diff --git a/docs/doc_yamls/full_configuration_template.yaml b/docs/doc_yamls/full_configuration_template.yaml
index c68b7570..ca6abf1a 100644
--- a/docs/doc_yamls/full_configuration_template.yaml
+++ b/docs/doc_yamls/full_configuration_template.yaml
@@ -22,7 +22,7 @@ max_cost_total:
 
 # Debug and Monitoring
 overwrite_working_directory: True
-post_run_summary: True
+post_run_summary: False
 development_stage_id:
 task_id:
 
@@ -36,7 +36,7 @@ cost_value_on_error:
 ignore_errors:
 
 # Customization Options
-searcher: bayesian_optimization       # Internal key to select a NePS optimizer.
+searcher: hyperband       # Internal key to select a NePS optimizer.
 
 # Hooks
 pre_load_hooks:
diff --git a/docs/reference/optimizers.md b/docs/reference/optimizers.md
index 5838d974..927ebe14 100644
--- a/docs/reference/optimizers.md
+++ b/docs/reference/optimizers.md
@@ -59,18 +59,17 @@ The library will then load your custom settings and use them for optimization.
 Here's the format of a custom YAML (`custom_bo.yaml`) configuration using `Bayesian Optimization` as an example:
 
 ```yaml
-searcher_init:
-  algorithm: bayesian_optimization
-searcher_kwargs:  # Specific arguments depending on the searcher
-  initial_design_size: 7
-  surrogate_model: gp
-  acquisition: EI
-  log_prior_weighted: false
-  acquisition_sampler: random
-  random_interleave_prob: 0.1
-  disable_priors: false
-  prior_confidence: high
-  sample_default_first: false
+algorithm: bayesian_optimization
+# Specific arguments depending on the searcher
+initial_design_size: 7
+surrogate_model: gp
+acquisition: EI
+log_prior_weighted: false
+acquisition_sampler: random
+random_interleave_prob: 0.1
+disable_priors: false
+prior_confidence: high
+sample_default_first: false
 ```
 
 ```python
diff --git a/neps/api.py b/neps/api.py
index 664c163f..9a5d47e9 100644
--- a/neps/api.py
+++ b/neps/api.py
@@ -10,7 +10,7 @@
 
 import ConfigSpace as CS
 from neps.utils.run_args_from_yaml import check_essential_arguments, get_run_args_from_yaml,\
-    check_arg_defaults
+    check_double_reference
 
 from neps.utils.common import instance_from_map
 from neps.runtime import launch_runtime
@@ -221,46 +221,37 @@ def run(
         del searcher_kwargs["budget"]
     logger = logging.getLogger("neps")
 
-    # if arguments via run_args provided overwrite them
     if run_args:
-        # Check if the user provided other arguments directly to neps.run().
-        # If so, raise an error.
-        check_arg_defaults(run, locals())
-
-        # Warning if the user has specified default values for arguments that differ
-        # from those specified in 'run_args'. These user-defined changes are not applied.
-        warnings.warn(
-            "WARNING: Loading arguments from 'run_args'. Arguments directly provided "
-            "to neps.run(...) will be not used!"
-        )
-
         optim_settings = get_run_args_from_yaml(run_args)
+        check_double_reference(run, locals(), optim_settings)
 
-        # Update each argument based on optim_settings. If not key is not provided in yaml
-        # use default value. Currently strict but will change in the future.
-        run_pipeline = optim_settings.get("run_pipeline", None)
-        root_directory = optim_settings.get("root_directory", None)
-        pipeline_space = optim_settings.get("pipeline_space", None)
+        run_pipeline = optim_settings.get("run_pipeline", run_pipeline)
+        root_directory = optim_settings.get("root_directory", root_directory)
+        pipeline_space = optim_settings.get("pipeline_space", pipeline_space)
         overwrite_working_directory = optim_settings.get(
-            "overwrite_working_directory", False
+            "overwrite_working_directory", overwrite_working_directory
         )
-        post_run_summary = optim_settings.get("post_run_summary", False)
-        development_stage_id = optim_settings.get("development_stage_id", None)
-        task_id = optim_settings.get("task_id", None)
-        max_evaluations_total = optim_settings.get("max_evaluations_total", None)
-        max_evaluations_per_run = optim_settings.get("max_evaluations_per_run", None)
+        post_run_summary = optim_settings.get("post_run_summary", post_run_summary)
+        development_stage_id = optim_settings.get("development_stage_id",
+                                                  development_stage_id)
+        task_id = optim_settings.get("task_id", task_id)
+        max_evaluations_total = optim_settings.get("max_evaluations_total",
+                                                   max_evaluations_total)
+        max_evaluations_per_run = optim_settings.get("max_evaluations_per_run",
+                                                     max_evaluations_per_run)
         continue_until_max_evaluation_completed = optim_settings.get(
             "continue_until_max_evaluation_completed",
-            False,
-        )
-        max_cost_total = optim_settings.get("max_cost_total", None)
-        ignore_errors = optim_settings.get("ignore_errors", False)
-        loss_value_on_error = optim_settings.get("loss_value_on_error", None)
-        cost_value_on_error = optim_settings.get("cost_value_on_error", None)
-        pre_load_hooks = optim_settings.get("pre_load_hooks", None)
-        searcher = optim_settings.get("searcher", "default")
-        searcher_path = optim_settings.get("searcher_path", None)
-        for key, value in optim_settings.get("searcher_kwargs", {}).items():
+            continue_until_max_evaluation_completed)
+        max_cost_total = optim_settings.get("max_cost_total", max_cost_total)
+        ignore_errors = optim_settings.get("ignore_errors", ignore_errors)
+        loss_value_on_error = optim_settings.get("loss_value_on_error",
+                                                 loss_value_on_error)
+        cost_value_on_error = optim_settings.get("cost_value_on_error",
+                                                 cost_value_on_error)
+        pre_load_hooks = optim_settings.get("pre_load_hooks", pre_load_hooks)
+        searcher = optim_settings.get("searcher", searcher)
+        searcher_path = optim_settings.get("searcher_path", searcher_path)
+        for key, value in optim_settings.get("searcher_kwargs", searcher_kwargs).items():
             searcher_kwargs[key] = value
 
     # check if necessary arguments are provided.
@@ -447,10 +438,11 @@ def _run_args(
         # Fetching the searcher data, throws an error when the searcher is not found
         config = get_searcher_data(searcher)
 
-    searcher_alg = config["searcher_init"]["algorithm"]
-    searcher_config = (
-        {} if config["searcher_kwargs"] is None else config["searcher_kwargs"]
-    )
+    if "algorithm" in config:
+        searcher_alg = config.pop("algorithm")
+    else:
+        raise KeyError(f"Missing key algorithm in searcher config:{config}")
+    searcher_config = config
 
     logger.info(f"Running {searcher} as the searcher")
     logger.info(f"Algorithm: {searcher_alg}")
diff --git a/neps/optimizers/default_searchers/asha.yaml b/neps/optimizers/default_searchers/asha.yaml
index 169adf36..8d914ad4 100644
--- a/neps/optimizers/default_searchers/asha.yaml
+++ b/neps/optimizers/default_searchers/asha.yaml
@@ -1,15 +1,13 @@
-searcher_init:
-  algorithm: asha
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  early_stopping_rate: 0
-  initial_design_type: max_budget
-  use_priors: false
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: asha
+# Arguments that can be modified by the user
+eta: 3
+early_stopping_rate: 0
+initial_design_type: max_budget
+use_priors: false
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: RandomUniformPolicy
-  # promotion_policy: AsyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: RandomUniformPolicy
+# promotion_policy: AsyncPromotionPolicy
diff --git a/neps/optimizers/default_searchers/asha_prior.yaml b/neps/optimizers/default_searchers/asha_prior.yaml
index e43ecdd2..dc6852d1 100644
--- a/neps/optimizers/default_searchers/asha_prior.yaml
+++ b/neps/optimizers/default_searchers/asha_prior.yaml
@@ -1,15 +1,13 @@
-searcher_init:
-  algorithm: asha_prior
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  early_stopping_rate: 0
-  initial_design_type: max_budget
-  prior_confidence: medium  # or {"low", "high"}
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: asha_prior
+# Arguments that can be modified by the user
+eta: 3
+early_stopping_rate: 0
+initial_design_type: max_budget
+prior_confidence: medium  # or {"low", "high"}
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: FixedPriorPolicy
-  # promotion_policy: AsyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: FixedPriorPolicy
+# promotion_policy: AsyncPromotionPolicy
diff --git a/neps/optimizers/default_searchers/bayesian_optimization.yaml b/neps/optimizers/default_searchers/bayesian_optimization.yaml
index ffc18c82..26d2c507 100644
--- a/neps/optimizers/default_searchers/bayesian_optimization.yaml
+++ b/neps/optimizers/default_searchers/bayesian_optimization.yaml
@@ -1,19 +1,17 @@
-searcher_init:
-  algorithm: bayesian_optimization
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  initial_design_size: 10
-  surrogate_model: gp  # or {"gp_hierarchy"}
-  acquisition: EI  # or {"LogEI", "AEI"}
-  log_prior_weighted: false
-  acquisition_sampler: mutation  # or {"random", "evolution"}
-  random_interleave_prob: 0.0
-  disable_priors: true
-  sample_default_first: false
+algorithm: bayesian_optimization
+# Arguments that can be modified by the user
+initial_design_size: 10
+surrogate_model: gp  # or {"gp_hierarchy"}
+acquisition: EI  # or {"LogEI", "AEI"}
+log_prior_weighted: false
+acquisition_sampler: mutation  # or {"random", "evolution"}
+random_interleave_prob: 0.0
+disable_priors: true
+sample_default_first: false
 
-  # Other arguments:
-  # surrogate_model_args: None # type: dict
-  # optimal_assignment: false # type: bool
-  # domain_se_kernel: None # type: str
-  # graph_kernels: None # type: list
-  # hp_kernels: None # type: list
+# Other arguments:
+# surrogate_model_args: None # type: dict
+# optimal_assignment: false # type: bool
+# domain_se_kernel: None # type: str
+# graph_kernels: None # type: list
+# hp_kernels: None # type: list
diff --git a/neps/optimizers/default_searchers/hyperband.yaml b/neps/optimizers/default_searchers/hyperband.yaml
index d3a16145..d39fb139 100644
--- a/neps/optimizers/default_searchers/hyperband.yaml
+++ b/neps/optimizers/default_searchers/hyperband.yaml
@@ -1,14 +1,12 @@
-searcher_init:
-  algorithm: hyperband
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  initial_design_type: max_budget
-  use_priors: false
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: hyperband
+# Arguments that can be modified by the user
+eta: 3
+initial_design_type: max_budget
+use_priors: false
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: RandomUniformPolicy
-  # promotion_policy: SyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: RandomUniformPolicy
+# promotion_policy: SyncPromotionPolicy
diff --git a/neps/optimizers/default_searchers/mobster.yaml b/neps/optimizers/default_searchers/mobster.yaml
index c016000b..385b74ad 100644
--- a/neps/optimizers/default_searchers/mobster.yaml
+++ b/neps/optimizers/default_searchers/mobster.yaml
@@ -1,27 +1,25 @@
-searcher_init:
-  algorithm: mobster
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  initial_design_type: max_budget
-  use_priors: false
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: mobster
+# Arguments that can be modified by the user
+eta: 3
+initial_design_type: max_budget
+use_priors: false
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # arguments for model
-  surrogate_model: gp  # or {"gp_hierarchy"}
-  acquisition: EI  # or {"LogEI", "AEI"}
-  log_prior_weighted: false
-  acquisition_sampler: random  # or {"mutation", "evolution"}
+# arguments for model
+surrogate_model: gp  # or {"gp_hierarchy"}
+acquisition: EI  # or {"LogEI", "AEI"}
+log_prior_weighted: false
+acquisition_sampler: random  # or {"mutation", "evolution"}
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: RandomUniformPolicy
-  # promotion_policy: AsyncPromotionPolicy
-  # model_policy: ModelPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: RandomUniformPolicy
+# promotion_policy: AsyncPromotionPolicy
+# model_policy: ModelPolicy
 
-  # Other arguments
-  # surrogate_model_args: None # type: dict
-  # domain_se_kernel: None # type: str
-  # graph_kernels: None # type: list
-  # hp_kernels: None # type: list
+# Other arguments
+# surrogate_model_args: None # type: dict
+# domain_se_kernel: None # type: str
+# graph_kernels: None # type: list
+# hp_kernels: None # type: list
diff --git a/neps/optimizers/default_searchers/pibo.yaml b/neps/optimizers/default_searchers/pibo.yaml
index 8c4fecf6..b75a23f3 100644
--- a/neps/optimizers/default_searchers/pibo.yaml
+++ b/neps/optimizers/default_searchers/pibo.yaml
@@ -1,20 +1,18 @@
-searcher_init:
-  algorithm: bayesian_optimization
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  initial_design_size: 10
-  surrogate_model: gp  # or {"gp_hierarchy"}
-  acquisition: EI  # or {"LogEI", "AEI"}
-  log_prior_weighted: false
-  acquisition_sampler: mutation  # or {"random", "evolution"}
-  random_interleave_prob: 0.0
-  disable_priors: false
-  prior_confidence: medium  # or {"low", "high"}
-  sample_default_first: false
+algorithm: bayesian_optimization
+# Arguments that can be modified by the user
+initial_design_size: 10
+surrogate_model: gp  # or {"gp_hierarchy"}
+acquisition: EI  # or {"LogEI", "AEI"}
+log_prior_weighted: false
+acquisition_sampler: mutation  # or {"random", "evolution"}
+random_interleave_prob: 0.0
+disable_priors: false
+prior_confidence: medium  # or {"low", "high"}
+sample_default_first: false
 
-  # Other arguments:
-  # surrogate_model_args: None # type: dict
-  # optimal_assignment: false # type: bool
-  # domain_se_kernel: None # type: str
-  # graph_kernels: None # type: list
-  # hp_kernels: None # type: list
+# Other arguments:
+# surrogate_model_args: None # type: dict
+# optimal_assignment: false # type: bool
+# domain_se_kernel: None # type: str
+# graph_kernels: None # type: list
+# hp_kernels: None # type: list
diff --git a/neps/optimizers/default_searchers/priorband.yaml b/neps/optimizers/default_searchers/priorband.yaml
index 9b11ae9a..f5a16f6f 100644
--- a/neps/optimizers/default_searchers/priorband.yaml
+++ b/neps/optimizers/default_searchers/priorband.yaml
@@ -1,22 +1,20 @@
-searcher_init:
-  algorithm: priorband
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  initial_design_type: max_budget
-  prior_confidence: medium  # or {"low", "high"}
-  random_interleave_prob: 0.0
-  sample_default_first: true
-  sample_default_at_target: false
-  prior_weight_type: geometric
-  inc_sample_type: mutation 
-  inc_mutation_rate: 0.5
-  inc_mutation_std: 0.25
-  inc_style: dynamic
+algorithm: priorband
+# Arguments that can be modified by the user
+eta: 3
+initial_design_type: max_budget
+prior_confidence: medium  # or {"low", "high"}
+random_interleave_prob: 0.0
+sample_default_first: true
+sample_default_at_target: false
+prior_weight_type: geometric
+inc_sample_type: mutation
+inc_mutation_rate: 0.5
+inc_mutation_std: 0.25
+inc_style: dynamic
 
-  # arguments for model
-  model_based: false # crucial argument to set to allow model-search
+# arguments for model
+model_based: false # crucial argument to set to allow model-search
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: EnsemblePolicy
-  # promotion_policy: SyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: EnsemblePolicy
+# promotion_policy: SyncPromotionPolicy
diff --git a/neps/optimizers/default_searchers/priorband_bo.yaml b/neps/optimizers/default_searchers/priorband_bo.yaml
index 04e530c1..134ff78c 100644
--- a/neps/optimizers/default_searchers/priorband_bo.yaml
+++ b/neps/optimizers/default_searchers/priorband_bo.yaml
@@ -1,32 +1,30 @@
-searcher_init:
-  algorithm: priorband
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  initial_design_type: max_budget
-  prior_confidence: medium  # or {"low", "high"}
-  random_interleave_prob: 0.0
-  sample_default_first: true
-  sample_default_at_target: false
-  prior_weight_type: geometric
-  inc_sample_type: mutation
-  inc_mutation_rate: 0.5
-  inc_mutation_std: 0.25
-  inc_style: dynamic
+algorithm: priorband
+# Arguments that can be modified by the user
+eta: 3
+initial_design_type: max_budget
+prior_confidence: medium  # or {"low", "high"}
+random_interleave_prob: 0.0
+sample_default_first: true
+sample_default_at_target: false
+prior_weight_type: geometric
+inc_sample_type: mutation
+inc_mutation_rate: 0.5
+inc_mutation_std: 0.25
+inc_style: dynamic
 
-  # arguments for model
-  model_based: true # crucial argument to set to allow model-search
-  modelling_type: joint 
-  initial_design_size: 10
-  surrogate_model: gp  # or {"gp_hierarchy"}
-  acquisition: EI  # or {"LogEI", "AEI"}
-  log_prior_weighted: false
-  acquisition_sampler: mutation  # or {"random", "evolution"}
+# arguments for model
+model_based: true # crucial argument to set to allow model-search
+modelling_type: joint
+initial_design_size: 10
+surrogate_model: gp  # or {"gp_hierarchy"}
+acquisition: EI  # or {"LogEI", "AEI"}
+log_prior_weighted: false
+acquisition_sampler: mutation  # or {"random", "evolution"}
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: EnsemblePolicy
-  # promotion_policy: SyncPromotionPolicy
-  # model_policy: ModelPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: EnsemblePolicy
+# promotion_policy: SyncPromotionPolicy
+# model_policy: ModelPolicy
 
   # Other arguments
   # surrogate_model_args: None # type: dict
diff --git a/neps/optimizers/default_searchers/random_search.yaml b/neps/optimizers/default_searchers/random_search.yaml
index 745aeef5..848a7873 100644
--- a/neps/optimizers/default_searchers/random_search.yaml
+++ b/neps/optimizers/default_searchers/random_search.yaml
@@ -1,6 +1,4 @@
-searcher_init:
-  algorithm: random_search
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  use_priors: false
-  ignore_fidelity: true
+algorithm: random_search
+# Arguments that can be modified by the user
+use_priors: false
+ignore_fidelity: true
diff --git a/neps/optimizers/default_searchers/regularized_evolution.yaml b/neps/optimizers/default_searchers/regularized_evolution.yaml
index efb62a6a..0e298423 100644
--- a/neps/optimizers/default_searchers/regularized_evolution.yaml
+++ b/neps/optimizers/default_searchers/regularized_evolution.yaml
@@ -1,11 +1,9 @@
-searcher_init:
-  algorithm: regularized_evolution
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  population_size: 30
-  sample_size: 10
-  assisted: false
+algorithm: regularized_evolution
+# Arguments that can be modified by the user
+population_size: 30
+sample_size: 10
+assisted: false
 
-  # Other arguments
-  # assisted_zero_cost_proxy: None # type: Callable
-  # assisted_init_population_dir: None # type: str | Path
+# Other arguments
+# assisted_zero_cost_proxy: None # type: Callable
+# assisted_init_population_dir: None # type: str | Path
diff --git a/neps/optimizers/default_searchers/successive_halving.yaml b/neps/optimizers/default_searchers/successive_halving.yaml
index 17161685..148cbc69 100644
--- a/neps/optimizers/default_searchers/successive_halving.yaml
+++ b/neps/optimizers/default_searchers/successive_halving.yaml
@@ -1,15 +1,13 @@
-searcher_init:
-  algorithm: successive_halving
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  early_stopping_rate: 0
-  initial_design_type: max_budget
-  use_priors: false
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: successive_halving
+# Arguments that can be modified by the user
+eta: 3
+early_stopping_rate: 0
+initial_design_type: max_budget
+use_priors: false
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: RandomUniformPolicy
-  # promotion_policy: SyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: RandomUniformPolicy
+# promotion_policy: SyncPromotionPolicy
diff --git a/neps/optimizers/default_searchers/successive_halving_prior.yaml b/neps/optimizers/default_searchers/successive_halving_prior.yaml
index f107940d..29b320dd 100644
--- a/neps/optimizers/default_searchers/successive_halving_prior.yaml
+++ b/neps/optimizers/default_searchers/successive_halving_prior.yaml
@@ -1,15 +1,13 @@
-searcher_init:
-  algorithm: successive_halving_prior
-searcher_kwargs:
-  # Arguments that can be modified by the user
-  eta: 3
-  early_stopping_rate: 0
-  initial_design_type: max_budget
-  prior_confidence: medium  # or {"low", "high"}
-  random_interleave_prob: 0.0
-  sample_default_first: false
-  sample_default_at_target: false
+algorithm: successive_halving_prior
+# Arguments that can be modified by the user
+eta: 3
+early_stopping_rate: 0
+initial_design_type: max_budget
+prior_confidence: medium  # or {"low", "high"}
+random_interleave_prob: 0.0
+sample_default_first: false
+sample_default_at_target: false
 
-  # Arguments that can not be modified by the user
-  # sampling_policy: FixedPriorPolicy
-  # promotion_policy: SyncPromotionPolicy
+# Arguments that can not be modified by the user
+# sampling_policy: FixedPriorPolicy
+# promotion_policy: SyncPromotionPolicy
diff --git a/neps/search_spaces/yaml_search_space_utils.py b/neps/search_spaces/yaml_search_space_utils.py
index 8606a3e5..27c268e4 100644
--- a/neps/search_spaces/yaml_search_space_utils.py
+++ b/neps/search_spaces/yaml_search_space_utils.py
@@ -99,26 +99,16 @@ def deduce_type(
         TypeError: If the type cannot be deduced or the details don't align with expected
                 constraints.
         """
-    try:
-        # Deduce type
+    if isinstance(details, (str,  int, float)):
+        param_type = "const"
+    elif isinstance(details, dict):
         if "type" in details:
             param_type = details.pop("type").lower()
         else:
-            # because details could be string
-            if isinstance(details, (str, int, float)):
-                param_type = "const"
-                return param_type
-            else:
-                param_type = deduce_param_type(name, details)
-    except TypeError as e:
-        # because details could be int, float
-        if isinstance(details, (str, int, float)):
-            param_type = "const"
-            return param_type
-        else:
-            raise TypeError(
-                f"Unable to deduce parameter type for '{name}' with details '{details}'.") \
-                from e
+            param_type = deduce_param_type(name, details)
+    else:
+        raise TypeError(
+            f"Unable to deduce parameter type for '{name}' with details '{details}'.")
 
     return param_type
 
diff --git a/neps/utils/run_args_from_yaml.py b/neps/utils/run_args_from_yaml.py
index 1f290423..c67aded3 100644
--- a/neps/utils/run_args_from_yaml.py
+++ b/neps/utils/run_args_from_yaml.py
@@ -85,7 +85,11 @@ def get_run_args_from_yaml(path: str) -> dict:
         if parameter in expected_parameters:
             settings[parameter] = value
         else:
-            raise KeyError(f"Parameter '{parameter}' is not an argument of neps.run().")
+            raise KeyError(f"Parameter '{parameter}' is not an argument of neps.run() "
+                           f"provided via run_args."
+                           f"See here all valid arguments:"
+                           f" {', '.join(expected_parameters)}, "
+                           f"'run_pipeline', 'preload_hooks', 'pipeline_space'")
 
     # Process complex configurations (e.g., 'pipeline_space', 'searcher') and integrate
     # them into 'settings'.
@@ -257,11 +261,28 @@ def process_config_key(settings: Dict, special_configs: Dict, keys: List) -> Non
 
 
 def process_pipeline_space(key, special_configs, settings):
+    """
+    Process or load the pipeline space configuration.
+
+    This function checks if the given key exists in the `special_configs` dictionary.
+    If it exists, it processes the associated value, which can be either a dictionary
+    or a string. Based on the keys of the dictionary it decides if the pipeline_space
+    have to be loaded or needs to be converted into a neps search_space structure.
+    The processed pipeline space is then stored in the `settings`
+    dictionary under the given key.
+
+    Args:
+        key (str): The key to check in the `special_configs` dictionary.
+        special_configs (dict): The dictionary containing special configuration values.
+        settings (dict): The dictionary where the processed pipeline space will be stored.
+
+    Raises:
+        TypeError: If the value associated with the key is neither a string nor a
+        dictionary.
+        """
     if special_configs.get(key) is not None:
         pipeline_space = special_configs[key]
         if isinstance(pipeline_space, dict):
-            # TODO: was ist wenn ein argument fehlt
-
             # determine if dict contains path_loading or the actual search space
             expected_keys = {"path", "name"}
             actual_keys = set(pipeline_space.keys())
@@ -346,32 +367,18 @@ def import_object(path):
 
 def load_hooks_from_config(pre_load_hooks_dict: Dict) -> List:
     """
-    Loads hook functions from configurations.
-
-    Iterates through a dictionary of pre-load hooks, dynamically imports each
-    specified function by its 'path' and 'name', and accumulates the loaded
-    functions into a list.
+    Loads hook functions from a dictionary of configurations.
 
     Args:
-        pre_load_hooks_dict (dict): Dictionary of hook configurations, each
-        containing 'path' and 'name' keys for the hook function.
+        pre_load_hooks_dict (Dict): Dictionary with hook names as keys and paths as values
 
     Returns:
-        list: List of loaded hook functions.
-
-    Raises:
-        KeyError: If any hook configuration lacks 'path' or 'name' keys.
+        List: List of loaded hook functions.
     """
     loaded_hooks = []
-    for hook_config in pre_load_hooks_dict.values():
-        if "path" in hook_config and "name" in hook_config:
-            hook_func = load_and_return_object(hook_config["path"], hook_config[
-                "name"], PRE_LOAD_HOOKS)
-            loaded_hooks.append(hook_func)
-        else:
-            raise KeyError(
-                f"Expected keys 'path' and 'name' for hook, but got: " f"{hook_config}."
-            )
+    for name, path in pre_load_hooks_dict.items():
+        hook_func = load_and_return_object(path, name, PRE_LOAD_HOOKS)
+        loaded_hooks.append(hook_func)
     return loaded_hooks
 
 
@@ -480,29 +487,34 @@ def check_essential_arguments(
         )
 
 
-def check_arg_defaults(func: Callable, provided_arguments: Dict) -> Any:
+def check_double_reference(func: Callable, func_arguments: Dict, yaml_arguments: Dict) -> Any:
     """
-    Checks if provided arguments deviate from default values defined in the function's
-    signature.
+    Checks if no argument is defined both via function arguments and YAML.
 
     Parameters:
     - func (Callable): The function to check arguments against.
-    - provided_arguments: A dictionary containing the provided arguments and their
-    values.
+    - func_arguments (Dict): A dictionary containing the provided arguments to the
+    function and their values.
+    - yaml_arguments (Dict): A dictionary containing the arguments provided via a YAML
+    file.
 
     Raises:
-    - ValueError: If any provided argument differs from its default value in the function
-    signature.
+    - ValueError: If any provided argument is defined both via function arguments and the
+    YAML file.
     """
     sig = inspect.signature(func)
+
     for name, param in sig.parameters.items():
-        if param.default != provided_arguments[name]:
+        if param.default != func_arguments[name]:
             if name == RUN_ARGS:
-                # ignoring run_args argument
+                # Ignoring run_args argument
                 continue
             if name == SEARCHER_KWARGS:
                 # searcher_kwargs does not have a default specified by inspect
-                if provided_arguments[name] == {}:
+                if func_arguments[name] == {}:
                     continue
-            raise ValueError(
-                f"Argument '{name}' must not be set directly when 'run_args' is used.")
+            if name in yaml_arguments:
+                raise ValueError(
+                    f"Conflict for argument '{name}': Argument is defined both via "
+                    f"function arguments and YAML, which is not allowed."
+                )
diff --git a/neps_examples/basic_usage/search_space_example.yaml b/neps_examples/basic_usage/search_space_example.yaml
deleted file mode 100644
index e69de29b..00000000
diff --git a/neps_examples/yaml_usage/pipeline_space.yaml b/neps_examples/yaml_usage/pipeline_space.yaml
index c052c7e8..bbc8715f 100644
--- a/neps_examples/yaml_usage/pipeline_space.yaml
+++ b/neps_examples/yaml_usage/pipeline_space.yaml
@@ -1,16 +1,15 @@
-pipeline_space:
-  epochs:
-    lower: 1
-    upper: 5
-  learning_rate:
-    lower: 1e-5
-    upper: 1e-1
-    log: True
-  num_layers:
-    lower: 1
-    upper: 5
-  optimizer:
-    choices: ["adam", "sgd"]
-  num_neurons:
-    lower: 64
-    upper: 128
+epochs:
+  lower: 1
+  upper: 5
+learning_rate:
+  lower: 1e-5
+  upper: 1e-1
+  log: True
+num_layers:
+  lower: 1
+  upper: 5
+optimizer:
+  choices: ["adam", "sgd"]
+num_neurons:
+  lower: 64
+  upper: 128
diff --git a/tests/test_neps_api/testing_yaml/optimizer_test.yaml b/tests/test_neps_api/testing_yaml/optimizer_test.yaml
index 96c585a7..9d7e27f7 100644
--- a/tests/test_neps_api/testing_yaml/optimizer_test.yaml
+++ b/tests/test_neps_api/testing_yaml/optimizer_test.yaml
@@ -1,12 +1,11 @@
-searcher_init:
-  algorithm: bayesian_optimization
-searcher_kwargs:  # Specific arguments depending on the searcher
-  initial_design_size: 7
-  surrogate_model: gp
-  acquisition: EI
-  log_prior_weighted: false
-  acquisition_sampler: random
-  random_interleave_prob: 0.1
-  disable_priors: false
-  prior_confidence: high
-  sample_default_first: false
+algorithm: bayesian_optimization
+# Specific arguments depending on the searcher
+initial_design_size: 7
+surrogate_model: gp
+acquisition: EI
+log_prior_weighted: false
+acquisition_sampler: random
+random_interleave_prob: 0.1
+disable_priors: false
+prior_confidence: high
+sample_default_first: false
diff --git a/tests/test_yaml_run_args/run_args_full.yaml b/tests/test_yaml_run_args/run_args_full.yaml
index 4c87974c..e9dc08eb 100644
--- a/tests/test_yaml_run_args/run_args_full.yaml
+++ b/tests/test_yaml_run_args/run_args_full.yaml
@@ -31,9 +31,5 @@ search:
     surrogate_model: gp
 
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
-  hook2:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook2
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
+  hook2: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/run_args_full_same_level.yaml b/tests/test_yaml_run_args/run_args_full_same_level.yaml
index e621c892..9e32b64d 100644
--- a/tests/test_yaml_run_args/run_args_full_same_level.yaml
+++ b/tests/test_yaml_run_args/run_args_full_same_level.yaml
@@ -20,6 +20,4 @@ searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args" # check if without .py also works
-    name: hook1
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args" # check if without .py also works
diff --git a/tests/test_yaml_run_args/run_args_invalid_key.yaml b/tests/test_yaml_run_args/run_args_invalid_key.yaml
index b478abb1..6fc840ce 100644
--- a/tests/test_yaml_run_args/run_args_invalid_key.yaml
+++ b/tests/test_yaml_run_args/run_args_invalid_key.yaml
@@ -31,9 +31,5 @@ search:
     surrogate_model: gp
 
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
-  hook2:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook2
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
+  hook2: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/run_args_key_missing.yaml b/tests/test_yaml_run_args/run_args_key_missing.yaml
index db3ca836..704d1a2e 100644
--- a/tests/test_yaml_run_args/run_args_key_missing.yaml
+++ b/tests/test_yaml_run_args/run_args_key_missing.yaml
@@ -20,6 +20,4 @@ searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/run_args_optional_loading_format.yaml b/tests/test_yaml_run_args/run_args_optional_loading_format.yaml
index 510c655c..9c447806 100644
--- a/tests/test_yaml_run_args/run_args_optional_loading_format.yaml
+++ b/tests/test_yaml_run_args/run_args_optional_loading_format.yaml
@@ -24,6 +24,4 @@ searcher_kwargs:
   initial_design_size: 5
   surrogate_model: gp
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/run_args_wrong_name.yaml b/tests/test_yaml_run_args/run_args_wrong_name.yaml
index 0b187332..c0b451c4 100644
--- a/tests/test_yaml_run_args/run_args_wrong_name.yaml
+++ b/tests/test_yaml_run_args/run_args_wrong_name.yaml
@@ -31,9 +31,5 @@ search:
     surrogate_model: gp
 
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
-  hook2:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook2
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
+  hook2: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/run_args_wrong_path.yaml b/tests/test_yaml_run_args/run_args_wrong_path.yaml
index 47abfe04..95254e69 100644
--- a/tests/test_yaml_run_args/run_args_wrong_path.yaml
+++ b/tests/test_yaml_run_args/run_args_wrong_path.yaml
@@ -31,9 +31,5 @@ search:
     surrogate_model: gp
 
 pre_load_hooks:
-  hook1:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook1
-  hook2:
-    path: "tests/test_yaml_run_args/test_yaml_run_args.py"
-    name: hook2
+  hook1: "tests/test_yaml_run_args/test_yaml_run_args.py"
+  hook2: "tests/test_yaml_run_args/test_yaml_run_args.py"
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/customizing_neps_optimizer.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/customizing_neps_optimizer.yaml
index da1f4ca5..b079193e 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/customizing_neps_optimizer.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/customizing_neps_optimizer.yaml
@@ -1,6 +1,6 @@
 run_pipeline:
   path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  name: example_pipeline              # Function name within the file
 
 pipeline_space:
   learning_rate:
@@ -19,10 +19,6 @@ searcher:
   initial_design_size: 7
   surrogate_model: gp
   acquisition: EI
-  log_prior_weighted: false
   acquisition_sampler: random
   random_interleave_prob: 0.1
-  disable_priors: false
-  prior_confidence: high
-  sample_default_first: false
 
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/defining_hooks.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/defining_hooks.yaml
index d792f7d7..922bb542 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/defining_hooks.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/defining_hooks.yaml
@@ -1,20 +1,25 @@
 # Basic NEPS Configuration Example
 run_pipeline:
-  path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  path: tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
+  name: run_pipeline_constant
 
 pipeline_space:
   learning_rate:
     lower: 1e-5
     upper: 1e-1
     log: True  # Log scale for learning rate
+  epochs:
+    lower: 5
+    upper: 20
+    is_fidelity: True
   optimizer:
     choices: [adam, sgd, adamw]
-  epochs: 50
+  batch_size: 64
 
-root_directory: path/to/results       # Directory for result storage
+root_directory: path/to/results/hooks       # Directory for result storage
 max_evaluations_total: 20               # Budget
 
 pre_load_hooks:
-    hook1: path/to/your/hooks.py # (function_name: Path to the function's file)
-    hook2: path/to/your/hooks.py # Different function name from the same file source
+    hook1: tests/test_yaml_run_args/test_declarative_usage_docs/hooks.py
+
+overwrite_working_directory: True
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/full_configuration_template.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/full_configuration_template.yaml
index eee0b0fe..b79616a4 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/full_configuration_template.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/full_configuration_template.yaml
@@ -1,24 +1,28 @@
 # Full Configuration Template for NePS
 run_pipeline:
-  path: tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py  # Path to the Python file that contains your run_pipeline
-  name: run_pipeline                  # Name of your run_pipeline function within this file
+  path: tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
+  name: run_pipeline_constant
 
 pipeline_space:
   learning_rate:
     lower: 1e-5
     upper: 1e-1
-    log: True
+    log: True  # Log scale for learning rate
+  epochs:
+    lower: 5
+    upper: 20
+    is_fidelity: True
   optimizer:
     choices: [adam, sgd, adamw]
-  epochs: 50
+  batch_size: 64
 
-root_directory: path/to/results       # Directory for result storage
+root_directory: path/to/results/full_config      # Directory for result storage
 max_evaluations_total: 20             # Budget
 max_cost_total:
 
 # Debug and Monitoring
 overwrite_working_directory: True
-post_run_summary: True
+post_run_summary: False
 development_stage_id:
 task_id:
 
@@ -32,7 +36,7 @@ cost_value_on_error:
 ignore_errors:
 
 # Customization Options
-searcher: bayesian_optimization       # Internal key to select a NePS optimizer.
+searcher: hyperband       # Internal key to select a NePS optimizer.
 
 # Hooks
 pre_load_hooks:
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/hooks.py b/tests/test_yaml_run_args/test_declarative_usage_docs/hooks.py
new file mode 100644
index 00000000..a26f28f3
--- /dev/null
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/hooks.py
@@ -0,0 +1,8 @@
+def hook1(sampler):
+    """func to test loading of pre_load_hooks"""
+    return sampler
+
+
+def hook2(sampler):
+    """func to test loading of pre_load_hooks"""
+    return sampler
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/loading_own_optimizer.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/loading_own_optimizer.yaml
index 6174cd38..26897062 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/loading_own_optimizer.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/loading_own_optimizer.yaml
@@ -1,6 +1,6 @@
 run_pipeline:
   path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  name: example_pipeline              # Function name within the file
 
 pipeline_space:
   learning_rate:
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/loading_pipeline_space_dict.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/loading_pipeline_space_dict.yaml
index f5f532e2..a8185c79 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/loading_pipeline_space_dict.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/loading_pipeline_space_dict.yaml
@@ -1,11 +1,11 @@
-# Basic NEPS Configuration Example
+# Loading pipeline space from a python dict
 run_pipeline:
   path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  name: example_pipeline                   # Function name within the file
 
 pipeline_space:
   path: path/to/your/search_space.py  # Path to the dict file
-  name: search_space                  # Name of the dict instance
+  name: pipeline_space                  # Name of the dict instance
 
 root_directory: path/to/results       # Directory for result storage
 max_evaluations_total: 20               # Budget
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/neps_run.py b/tests/test_yaml_run_args/test_declarative_usage_docs/neps_run.py
index 7829225d..16533af6 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/neps_run.py
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/neps_run.py
@@ -1,15 +1,7 @@
 import argparse
-import numpy as np
 import neps
-
-
-def run_pipeline(learning_rate, optimizer, epochs):
-    """func for test loading of run_pipeline"""
-    if optimizer == "a":
-        eval_score = np.random.choice([learning_rate, epochs], 1)
-    else:
-        eval_score = 5.0
-    return {"loss": eval_score}
+from tests.test_yaml_run_args.test_declarative_usage_docs.run_pipeline import \
+    run_pipeline_constant
 
 
 if __name__ == "__main__":
@@ -17,5 +9,11 @@ def run_pipeline(learning_rate, optimizer, epochs):
         description="Run NEPS optimization with run_args.yml."
     )
     parser.add_argument("run_args", type=str, help="Path to the YAML configuration file.")
+    parser.add_argument("--run_pipeline", action="store_true")
     args = parser.parse_args()
-    neps.run(run_args=args.run_args)
+
+    if args.run_pipeline:
+        neps.run(run_args=args.run_args, run_pipeline=run_pipeline_constant)
+    else:
+        neps.run(run_args=args.run_args)
+
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_optimizer.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_optimizer.yaml
index 17bd4ab4..e6a3cea5 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_optimizer.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_optimizer.yaml
@@ -1,7 +1,7 @@
-# Basic NEPS Configuration Example
+# Optimizer settings from YAML configuration
 run_pipeline:
   path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  name: example_pipeline              # Function name within the file
 
 pipeline_space:
   learning_rate:
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_pipeline_space.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_pipeline_space.yaml
index 75e50c30..68558569 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_pipeline_space.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/outsourcing_pipeline_space.yaml
@@ -1,6 +1,7 @@
+# Pipeline space settings from YAML
 run_pipeline:
   path: path/to/your/run_pipeline.py  # Path to the function file
-  name: example_run                   # Function name within the file
+  name: example_pipeline              # Function name within the file
 
 pipeline_space: path/to/your/pipeline_space.yaml
 
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/pipeline_space.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/pipeline_space.yaml
index 5f416fbd..a4782db5 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/pipeline_space.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/pipeline_space.yaml
@@ -1,8 +1,22 @@
+# pipeline_space including priors and fidelity
 pipeline_space:
   learning_rate:
     lower: 1e-5
     upper: 1e-1
     log: True  # Log scale for learning rate
+    default: 1e-2
+    default_confidence: "medium"
+  epochs:
+    lower: 5
+    upper: 20
+    is_fidelity: True
+  dropout_rate:
+    lower: 0.1
+    upper: 0.5
+    default: 0.2
+    default_confidence: "high"
   optimizer:
     choices: [adam, sgd, adamw]
-  epochs: 50
+    default: adam
+    # default confidence low
+  batch_size: 64
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py b/tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
index b0b26c3d..f44e6e71 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
@@ -9,3 +9,13 @@ def run_pipeline(learning_rate, optimizer, epochs):
         eval_score = 5.0
     return {"loss": eval_score}
 
+
+def run_pipeline_constant(learning_rate, optimizer, epochs, batch_size):
+    """func for test loading of run_pipeline"""
+    if optimizer == "a":
+        eval_score = np.random.choice([learning_rate, epochs], 1)
+    else:
+        eval_score = 5.0
+    eval_score += batch_size
+    return {"loss": eval_score}
+
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example.yaml
index 77ceccb5..a167964c 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example.yaml
@@ -3,10 +3,17 @@ pipeline_space:
   learning_rate:
     lower: 1e-5
     upper: 1e-1
-    log: True
+    log: True  # Log scale for learning rate
+  epochs:
+    lower: 5
+    upper: 20
+    is_fidelity: True
   optimizer:
     choices: [adam, sgd, adamw]
-  epochs: 50
+  batch_size: 64
 
-root_directory: path/to/results       # Directory for result storage
+root_directory: path/to/results/simple_example       # Directory for result storage
 max_evaluations_total: 20             # Budget
+
+
+overwrite_working_directory: True
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example_including_run_pipeline.yaml b/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example_including_run_pipeline.yaml
index d46f95f4..53cde312 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example_including_run_pipeline.yaml
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/simple_example_including_run_pipeline.yaml
@@ -1,16 +1,22 @@
-# Extended NePS Configuration Example with External Pipeline Function
+# Simple NePS configuration including run_pipeline
 run_pipeline:
   path: tests/test_yaml_run_args/test_declarative_usage_docs/run_pipeline.py
-  name: run_pipeline
+  name: run_pipeline_constant
 
 pipeline_space:
   learning_rate:
     lower: 1e-5
     upper: 1e-1
-    log: True
+    log: True  # Log scale for learning rate
+  epochs:
+    lower: 5
+    upper: 20
+    is_fidelity: True
   optimizer:
     choices: [adam, sgd, adamw]
-  epochs: 50
+  batch_size: 64
 
-root_directory: path/to/results       # Directory for result storage
+root_directory: path/to/results/simple_example_including_run_pipeline       # Directory for result storage
 max_evaluations_total: 20             # Budget
+
+overwrite_working_directory: True
diff --git a/tests/test_yaml_run_args/test_declarative_usage_docs/test_declarative_usage_docs.py b/tests/test_yaml_run_args/test_declarative_usage_docs/test_declarative_usage_docs.py
index c8459b6c..ad6d94f7 100644
--- a/tests/test_yaml_run_args/test_declarative_usage_docs/test_declarative_usage_docs.py
+++ b/tests/test_yaml_run_args/test_declarative_usage_docs/test_declarative_usage_docs.py
@@ -1,6 +1,6 @@
 import pytest
-import subprocess
 import os
+import subprocess
 import sys
 BASE_PATH = "tests/test_yaml_run_args/test_declarative_usage_docs/"
 
@@ -8,15 +8,38 @@
 @pytest.mark.neps_api
 @pytest.mark.parametrize("yaml_file", [
     "simple_example_including_run_pipeline.yaml",
-    "full_configuration_template.yaml"
+    "full_configuration_template.yaml",
+    "defining_hooks.yaml"
 ])
 def test_run_with_yaml(yaml_file: str) -> None:
-    """Test "neps.run" with various run_args.yaml settings to simulate loading options
-    for variables."""
-    assert os.path.exists(BASE_PATH + yaml_file), f"{yaml_file} does not exist."
+    """
+    Test 'neps.run' with various run_args.yaml settings to simulate loading options
+    for variables.
+    """
+    yaml_path = os.path.join(BASE_PATH, yaml_file)
+    assert os.path.exists(yaml_path), f"{yaml_file} does not exist."
+
+    try:
+        subprocess.check_call(
+            [sys.executable, BASE_PATH + 'neps_run.py', yaml_path])
+    except subprocess.CalledProcessError as e:
+        pytest.fail(
+            f"NePS run failed for configuration: {yaml_file} with error: {str(e)}")
+
+
+@pytest.mark.neps_api
+def test_run_with_yaml_and_run_pipeline() -> None:
+    """
+    Test 'neps.run' with simple_example.yaml as run_args + a run_pipeline that is
+    provided separately.
+    """
+    yaml_path = os.path.join(BASE_PATH, "simple_example.yaml")
+    assert os.path.exists(yaml_path), f"{yaml_path} does not exist."
 
     try:
-        subprocess.check_call([sys.executable, BASE_PATH + 'neps_run.py', BASE_PATH +
-                               yaml_file])
-    except subprocess.CalledProcessError:
-        pytest.fail(f"NePS run failed for configuration: {yaml_file}")
+        subprocess.check_call(
+            [sys.executable, BASE_PATH + 'neps_run.py', yaml_path, "--run_pipeline"]
+        )
+    except subprocess.CalledProcessError as e:
+        pytest.fail(
+            f"NePS run failed for configuration: simple_example.yaml with error: {str(e)}")
diff --git a/tests/test_yaml_run_args/test_yaml_run_args.py b/tests/test_yaml_run_args/test_yaml_run_args.py
index c9d3901e..6ebb7ddc 100644
--- a/tests/test_yaml_run_args/test_yaml_run_args.py
+++ b/tests/test_yaml_run_args/test_yaml_run_args.py
@@ -12,7 +12,6 @@
                       batch_size=neps.ConstantParameter(value=64))
 
 
-
 def run_pipeline():
     """func to test loading of run_pipeline"""
     return