diff --git a/modules/deepbgc/download/main.nf b/modules/deepbgc/download/main.nf
index 1da817a6..bf0a4904 100644
--- a/modules/deepbgc/download/main.nf
+++ b/modules/deepbgc/download/main.nf
@@ -1,5 +1,4 @@
 process DEEPBGC_DOWNLOAD {
-    tag "download"
     label 'process_low'
 
     conda (params.enable_conda ? "bioconda::deepbgc=0.1.30" : null)
@@ -8,8 +7,8 @@ process DEEPBGC_DOWNLOAD {
         'quay.io/biocontainers/deepbgc:0.1.30--pyhb7b1952_1' }"
 
     output:
-    path "deepbgc_db/"             , emit: db
-    path "versions.yml"           , emit: versions
+    path "deepbgc_db/"  , emit: db
+    path "versions.yml" , emit: versions
 
     when:
     task.ext.when == null || task.ext.when
diff --git a/modules/deepbgc/download/meta.yml b/modules/deepbgc/download/meta.yml
index 5089142d..c2d74aa6 100644
--- a/modules/deepbgc/download/meta.yml
+++ b/modules/deepbgc/download/meta.yml
@@ -1,13 +1,13 @@
 name: "deepbgc_download"
-description: database to detect BGCs in bacterial and fungal genomes using deep learning
+description: Database download module for DeepBGC which detects BGCs in bacterial and fungal genomes using deep learning.
 keywords:
   - database
   - download
   - BGC
-  - Biosynthetic Gene Cluster
+  - biosynthetic gene cluster
   - deep learning
   - neural network
-  - random forrest
+  - random forest
   - genomes
   - bacteria
   - fungi
@@ -27,8 +27,8 @@ output:
       pattern: "versions.yml"
   - deepbgc_db:
       type: directory
-      description: contains files of reference db from 'deepbgc download'
-      pattern: "*db"
+      description: Contains reference database files
+      pattern: "deepbgc_db"
 
 authors:
   - "@louperelo"
diff --git a/modules/deepbgc/pipeline/meta.yml b/modules/deepbgc/pipeline/meta.yml
index 6a9a2b6c..fb388661 100644
--- a/modules/deepbgc/pipeline/meta.yml
+++ b/modules/deepbgc/pipeline/meta.yml
@@ -1,7 +1,8 @@
 name: "deepbgc_pipeline"
-description: detect BGCs in bacterial and fungal genomes using deep learning
+description: DeepBGC detects BGCs in bacterial and fungal genomes using deep learning.
 keywords:
-  - Biosynthetic Gene Cluster
+  - BGC
+  - biosynthetic gene cluster
   - deep learning
   - neural network
   - random forest
@@ -48,15 +49,15 @@ output:
       pattern: "*.{txt}"
   - json:
       type: file
-      description: AntiSMASH JSON file for sideloading.
+      description: AntiSMASH JSON file for sideloading
       pattern: "*.{json}"
   - bgc_gbk:
       type: file
-      description: Sequences and features of all detected BGCs in GenBank format.
+      description: Sequences and features of all detected BGCs in GenBank format
       pattern: "*.{bgc.gbk}"
   - bgc_tsv:
       type: file
-      description: Table of detected BGCs and their properties.
+      description: Table of detected BGCs and their properties
       pattern: "*.{bgc.tsv}"
   - full_gbk:
       type: file
@@ -64,23 +65,23 @@ output:
       pattern: "*.{full.gbk}"
   - pfam_tsv:
       type: file
-      description: Table of Pfam domains (pfam_id) from given sequence (sequence_id) in genomic order, with BGC detection scores.
+      description: Table of Pfam domains (pfam_id) from given sequence (sequence_id) in genomic order, with BGC detection scores
       pattern: "*.{pfam.tsv}"
   - bgc_png:
       type: file
-      description: Detected BGCs plotted by their nucleotide coordinates.
+      description: Detected BGCs plotted by their nucleotide coordinates
       pattern: "*.{bgc.png}"
   - pr_png:
       type: file
-      description: Precision-Recall curve based on predicted per-Pfam BGC scores.
+      description: Precision-Recall curve based on predicted per-Pfam BGC scores
       pattern: "*.{pr.png}"
   - roc_png:
       type: file
-      description: ROC curve based on predicted per-Pfam BGC scores.
+      description: ROC curve based on predicted per-Pfam BGC scores
       pattern: "*.{roc.png}"
   - score_png:
       type: file
-      description: BGC detection scores of each Pfam domain in genomic order.
+      description: BGC detection scores of each Pfam domain in genomic order
       pattern: "*.{score.png}"
 
 authors: