diff --git a/config/README.md b/config/README.md
index 41d2a15..32d9a64 100644
--- a/config/README.md
+++ b/config/README.md
@@ -2,13 +2,14 @@ The `config` folder contains configuration files which customize default **PyAut
 
 # Folders
 
-- `grids`: Configs for default behaviour of grids when used for ray-tracing.
-- `non-linear`: Configs for default non-linear search (e.g. MCMC, nested sampling) settings.
-- `notation`: Configs defining labels and formatting of model parameters when used for visualization.
+- `non_linear`: Configs for default non-linear search (e.g. MCMC, nested sampling) settings.
 - `priors`: Configs defining default priors assumed on every model component and set of parameters.
 - `visualize`: Configs defining what images are output by a model fit.
+- `build`: Configs used by the automated build and test system (not relevant to normal use).
 
 # Files
 
 - `general.yaml`: Customizes general **PyAutoLens** settings.
 - `logging.yaml`: Customizes the logging behaviour of **PyAutoLens**.
+- `notation.yaml`: Defines labels and formatting of model parameters when used for visualization.
+- `output.yaml`: Customizes what a model-fit writes to the output folder.
diff --git a/config/non_linear/README.md b/config/non_linear/README.md
index f69c3b3..c7e7a57 100644
--- a/config/non_linear/README.md
+++ b/config/non_linear/README.md
@@ -1,8 +1,9 @@
-The `non_linear` folder contains configuration files which customize the default behaviour of non-linear searches in
-**PyAutoLens**.
+The `non_linear` folder contains configuration files which customize the default behaviour of non-linear
+searches in **PyAutoLens**.
+
+Defaults for individual searches (e.g. Nautilus, Emcee, LBFGS) ship with **PyAutoFit** itself; this folder
+holds only the workspace-level overrides.
 
 # Files
 
-- `mcmc.yaml`: Settings default behaviour of MCMC non-linear searches (e.g. Emcee).
-- `nest.yaml`: Settings default behaviour of nested sampler non-linear searches (e.g. Dynesty).
-- `mle.yaml`: Settings default behaviour of maximum likelihood estimator (mle) searches (e.g. LBFGS).
+- `GridSearch.yaml`: Settings for the non-linear search grid search.
diff --git a/config/visualize/README.md b/config/visualize/README.md
index 6fa8589..b0a4869 100644
--- a/config/visualize/README.md
+++ b/config/visualize/README.md
@@ -1,11 +1,7 @@
-The `config` folder contains configuration files which customize default **PyAutoLens**.
+The `visualize` folder contains configuration files which customize what a model-fit outputs.
 
 # Files
 
 - `general.yaml`: Customizes general visualization settings (e.g. the matplotlib backend).
-- `include.yaml`: Customize features that appears on plotted images by default (e.g. a mask, a grid).
 - `plots.yaml`: Customize which figures are output during a model-fit.
 - `plots_search.yaml`: Customize which non-linear search figures are output during a model-fit.
-- `mat_wrap.yaml`: Specify the default matplotlib settings when figures and subplots are plotted.
-- `mat_wrap_1d.yaml`: Specify the default matplotlib settings when 1D figures and subplots are plotted.
-- `mat_wrap_2d.yaml`: Specify the default matplotlib settings when 2D figures and subplots are plotted.
diff --git a/notebooks/README.md b/notebooks/README.md
index 56dd067..c103a00 100644
--- a/notebooks/README.md
+++ b/notebooks/README.md
@@ -7,7 +7,6 @@ a strong lens.
 - `chapter_2_lens_modeling`: How to model strong lenses, including a primer on Bayesian non-linear analysis.
 - `chapter_3_search_chaining`: How to fit complex lens models using non-linear search chaining.
 - `chapter_4_pixelizations`: How to perform pixelized reconstructions of the source-galaxy.
-- `chapter_5_hyper_mode`: How to use **PyAutoLens** advanced modeling features that adapt the model to the strong lens being analysed.
 - `chapter_optional`: Optional tutorials.
 
 # Full Explanation
diff --git a/scripts/README.md b/scripts/README.md
index 56dd067..c103a00 100644
--- a/scripts/README.md
+++ b/scripts/README.md
@@ -7,7 +7,6 @@ a strong lens.
 - `chapter_2_lens_modeling`: How to model strong lenses, including a primer on Bayesian non-linear analysis.
 - `chapter_3_search_chaining`: How to fit complex lens models using non-linear search chaining.
 - `chapter_4_pixelizations`: How to perform pixelized reconstructions of the source-galaxy.
-- `chapter_5_hyper_mode`: How to use **PyAutoLens** advanced modeling features that adapt the model to the strong lens being analysed.
 - `chapter_optional`: Optional tutorials.
 
 # Full Explanation