates
+### Time fixedness predicates
 
 Check whether initial or final times are fixed or free:
 
@@ -225,7 +218,7 @@ has_fixed_final_time(ocp)  # false (tf is free in this OCP)
 has_free_final_time(ocp)  # true (tf is part of variable v)
 ```
 
-#### Autonomy
+### Autonomy
 
 Check if the dynamics and Lagrange cost are autonomous (time-independent):
 
@@ -235,7 +228,7 @@ is_autonomous(ocp)  # false if dynamics or cost depend on time
 
 For more details on autonomy, see the [Time dependence](@ref manual-model-time-dependence) section below.
 
-#### [Summary table](@id manual-model-summary-time)
+### [Summary table](@id manual-model-summary-time)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -252,11 +245,11 @@ For more details on autonomy, see the [Time dependence](@ref manual-model-time-d
 | `has_free_final_time(ocp)` | `Bool` | True if tf is free |
 | `is_autonomous(ocp)` | `Bool` | True if time-independent |
 
-### State
+## State
 
 The state component represents the state variables of the optimal control problem.
 
-#### State component information
+### State component information
 
 Get the name, dimension, and component names of the state:
 
@@ -276,7 +269,7 @@ state_components(ocp)  # returns ["x", "y"] (component names)
 
     The component names are used when plotting the solution. See the [plot manual](@ref manual-plot).
 
-#### State box constraints
+### State box constraints
 
 Get the box constraints on the state (lower and upper bounds):
 
@@ -298,7 +291,7 @@ Get the dimension of state box constraints:
 dim_state_constraints_box(ocp)  # returns number of box constraints on state
 ```
 
-#### [Summary table](@id manual-model-summary-state)
+### [Summary table](@id manual-model-summary-state)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -308,11 +301,11 @@ dim_state_constraints_box(ocp)  # returns number of box constraints on state
 | `state_constraints_box(ocp)` | Box constraints | State box constraints |
 | `dim_state_constraints_box(ocp)` | `Int` | Number of state box constraints |
 
-### Control
+## Control
 
 The control component represents the control variables of the optimal control problem.
 
-#### Control component information
+### Control component information
 
 Get the name, dimension, and component names of the control:
 
@@ -328,7 +321,7 @@ control_dimension(ocp)  # returns 1 (dimension of control)
 control_components(ocp)  # returns ["u"] (component names)
 ```
 
-#### Control box constraints
+### Control box constraints
 
 Get the box constraints on the control:
 
@@ -350,7 +343,19 @@ Get the dimension of control box constraints:
 dim_control_constraints_box(ocp)  # returns number of box constraints on control
 ```
 
-#### [Summary table](@id manual-model-summary-control)
+### Control presence
+
+Check whether the problem has a control input:
+
+```@example main
+has_control(ocp)  # true if problem has a control input
+```
+
+!!! note "Variant method"
+
+    - `is_control_free(ocp)` ≡ `!has_control(ocp)`
+
+### [Summary table](@id manual-model-summary-control)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -359,12 +364,14 @@ dim_control_constraints_box(ocp)  # returns number of box constraints on control
 | `control_components(ocp)` | `Vector{String}` | Control component names |
 | `control_constraints_box(ocp)` | Box constraints | Control box constraints |
 | `dim_control_constraints_box(ocp)` | `Int` | Number of control box constraints |
+| `has_control(ocp)` | `Bool` | True if problem has a control input |
+| `is_control_free(ocp)` | `Bool` | True if problem has no control (`≡ !has_control`) |
 
-### Variable
+## Variable
 
 The variable component represents the optimization variables (parameters) of the optimal control problem.
 
-#### Variable component information
+### Variable component information
 
 Get the name, dimension, and component names of the variable:
 
@@ -380,7 +387,7 @@ variable_dimension(ocp)  # returns 2 (dimension of variable)
 variable_components(ocp)  # returns ["w", "tf"] (component names)
 ```
 
-#### Variable box constraints
+### Variable box constraints
 
 Get the box constraints on the variable:
 
@@ -402,7 +409,20 @@ Get the dimension of variable box constraints:
 dim_variable_constraints_box(ocp)  # returns number of box constraints on variable
 ```
 
-#### [Summary table](@id manual-model-summary-variable)
+### Variable presence
+
+Check whether the problem has optimization variables:
+
+```@example main
+has_variable(ocp)  # true if problem has optimization variables
+```
+
+!!! note "Variant methods"
+
+    - `is_variable(ocp)` ≡ `has_variable(ocp)`
+    - `is_nonvariable(ocp)` ≡ `!has_variable(ocp)`
+
+### [Summary table](@id manual-model-summary-variable)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -411,12 +431,15 @@ dim_variable_constraints_box(ocp)  # returns number of box constraints on variab
 | `variable_components(ocp)` | `Vector{String}` | Variable component names |
 | `variable_constraints_box(ocp)` | Box constraints | Variable box constraints |
 | `dim_variable_constraints_box(ocp)` | `Int` | Number of variable box constraints |
+| `has_variable(ocp)` | `Bool` | True if problem has optimization variables |
+| `is_variable(ocp)` | `Bool` | Alias for `has_variable` |
+| `is_nonvariable(ocp)` | `Bool` | True if problem has no variables (`≡ !has_variable`) |
 
-### Dynamics
+## Dynamics
 
 The dynamics component defines the differential equations governing the state evolution.
 
-#### Dynamics function
+### Dynamics function
 
 The dynamics are stored as an in-place function of the form `f!(dx, t, x, u, v)`:
 
@@ -438,17 +461,17 @@ The first argument `dx` is mutated upon call and contains the state derivative.
 * `u`: control
 * `v`: variable
 
-#### [Summary table](@id manual-model-summary-dynamics)
+### [Summary table](@id manual-model-summary-dynamics)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
 | `dynamics(ocp)` | `Function` | In-place dynamics function f!(dx, t, x, u, v) |
 
-### Objective
+## Objective
 
 The objective component defines the cost function to minimize or maximize.
 
-#### Criterion
+### Criterion
 
 The criterion indicates whether the problem is a minimization or maximization:
 
@@ -456,7 +479,7 @@ The criterion indicates whether the problem is a minimization or maximization:
 criterion(ocp)  # returns :min or :max
 ```
 
-#### Objective form
+### Objective form
 
 The objective function can be in Mayer form, Lagrange form, or Bolza form (combination of both):
 
@@ -479,7 +502,7 @@ has_lagrange_cost(ocp)  # true if Lagrange cost exists
     - `is_mayer_cost_defined(ocp)` ≡ `has_mayer_cost(ocp)`
     - `is_lagrange_cost_defined(ocp)` ≡ `has_lagrange_cost(ocp)`
 
-#### Mayer cost
+### Mayer cost
 
 Get the Mayer cost function with signature `g(x0, xf, v)`:
 
@@ -487,7 +510,7 @@ Get the Mayer cost function with signature `g(x0, xf, v)`:
 g = mayer(ocp)  # error if no Mayer cost
 ```
 
-#### Lagrange cost
+### Lagrange cost
 
 Get the Lagrange cost function with signature `f⁰(t, x, u, v)`:
 
@@ -500,7 +523,7 @@ v = [1.0, 2.0]
 f⁰(s, q, u, v)  # returns the integrand value
 ```
 
-#### [Summary table](@id manual-model-summary-objective)
+### [Summary table](@id manual-model-summary-objective)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -510,11 +533,11 @@ f⁰(s, q, u, v)  # returns the integrand value
 | `mayer(ocp)` | `Function` | Mayer cost function g(x0, xf, v) |
 | `lagrange(ocp)` | `Function` | Lagrange cost function f⁰(t, x, u, v) |
 
-### Constraints
+## Constraints
 
 The constraints component defines the constraints on the optimal control problem.
 
-#### Individual constraints
+### Individual constraints
 
 Retrieve a specific constraint by its label using the `constraint` function. It returns a tuple `(type, f, lb, ub)`:
 
@@ -557,7 +580,7 @@ println("type: ", type)
 println("val: ", f(s, q, u, v))
 ```
 
-#### All constraints
+### All constraints
 
 Get all constraints as a collection:
 
@@ -565,7 +588,7 @@ Get all constraints as a collection:
 constraints(ocp)  # returns all constraints
 ```
 
-#### Nonlinear constraints
+### Nonlinear constraints
 
 Get nonlinear path and boundary constraints:
 
@@ -602,7 +625,7 @@ dim_boundary_constraints_nl(ocp)  # number of nonlinear boundary constraints
 
     To get the dual variable (or Lagrange multiplier) associated to a constraint, use the [`dual`](@ref) method on a solution.
 
-#### [Summary table](@id manual-model-summary-constraints)
+### [Summary table](@id manual-model-summary-constraints)
 
 | Method | Returns | Description |
 | -------- | --------- | --------- |
@@ -613,9 +636,7 @@ dim_boundary_constraints_nl(ocp)  # number of nonlinear boundary constraints
 | `dim_path_constraints_nl(ocp)` | `Int` | Number of nonlinear path constraints |
 | `dim_boundary_constraints_nl(ocp)` | `Int` | Number of nonlinear boundary constraints |
 
-### Other accessors
-
-#### Problem definition
+## Problem definition
 
 Get the problem definition as a string:
 
@@ -634,7 +655,19 @@ nothing # hide
 
     The definition is optional and can be `EmptyDefinition`. Use `has_abstract_definition(ocp)` to check if a definition is present.
 
-### [Time dependence](@id manual-model-time-dependence)
+### Definition presence
+
+Check whether the problem carries an abstract definition:
+
+```@example main
+has_abstract_definition(ocp)  # true if definition is present (not EmptyDefinition)
+```
+
+!!! note "Variant method"
+
+    - `is_abstractly_defined(ocp)` ≡ `has_abstract_definition(ocp)`
+
+## [Time dependence](@id manual-model-time-dependence)
 
 Optimal control problems can be **autonomous** or **non-autonomous**. In an autonomous problem, neither the dynamics nor the Lagrange cost explicitly depends on the time variable.
 
@@ -677,60 +710,12 @@ end
 is_autonomous(ocp)
 ```
 
-### Model predicates
-
-Check various properties of the optimal control problem model.
-
-#### Variable and control presence
-
-Check if the problem has optimization variables or control input:
-
-```@example main
-has_variable(ocp)  # true if problem has optimization variables
-```
-
-```@example main
-has_control(ocp)  # true if problem has control input
-```
-
-!!! note "Variant methods"
-
-    Alternative methods are also available:
-    - `is_variable(ocp)` ≡ `has_variable(ocp)`
-    - `is_nonvariable(ocp)` ≡ `!has_variable(ocp)`
-    - `is_control_free(ocp)` ≡ `!has_control(ocp)`
-
-#### Definition presence
-
-Check if the problem has an abstract definition:
-
-```@example main
-has_abstract_definition(ocp)  # true if definition is present (not EmptyDefinition)
-```
-
-!!! note "Variant methods"
-
-    - `is_abstractly_defined(ocp)` ≡ `has_abstract_definition(ocp)`
-
-#### Time dependence
-
-Check if the problem is non-autonomous (time-dependent):
+The variant predicate `is_nonautonomous` is also available and returns the opposite of `is_autonomous`:
 
 ```@example main
 is_nonautonomous(ocp)  # true if dynamics or cost depend on time
 ```
 
-!!! note "Variant methods"
+!!! note "Variant method"
 
     - `is_nonautonomous(ocp)` ≡ `!is_autonomous(ocp)`
-
-#### [Summary table](@id manual-model-summary-predicates)
-
-| Method | Returns | Description |
-| -------- | --------- | ------------- |
-| `has_variable(ocp)` | `Bool` | True if problem has optimization variables |
-| `has_control(ocp)` | `Bool` | True if problem has control input |
-| `has_abstract_definition(ocp)` | `Bool` | True if definition is present |
-| `is_abstractly_defined(ocp)` | `Bool` | Alias for has_abstract_definition |
-| `is_nonautonomous(ocp)` | `Bool` | True if time-dependent |
-| `is_nonvariable(ocp)` | `Bool` | True if no optimization variables |
diff --git a/docs/src/manual-solution.md b/docs/src/manual-solution.md
index e537b463b..07b5a8099 100644
--- a/docs/src/manual-solution.md
+++ b/docs/src/manual-solution.md
@@ -1,9 +1,5 @@
 # [The optimal control solution object: structure and usage](@id manual-solution)
 
-```@meta
-Draft = false
-```
-
 In this manual, we'll first recall the **main functionalities** you can use when working with a solution of an optimal control problem. This includes essential operations like:
 
 * **Plotting a solution**: How to plot the optimal solution for your defined problem.
@@ -13,11 +9,12 @@ After covering these core functionalities, we'll delve into the **structure of a
 
 ---
 
-## Content
+**Content**
 
-* [Main functionalities](@ref manual-solution-main-functionalities)
-* [Solution struct](@ref manual-solution-struct)
-* [API Reference by Component](@ref manual-solution-api)
+```@contents
+Pages = ["manual-solution.md"]
+Depth = 2
+```
 
 ---
 
@@ -103,15 +100,11 @@ You can also retrieve the original optimal control problem from the solution:
 model(sol)  # returns the original OCP model
 ```
 
-## [API Reference by Component](@id manual-solution-api)
-
-This section provides a comprehensive reference of all methods available for inspecting and querying optimal control solutions. Methods are organized by component for easy navigation.
-
-### Trajectories
+## Trajectories
 
 The trajectory component provides access to the state, control, variable, and costate trajectories.
 
-#### State trajectory
+### State trajectory
 
 Get the state trajectory as a function of time:
 
@@ -136,7 +129,7 @@ The state function can be evaluated at any time within the problem horizon, even
 x(0.25)  # still works: interpolated value
 ```
 
-#### Control trajectory
+### Control trajectory
 
 Get the control trajectory as a function of time:
 
@@ -148,7 +141,7 @@ u = control(sol)  # returns a function of time
 u(t)  # returns control value at t
 ```
 
-#### Variable values
+### Variable values
 
 Get the optimization variable values:
 
@@ -156,7 +149,7 @@ Get the optimization variable values:
 v = variable(sol)  # returns an empty vector if no variable
 ```
 
-#### Costate trajectory
+### Costate trajectory
 
 Get the costate (adjoint) trajectory as a function of time:
 
@@ -168,7 +161,7 @@ p = costate(sol)  # returns a function of time
 p(t)  # returns costate vector at t
 ```
 
-#### Time information
+### Time information
 
 Get time-related information from the solution:
 
@@ -199,7 +192,7 @@ times(sol)  # returns the TimesModel struct containing time information
 !!! note "Trajectory data formats"
     Trajectories (`state`, `control`, `costate`, `path_constraints_dual`) can be provided either as matrices (rows = time points, columns = components) or as functions `t -> vector` for interpolated or analytical data.
 
-#### [Summary table](@id manual-solution-summary-trajectories)
+### [Summary table](@id manual-solution-summary-trajectories)
 
 | Method | Returns | Description |
 | -------- | --------- | ------------- |
@@ -210,11 +203,11 @@ times(sol)  # returns the TimesModel struct containing time information
 | `time_grid(sol)` | `Vector{Float64}` | Discretization time grid |
 | `times(sol)` | `TimesModel` | TimesModel struct containing time information |
 
-### Objective
+## Objective
 
 The objective component provides access to the objective value.
 
-#### Objective value
+### Objective value
 
 Get the optimal objective value:
 
@@ -222,13 +215,13 @@ Get the optimal objective value:
 objective(sol)  # returns the objective value
 ```
 
-#### [Summary table](@id manual-solution-summary-objective)
+### [Summary table](@id manual-solution-summary-objective)
 
 | Method | Returns | Description |
 | -------- | --------- | ------------- |
 | `objective(sol)` | `Float64` | Objective value |
 
-### Dual variables
+## Dual variables
 
 The dual variables (Lagrange multipliers) provide sensitivity information about constraints.
 
@@ -253,7 +246,7 @@ sol = solve(ocp; display=false)
 nothing # hide
 ```
 
-#### Dual of labeled constraints
+### Dual of labeled constraints
 
 Get the dual variable for a specific labeled constraint:
 
@@ -299,7 +292,7 @@ plot(time_grid(sol), μ_v)
 
     The raw non-negative `*_lb_dual(sol)` / `*_ub_dual(sol)` accessors (see below) remain available if the unsigned components are needed separately.
 
-#### Box constraint duals
+### Box constraint duals
 
 Get dual variables for box constraints on state, control, and variable:
 
@@ -327,7 +320,7 @@ variable_constraints_lb_dual(sol)  # lower bound duals for variable
 variable_constraints_ub_dual(sol)  # upper bound duals for variable
 ```
 
-#### Box constraint dual dimensions
+### Box constraint dual dimensions
 
 Get the dimensions of the box-constraint dual vectors (one entry per primal component that is box-constrained):
 
@@ -343,7 +336,7 @@ dim_dual_control_constraints_box(sol)  # dimension of control box constraint dua
 dim_dual_variable_constraints_box(sol)  # dimension of variable box constraint duals
 ```
 
-#### Nonlinear constraint duals
+### Nonlinear constraint duals
 
 Get dual variables for nonlinear path and boundary constraints:
 
@@ -365,7 +358,7 @@ dim_path_constraints_nl(sol)  # number of nonlinear path constraints
 dim_boundary_constraints_nl(sol)  # number of nonlinear boundary constraints
 ```
 
-#### Summary table
+### Summary table
 
 | Method | Returns | Description |
 | -------- | --------- | ------------- |
@@ -384,11 +377,11 @@ dim_boundary_constraints_nl(sol)  # number of nonlinear boundary constraints
 | `dim_path_constraints_nl(sol)` | `Int` | Number of nonlinear path constraints |
 | `dim_boundary_constraints_nl(sol)` | `Int` | Number of nonlinear boundary constraints |
 
-### Solution metadata
+## Solution metadata
 
 The solution metadata provides information about the solver performance and status.
 
-#### Solver status
+### Solver status
 
 Check if the solution was successful:
 
@@ -408,7 +401,7 @@ Get the solver message:
 message(sol)  # returns solver message string
 ```
 
-#### Iteration count
+### Iteration count
 
 Get the number of solver iterations:
 
@@ -416,7 +409,7 @@ Get the number of solver iterations:
 iterations(sol)  # returns iteration count
 ```
 
-#### Constraints violation
+### Constraints violation
 
 Get the maximum constraint violation:
 
@@ -424,7 +417,7 @@ Get the maximum constraint violation:
 constraints_violation(sol)  # returns max violation
 ```
 
-#### Additional solver information
+### Additional solver information
 
 Get additional solver-specific information:
 
@@ -432,7 +425,7 @@ Get additional solver-specific information:
 infos(sol)  # returns dictionary of solver info
 ```
 
-#### [Summary table](@id manual-solution-summary-solver)
+### [Summary table](@id manual-solution-summary-solver)
 
 | Method | Returns | Description |
 | -------- | --------- | ------------- |
diff --git a/src/imports/ctmodels.jl b/src/imports/ctmodels.jl
index 10d250bc5..9e2aab40a 100644
--- a/src/imports/ctmodels.jl
+++ b/src/imports/ctmodels.jl
@@ -80,6 +80,9 @@ import CTModels:
     variable_constraints_box,
     dim_path_constraints_nl,
     dim_boundary_constraints_nl,
+    dim_state_constraints_box,
+    dim_control_constraints_box,
+    dim_variable_constraints_box,
     dim_dual_state_constraints_box,
     dim_dual_control_constraints_box,
     dim_dual_variable_constraints_box,
diff --git a/test/suite/reexport/test_ctmodels.jl b/test/suite/reexport/test_ctmodels.jl
index e71466a5e..63eb2b81b 100644
--- a/test/suite/reexport/test_ctmodels.jl
+++ b/test/suite/reexport/test_ctmodels.jl
@@ -142,6 +142,9 @@ function test_ctmodels()
                 :variable_constraints_box,
                 :dim_path_constraints_nl,
                 :dim_boundary_constraints_nl,
+                :dim_state_constraints_box,
+                :dim_control_constraints_box,
+                :dim_variable_constraints_box,
                 :dim_dual_state_constraints_box,
                 :dim_dual_control_constraints_box,
                 :dim_dual_variable_constraints_box,