Bio Agent Skills Hub
A router/index skill over 1,676 deduplicated biomedical AI agent skills, aggregated and
deduplicated from 20 open-source repositories into 15 categories. Each skill is a
self-contained SKILL.md folder compatible with Claude-based agent frameworks.
This skill does not duplicate the 1,676 skills. It tells the agent how to (1) search the
index, (2) locate the single best-matching skill, (3) fetch that skill's SKILL.md on
demand, and (4) follow it. Skill bodies are fetched from GitHub on demand; a git clone
fallback (incl. a China mirror) is provided for offline / bulk / private use.
How to use this skill (router workflow)
When a user asks for any bioinformatics task, workflow, or analysis:
Step 1 — Search the index to find candidate skills
The index has columns: skill_name, folder_name, source_repo, category, description, file_count, archive_path.
archive_path = <source_repo>/<folder_name> and is the path under skills/.
Search skill_name + description + category + source_repo together (descriptions contain
rich "Use when..." text), and present ranked candidates with their category and archive_path
so the right one can be chosen:
import pandas as pd
# Authoritative v3 index. Prefer a local copy if this skill bundles one; else read from GitHub raw.
INDEX_URL = "https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/bioskill_index_v3.csv"
df = pd.read_csv(INDEX_URL) # 1,676 rows
def search_skills(query, category=None, source=None, top=15):
"""Keyword search over name+description+category+source. Returns candidate skills."""
q = query.lower()
hay = (df["skill_name"].fillna("") + " | " +
df["description"].fillna("") + " | " +
df["category"].fillna("") + " | " +
df["source_repo"].fillna("")).str.lower()
hits = df[hay.str.contains(q, regex=False)].copy()
if category:
hits = hits[hits["category"] == category]
if source:
hits = hits[hits["source_repo"] == source]
# rank: name match first, then description match
hits["_name_hit"] = hits["skill_name"].str.lower().str.contains(q, regex=False)
hits = hits.sort_values(["_name_hit", "file_count"], ascending=[False, False])
return hits[["skill_name", "category", "source_repo", "archive_path", "description"]].head(top)
print(search_skills("variant calling").to_string(index=False))
If nothing matches, broaden the query (try a synonym), or filter by category (see the table below)
and browse that category's README section.
Step 2 — Fetch the chosen skill's SKILL.md (content on demand)
Once you pick a candidate's archive_path (e.g. bioskills/clair3-variants):
import urllib.request
archive_path = "bioskills/clair3-variants" # from the search result
url = f"https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/{archive_path}/SKILL.md"
skill_md = urllib.request.urlopen(url, timeout=30).read().decode()
print(skill_md) # read it, then follow its instructions
Some skills ship supporting files (scripts/, references/); list a folder via the GitHub API or
clone it (Step 3) if you need them.
Step 3 — Offline / bulk / private fallback (clone)
If raw fetch is unavailable, or you want all supporting files, clone and copy the skill folder:
Standard (international):
git clone https://github.com/BioTender-max/awesome-bio-agent-skills.git
cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/
China-accelerated (ghfast.top mirror) — prepend the mirror to the GitHub URL; works for cloning
this or any source repo (https://ghfast.top/https://github.com/<owner>/<repo>.git):
git clone https://ghfast.top/https://github.com/BioTender-max/awesome-bio-agent-skills.git
cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/
Categories (15) — counts and where to browse
Filter searches with the category key (left column). README section links jump to the
browsable table for that category.
Category (key) |
Skills |
README section |
Topics |
genomics |
526 |
Genomics |
WGS/WES, variant calling, GWAS, CNV, structural variants, alignment, assembly |
biology-other |
236 |
Biology and AI |
Drug discovery, molecular docking, protein binder design, cheminformatics |
proteomics |
167 |
Proteomics |
Mass spectrometry, structure prediction (AlphaFold/ESM), binding affinity |
clinical |
152 |
Clinical and Medical |
EHR, clinical trials, survival analysis, ACMG, precision medicine |
single-cell |
144 |
Single-Cell Analysis |
scRNA-seq QC, clustering, trajectory, cell communication, spatial, multimodal |
transcriptomics |
97 |
Transcriptomics |
Bulk RNA-seq, differential expression, splicing, lncRNA, isoforms |
bioinformatics-general |
86 |
Bioinformatics Utilities |
BLAST, MSA, phylogenetics, sequence utilities, stats libraries |
multi-omics |
69 |
Multi-Omics Integration |
MOFA, DIABLO, integration, spatial multi-omics |
database-query |
63 |
Database Query |
UniProt, PDB, KEGG, Reactome, GEO, ClinVar, Ensembl, dbSNP |
visualization |
48 |
Visualization |
Volcano plots, heatmaps, UMAP, genome tracks, interactive charts |
workflow |
38 |
Workflow Orchestration |
Snakemake, Nextflow, CWL, WDL, HPC orchestration, lab automation |
epigenomics |
19 |
Epigenomics |
ChIP-seq, ATAC-seq, DNA methylation, Hi-C, chromatin state |
pathway |
15 |
Pathway Analysis |
KEGG, Reactome, GO enrichment, GSEA |
metagenomics |
9 |
Metagenomics |
16S, Kraken2/Bracken, MetaPhlAn, QIIME2 |
protein-design |
7 |
Protein Design |
RFdiffusion, ProteinMPNN, Boltz, Chai, LigandMPNN |
Source repositories (20)
Skills are aggregated and deduplicated from these repositories. Use the source_repo key to
filter the index. (bio-agent-skills-hub is this self-referential hub entry.)
Source repo (source_repo) |
Skills |
Focus |
bioskills — GPTomics/bioSkills |
536 |
Systematic bioinformatics suite from QC to multi-omics. |
openclaw — FreedomIntelligence/OpenClaw-Medical-Skills |
359 |
Medical AI library aggregating 12 specialized sub-repositories. |
sciagent — jaechang-hits/SciAgent-Skills |
154 |
Statistics, databases, and clinical decision skills. |
kdense — K-Dense-AI/scientific-agent-skills |
102 |
General scientific computing and HPC workflow skills. |
neuroclaw — CUHK-AIM-Group/NeuroClaw |
86 |
Neuroimaging: sMRI, fMRI, dMRI, EEG (BIDS, FreeSurfer, FSL, fMRIPrep). |
clawbio — ClawBio/ClawBio |
63 |
Bioinformatics workflow orchestration for GWAS and single-cell. |
labclaw — wu-yc/LabClaw |
59 |
Lab automation and biomedical research skills. |
drugclaw — QSong-github/DrugClaw |
57 |
Drug intelligence: DTI, ADR, DDI, pharmacogenomics, repurposing. |
nobel — ChrisLou-bioinfo/nobel-medicine-minds |
55 |
Cognitive frameworks of Nobel Medicine laureates as SKILL.md. |
bioclaw_hub — zongtingwei/Bioclaw_Skills_Hub |
46 |
Ten-category biological skills hub. |
bioclaw — Runchuan-BU/BioClaw |
37 |
Core bioinformatics tools and database query skills. |
omics — fmschulz/omics-skills |
29 |
Single-cell and spatial omics specialized skills. |
omicsclaw — TianGzlab/OmicsClaw |
28 |
6-omics domain skills: spatial, scRNA, bulk RNA, genomics, proteomics, metabolomics. |
adaptyv — adaptyvbio/protein-design-skills |
21 |
Protein design toolkit: RFdiffusion, ProteinMPNN, Boltz, Chai. |
pantheon — aristoteleo/PantheonOS |
18 |
Single-cell and spatial transcriptomics (Dynamo/Spateo team). |
evoskills — EvoScientist/EvoSkills |
13 |
Research-lifecycle skills: ideation, planning, execution, writing, review. |
medgeclaw — xjtulyc/MedgeClaw |
7 |
Biomedical research skills with dashboard, RStudio, JupyterLab integration. |
zamushwani — zamushwani2/biomedical-ai-skills |
4 |
Cancer multi-omics analysis skills in R. |
bio-agent-skills-hub — BioTender-max/awesome-bio-agent-skills |
1 |
Self-referential hub skill that indexes this collection. |
sragent — ArcInstitute/SRAgent |
1 |
Intelligent SRA and GEO dataset retrieval. |
Example interactions
User: "I need a GWAS pipeline."
Agent: search_skills("gwas") → top hit bio-workflows-gwas-pipeline (genomics,
bioskills/gwas-pipeline); also gwas-pipeline (clawbio/gwas-pipeline) and plink2-gwas-analysis
(sciagent/plink2-gwas-analysis). Fetch
https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/bioskills/gwas-pipeline/SKILL.md and follow it. Browse more: https://github.com/BioTender-max/awesome-bio-agent-skills#genomics
User: "Preprocess and cluster my scRNA-seq data."
Agent: search_skills("scrna preprocessing", category="single-cell") →
scrna-preprocessing-clustering (bioclaw/scrna-preprocessing-clustering). Fetch its SKILL.md and
follow it. 144 single-cell skills total: https://github.com/BioTender-max/awesome-bio-agent-skills#single-cell-analysis
User: "Design a protein binder backbone."
Agent: search_skills("rfdiffusion") → rfdiffusion (protein-design, adaptyv/rfdiffusion).
Related: proteinmpnn (adaptyv/proteinmpnn), bindcraft (adaptyv/bindcraft). Fetch the SKILL.md
for the chosen tool. Browse: https://github.com/BioTender-max/awesome-bio-agent-skills#protein-design
User: "Call variants from long reads."
Agent: search_skills("variant calling", category="genomics") →
bio-long-read-sequencing-clair3-variants (bioskills/clair3-variants); for short reads see
bio-variant-calling-deepvariant (bioskills/deepvariant). Fetch and follow.
Notes
- The index (
bioskill_index_v3.csv) is the single source of truth for what exists and where; always
resolve archive_path from it rather than guessing folder names.
- Counts above (1,676 skills / 20 sources / 15 categories) match the repository README and index.
- Content fetch requires network access and a public repository; use the clone fallback otherwise.
1---2name: bio-agent-skills-hub3description: Discover and invoke 1,676 deduplicated biomedical AI agent skills from the Awesome Bio Agent Skills repository (20 source repos, 15 categories). Use this skill as a router whenever a user needs a bioinformatics/biomedical task (genomics, transcriptomics, single-cell, proteomics, protein design, clinical, epigenomics, multi-omics, pathway, metagenomics, database queries, visualization, workflows): search the index, locate the best-matching skill, fetch its SKILL.md, and follow it.4---5
6# Bio Agent Skills Hub
7
8A **router/index skill** over **1,676 deduplicated biomedical AI agent skills**, aggregated and
9deduplicated from **20 open-source repositories** into **15 categories**. Each skill is a
10self-contained `SKILL.md` folder compatible with Claude-based agent frameworks.
11
12- Repository: **https://github.com/BioTender-max/awesome-bio-agent-skills**
13- Machine-readable index (authoritative): **`https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/bioskill_index_v3.csv`** (1,676 rows)
14
15> This skill does **not** duplicate the 1,676 skills. It tells the agent how to (1) **search** the
16> index, (2) **locate** the single best-matching skill, (3) **fetch** that skill's `SKILL.md` on
17> demand, and (4) **follow** it. Skill bodies are fetched from GitHub on demand; a `git clone`
18> fallback (incl. a China mirror) is provided for offline / bulk / private use.
19
20---
21
22## How to use this skill (router workflow)
23
24When a user asks for any bioinformatics task, workflow, or analysis:
25
26### Step 1 — Search the index to find candidate skills
27
28The index has columns: `skill_name, folder_name, source_repo, category, description, file_count, archive_path`.
29`archive_path` = `<source_repo>/<folder_name>` and is the path under `skills/`.
30
31Search **`skill_name` + `description` + `category` + `source_repo`** together (descriptions contain
32rich "Use when..." text), and present ranked candidates with their **category** and **`archive_path`**
33so the right one can be chosen:
34
35```python
36import pandas as pd
37
38# Authoritative v3 index. Prefer a local copy if this skill bundles one; else read from GitHub raw.
39INDEX_URL = "https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/bioskill_index_v3.csv"
40df = pd.read_csv(INDEX_URL) # 1,676 rows
41
42def search_skills(query, category=None, source=None, top=15):
43 """Keyword search over name+description+category+source. Returns candidate skills."""
44 q = query.lower()
45 hay = (df["skill_name"].fillna("") + " | " +
46 df["description"].fillna("") + " | " +
47 df["category"].fillna("") + " | " +
48 df["source_repo"].fillna("")).str.lower()
49 hits = df[hay.str.contains(q, regex=False)].copy()
50 if category:
51 hits = hits[hits["category"] == category]
52 if source:
53 hits = hits[hits["source_repo"] == source]
54 # rank: name match first, then description match
55 hits["_name_hit"] = hits["skill_name"].str.lower().str.contains(q, regex=False)
56 hits = hits.sort_values(["_name_hit", "file_count"], ascending=[False, False])
57 return hits[["skill_name", "category", "source_repo", "archive_path", "description"]].head(top)
58
59print(search_skills("variant calling").to_string(index=False))
60```
61
62If nothing matches, broaden the query (try a synonym), or filter by `category` (see the table below)
63and browse that category's README section.
64
65### Step 2 — Fetch the chosen skill's SKILL.md (content on demand)
66
67Once you pick a candidate's `archive_path` (e.g. `bioskills/clair3-variants`):
68
69```python
70import urllib.request
71
72archive_path = "bioskills/clair3-variants" # from the search result
73url = f"https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/{archive_path}/SKILL.md"
74skill_md = urllib.request.urlopen(url, timeout=30).read().decode()
75print(skill_md) # read it, then follow its instructions
76```
77
78Some skills ship supporting files (`scripts/`, `references/`); list a folder via the GitHub API or
79clone it (Step 3) if you need them.
80
81### Step 3 — Offline / bulk / private fallback (clone)
82
83If raw fetch is unavailable, or you want all supporting files, clone and copy the skill folder:
84
85**Standard (international):**
86```bash
87git clone https://github.com/BioTender-max/awesome-bio-agent-skills.git
88cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/
89```
90
91**China-accelerated (ghfast.top mirror)** — prepend the mirror to the GitHub URL; works for cloning
92this or any source repo (`https://ghfast.top/https://github.com/<owner>/<repo>.git`):
93```bash
94git clone https://ghfast.top/https://github.com/BioTender-max/awesome-bio-agent-skills.git
95cp -r awesome-bio-agent-skills/skills/<archive_path>/ /path/to/your/agent/skills/
96```
97
98---
99
100## Categories (15) — counts and where to browse
101
102Filter searches with the `category` **key** (left column). README section links jump to the
103browsable table for that category.
104
105| Category (`key`) | Skills | README section | Topics |
106|------------------|-------:|----------------|--------|
107| `genomics` | 526 | [Genomics](https://github.com/BioTender-max/awesome-bio-agent-skills#genomics) | WGS/WES, variant calling, GWAS, CNV, structural variants, alignment, assembly |
108| `biology-other` | 236 | [Biology and AI](https://github.com/BioTender-max/awesome-bio-agent-skills#biology-and-ai) | Drug discovery, molecular docking, protein binder design, cheminformatics |
109| `proteomics` | 167 | [Proteomics](https://github.com/BioTender-max/awesome-bio-agent-skills#proteomics) | Mass spectrometry, structure prediction (AlphaFold/ESM), binding affinity |
110| `clinical` | 152 | [Clinical and Medical](https://github.com/BioTender-max/awesome-bio-agent-skills#clinical-and-medical) | EHR, clinical trials, survival analysis, ACMG, precision medicine |
111| `single-cell` | 144 | [Single-Cell Analysis](https://github.com/BioTender-max/awesome-bio-agent-skills#single-cell-analysis) | scRNA-seq QC, clustering, trajectory, cell communication, spatial, multimodal |
112| `transcriptomics` | 97 | [Transcriptomics](https://github.com/BioTender-max/awesome-bio-agent-skills#transcriptomics) | Bulk RNA-seq, differential expression, splicing, lncRNA, isoforms |
113| `bioinformatics-general` | 86 | [Bioinformatics Utilities](https://github.com/BioTender-max/awesome-bio-agent-skills#bioinformatics-utilities) | BLAST, MSA, phylogenetics, sequence utilities, stats libraries |
114| `multi-omics` | 69 | [Multi-Omics Integration](https://github.com/BioTender-max/awesome-bio-agent-skills#multi-omics-integration) | MOFA, DIABLO, integration, spatial multi-omics |
115| `database-query` | 63 | [Database Query](https://github.com/BioTender-max/awesome-bio-agent-skills#database-query) | UniProt, PDB, KEGG, Reactome, GEO, ClinVar, Ensembl, dbSNP |
116| `visualization` | 48 | [Visualization](https://github.com/BioTender-max/awesome-bio-agent-skills#visualization) | Volcano plots, heatmaps, UMAP, genome tracks, interactive charts |
117| `workflow` | 38 | [Workflow Orchestration](https://github.com/BioTender-max/awesome-bio-agent-skills#workflow-orchestration) | Snakemake, Nextflow, CWL, WDL, HPC orchestration, lab automation |
118| `epigenomics` | 19 | [Epigenomics](https://github.com/BioTender-max/awesome-bio-agent-skills#epigenomics) | ChIP-seq, ATAC-seq, DNA methylation, Hi-C, chromatin state |
119| `pathway` | 15 | [Pathway Analysis](https://github.com/BioTender-max/awesome-bio-agent-skills#pathway-analysis) | KEGG, Reactome, GO enrichment, GSEA |
120| `metagenomics` | 9 | [Metagenomics](https://github.com/BioTender-max/awesome-bio-agent-skills#metagenomics) | 16S, Kraken2/Bracken, MetaPhlAn, QIIME2 |
121| `protein-design` | 7 | [Protein Design](https://github.com/BioTender-max/awesome-bio-agent-skills#protein-design) | RFdiffusion, ProteinMPNN, Boltz, Chai, LigandMPNN |
122
123---
124
125## Source repositories (20)
126
127Skills are aggregated and deduplicated from these repositories. Use the `source_repo` **key** to
128filter the index. (`bio-agent-skills-hub` is this self-referential hub entry.)
129
130| Source repo (`source_repo`) | Skills | Focus |
131|-----------------------------|-------:|-------|
132| `bioskills` — [GPTomics/bioSkills](https://github.com/GPTomics/bioSkills) | 536 | Systematic bioinformatics suite from QC to multi-omics. |
133| `openclaw` — [FreedomIntelligence/OpenClaw-Medical-Skills](https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills) | 359 | Medical AI library aggregating 12 specialized sub-repositories. |
134| `sciagent` — [jaechang-hits/SciAgent-Skills](https://github.com/jaechang-hits/SciAgent-Skills) | 154 | Statistics, databases, and clinical decision skills. |
135| `kdense` — [K-Dense-AI/scientific-agent-skills](https://github.com/K-Dense-AI/scientific-agent-skills) | 102 | General scientific computing and HPC workflow skills. |
136| `neuroclaw` — [CUHK-AIM-Group/NeuroClaw](https://github.com/CUHK-AIM-Group/NeuroClaw) | 86 | Neuroimaging: sMRI, fMRI, dMRI, EEG (BIDS, FreeSurfer, FSL, fMRIPrep). |
137| `clawbio` — [ClawBio/ClawBio](https://github.com/ClawBio/ClawBio) | 63 | Bioinformatics workflow orchestration for GWAS and single-cell. |
138| `labclaw` — [wu-yc/LabClaw](https://github.com/wu-yc/LabClaw) | 59 | Lab automation and biomedical research skills. |
139| `drugclaw` — [QSong-github/DrugClaw](https://github.com/QSong-github/DrugClaw) | 57 | Drug intelligence: DTI, ADR, DDI, pharmacogenomics, repurposing. |
140| `nobel` — [ChrisLou-bioinfo/nobel-medicine-minds](https://github.com/ChrisLou-bioinfo/nobel-medicine-minds) | 55 | Cognitive frameworks of Nobel Medicine laureates as SKILL.md. |
141| `bioclaw_hub` — [zongtingwei/Bioclaw_Skills_Hub](https://github.com/zongtingwei/Bioclaw_Skills_Hub) | 46 | Ten-category biological skills hub. |
142| `bioclaw` — [Runchuan-BU/BioClaw](https://github.com/Runchuan-BU/BioClaw) | 37 | Core bioinformatics tools and database query skills. |
143| `omics` — [fmschulz/omics-skills](https://github.com/fmschulz/omics-skills) | 29 | Single-cell and spatial omics specialized skills. |
144| `omicsclaw` — [TianGzlab/OmicsClaw](https://github.com/TianGzlab/OmicsClaw) | 28 | 6-omics domain skills: spatial, scRNA, bulk RNA, genomics, proteomics, metabolomics. |
145| `adaptyv` — [adaptyvbio/protein-design-skills](https://github.com/adaptyvbio/protein-design-skills) | 21 | Protein design toolkit: RFdiffusion, ProteinMPNN, Boltz, Chai. |
146| `pantheon` — [aristoteleo/PantheonOS](https://github.com/aristoteleo/PantheonOS) | 18 | Single-cell and spatial transcriptomics (Dynamo/Spateo team). |
147| `evoskills` — [EvoScientist/EvoSkills](https://github.com/EvoScientist/EvoSkills) | 13 | Research-lifecycle skills: ideation, planning, execution, writing, review. |
148| `medgeclaw` — [xjtulyc/MedgeClaw](https://github.com/xjtulyc/MedgeClaw) | 7 | Biomedical research skills with dashboard, RStudio, JupyterLab integration. |
149| `zamushwani` — [zamushwani2/biomedical-ai-skills](https://github.com/zamushwani2/biomedical-ai-skills) | 4 | Cancer multi-omics analysis skills in R. |
150| `bio-agent-skills-hub` — [BioTender-max/awesome-bio-agent-skills](https://github.com/BioTender-max/awesome-bio-agent-skills) | 1 | Self-referential hub skill that indexes this collection. |
151| `sragent` — [ArcInstitute/SRAgent](https://github.com/ArcInstitute/SRAgent) | 1 | Intelligent SRA and GEO dataset retrieval. |
152
153---
154
155## Example interactions
156
157**User:** "I need a GWAS pipeline."
158**Agent:** `search_skills("gwas")` → top hit `bio-workflows-gwas-pipeline` (`genomics`,
159`bioskills/gwas-pipeline`); also `gwas-pipeline` (`clawbio/gwas-pipeline`) and `plink2-gwas-analysis`
160(`sciagent/plink2-gwas-analysis`). Fetch
161`https://raw.githubusercontent.com/BioTender-max/awesome-bio-agent-skills/main/skills/bioskills/gwas-pipeline/SKILL.md` and follow it. Browse more: https://github.com/BioTender-max/awesome-bio-agent-skills#genomics
162
163**User:** "Preprocess and cluster my scRNA-seq data."
164**Agent:** `search_skills("scrna preprocessing", category="single-cell")` →
165`scrna-preprocessing-clustering` (`bioclaw/scrna-preprocessing-clustering`). Fetch its SKILL.md and
166follow it. 144 single-cell skills total: https://github.com/BioTender-max/awesome-bio-agent-skills#single-cell-analysis
167
168**User:** "Design a protein binder backbone."
169**Agent:** `search_skills("rfdiffusion")` → `rfdiffusion` (`protein-design`, `adaptyv/rfdiffusion`).
170Related: `proteinmpnn` (`adaptyv/proteinmpnn`), `bindcraft` (`adaptyv/bindcraft`). Fetch the SKILL.md
171for the chosen tool. Browse: https://github.com/BioTender-max/awesome-bio-agent-skills#protein-design
172
173**User:** "Call variants from long reads."
174**Agent:** `search_skills("variant calling", category="genomics")` →
175`bio-long-read-sequencing-clair3-variants` (`bioskills/clair3-variants`); for short reads see
176`bio-variant-calling-deepvariant` (`bioskills/deepvariant`). Fetch and follow.
177
178---
179
180## Notes
181
182- The index (`bioskill_index_v3.csv`) is the single source of truth for what exists and where; always
183 resolve `archive_path` from it rather than guessing folder names.
184- Counts above (1,676 skills / 20 sources / 15 categories) match the repository README and index.
185- Content fetch requires network access and a public repository; use the clone fallback otherwise.