Arboreto
K-Dense-AI/scientific-agent-skills
Infers candidate gene regulatory networks from bulk or single-cell expression data using AertsLab Arboreto GRNBoost2 and GENIE3.
Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser.
Install Ucsc Conservation And Tfbs
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbs --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .claude/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .claude/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbs --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .agents/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .agents/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbs --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .cursor/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .cursor/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/google-deepmind/science-skills.git --path skills/ucsc_conservation_and_tfbs--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbs --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .gemini/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .gemini/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .github/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .github/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install google-deepmind/science-skills ucsc-conservation-and-tfbs --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/google-deepmind/science-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/ucsc_conservation_and_tfbs .opencode/skills/ucsc-conservation-and-tfbs && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "ucsc-conservation-and-tfbs" agent skill from https://github.com/google-deepmind/science-skills/tree/main/skills/ucsc_conservation_and_tfbs into .opencode/skills/ucsc-conservation-and-tfbs/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "ucsc-conservation-and-tfbs", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
ucsc-conservation-and-tfbs- GitHub stars
- 3.2k
- Used in
- 1 other repo
- Token cost
- ~1.9k tokens
- SKILL.md length
- 757 words
- Files
- 5 (incl. scripts, references)
- Skills in repo
- 40
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser.
- Works in 2 steps: uv: Read the uv skill and follow its… → User Notification: If…
- Analyzing whether genomic variants
- SKILL.md covers Prerequisites, Core Rules, Utility Scripts and Anti-Patterns
- Runs Python scripts from its folder; calls uv
What it does
Ucsc Conservation And Tfbs is an agent skill from google-deepmind/science-skills. Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing whether genomic variants or regions are evolutionarily conserved, functionally important, or bounded by TF regulators across major projects (ENCODE, JASPAR, ReMap).
Its SKILL.md is about 1.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files, including scripts and reference files (for example `scripts/get_conservation.py`, `scripts/get_tfbs.py` and `scripts/list_tracks.py`).
It sits in Research & Science, covering Bioinformatics, Transcription and Browser automation. The repository describes itself as: GDM Science Skills to speed up agentic scientific workflows with better grounding and higher token efficiency. Integrate insights from AlphaGenome, AFDB, UniProt and 30+ other… The licence is Apache-2.0.
When your agent uses it
- Analyzing whether genomic variants
- Regions are evolutionarily conserved
- Functionally important
- Bounded by TF regulators across major projects (ENCODE
Example prompts
- “/ucsc-conservation-and-tfbs”
Requirements
- Python 3
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- uv: Read the uv skill and follow its Setup instructions to ensure
- User Notification: If .licenses/ucsc_conservation_and_tfbs_LICENSE.txt
What it can do on your machine
Read from SKILL.md and the folder at commit 8ab7672. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships 3 files in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
uv
From the folder's file list and the shell code blocks in SKILL.md.
Network
Links to these hosts (documentation or services it may open):
genome.ucsc.edu
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Ucsc Conservation And Tfbs loads about 1.9k tokens when it runs, and up to ~2.1k if it reads all its reference files. Until then it costs about 86 tokens; SKILL.md has 757 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
SKILL.md
The full file from google-deepmind/science-skills at commit 8ab7672, republished under its Apache-2.0 licence (© google-deepmind). 757 words, ~1,928 tokens.
Download SKILL.mdSave it as
.claude/skills/ucsc-conservation-and-tfbs/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.- name
- ucsc-conservation-and-tfbs
- description
- Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Use when analyzing whether genomic variants or regions are evolutionarily conserved, functionally important, or bounded by TF regulators across major projects (ENCODE, JASPAR, ReMap).
Conservation Scores & TFBS Lookup (UCSC)
This skill provides access to evolutionary constraint scores and conserved
elements from the UCSC Genome Browser. It retrieves scores from the PHAST
package — specifically phastCons (identifying functional blocks) and phyloP
(measuring individual site constraint) — calculated from multiple alignments.
Use this skill to determine if a non-coding variant hits a site that hasn't changed since a common ancestor (which is a strong signal for pathogenicity) or to find conservation peaks across a regulatory element.
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If .licenses/ucsc_conservation_and_tfbs_LICENSE.txt does not already exist in the workspace root directory then (1) prominently notify the user to check the terms at https://genome.ucsc.edu/conditions.html and https://genome.ucsc.edu/goldenPath/help/api.html, then (2) create the file recording the notification text and timestamp.
Core Rules
- Use the Wrapper: ALWAYS execute the provided helper scripts to query the database rather than accessing the database directly. The scripts automatically enforce the required rate limit gracefully.
- Large Output Handling: Always pass --output to redirect output to a file. Parse it separately (using jq or your own code).
- Notification: If this skill is used, ensure this is mentioned in the output.
Utility Scripts
This skill includes scripts to query different types of genomic data from UCSC:
scripts/get_conservation.py: For Evolutionary Conservation scores (phyloP, phastCons).scripts/get_tfbs.py: For Transcription Factor Binding Sites (TFBS).scripts/list_tracks.py: For listing available tracks based on search or group constraints.
Always use the hg38 genome assembly by default, unless the user has specified
otherwise.
Fetching Conservation for Specific Variants
To get the evolutionary constraint at a single base, or a list of specific
bases. This is optimal for single nucleotide variants (SNVs). phyloP is the
best metric for individual bases.
uv run scripts/get_conservation.py --coordinates "chr1:215867804" "chr1:215867823" --output /tmp/cons_output.jsonFetching Regions and Conserved Elements
To identify "conservation peaks" across a non-coding regulatory element (like an
enhancer) to see if an ISM-predicted importance peak aligns with evolutionary
history. phastCons is best for functional windows due to HMM smoothing. The
--conserved-elements flag will also retrieve predefined blocks under extreme
constraint.
uv run scripts/get_conservation.py --coordinates "chr8:11748914-11749085" --conserved-elements --output /tmp/region_cons.jsonLineage-Specific Constraints
You can control the evolutionary depth using the --collection flag. The
default (vertebrate) uses the 100-vertebrate Multiz alignment for both
hg38 and hg19, matching the UCSC Genome Browser's default comparative genomics
tracks.
hg38 Collections
vertebrate(default): UCSC 100-vertebrate Multiz alignment. phyloP:phyloP100way, phastCons:phastCons100way.mammal: Hiller Lab 470-way mammalian alignment. phyloP:phyloP470wayBW, phastCons:phastCons470way.primate: UCSC 30-primate Multiz alignment. phyloP:phyloP30way, phastCons:phastCons30way.
hg19 Collections
vertebrate(default): UCSC 100-vertebrate Multiz alignment. phyloP:phyloP100way, phastCons:phastCons100way.vertebrate46: UCSC 46-vertebrate Multiz alignment (legacy). phyloP:phyloP46wayAll, phastCons:phastCons46way.mammal: 46-way placental mammal subset. phyloP:phyloP46wayPlacental, phastCons:phastCons46wayPlacental.primate: 46-way primate subset. phyloP:phyloP46wayPrimates, phastCons:phastCons46wayPrimates.
# hg38 mammal (Hiller 470-way)
uv run scripts/get_conservation.py --coordinates "chr5:1045330-1046172" --collection mammal --output /tmp/mammal_cons.json
# hg19 with legacy 46-vertebrate alignment
uv run scripts/get_conservation.py --coordinates "chr5:1045330-1046172" --genome hg19 --collection vertebrate46 --output /tmp/vert46_cons.jsonShow full SKILL.md (310 more words)Show less
Analyzing Evolutionary Acceleration
To analyze whether a specific locus is undergoing evolutionary acceleration
(i.e. evolving more rapidly than the neutral drift baseline), use --analyze.
This will compute scalar statistics (mean, min, max) for phyloP scores and
provide a heuristic boolean is_accelerated to simplify your evaluation.
uv run scripts/get_conservation.py --coordinates "chr5:1045330-1046172" --analyze --output /tmp/accelerated_cons.jsonFetching Transcription Factor Binding Sites (TFBS)
To identify transcription factor binding sites for a given genomic interval. This is useful for interpreting non-coding variants that might disrupt TF binding.
Run scripts/get_tfbs.py with --coordinates and --tracks. You can query
multiple tracks at once.
uv run scripts/get_tfbs.py --coordinates "chr11:1001000-1010000" --tracks encRegTfbsClustered --output /tmp/tfbs_encode.jsonJASPAR tracks may return very large result sets. Use --tf-filter to keep only
items whose TFName field contains the given substring (case-insensitive):
uv run scripts/get_tfbs.py --coordinates "chr6:36670000-36690000" --tracks jaspar2024 --tf-filter TP53 --output /tmp/tp53_sites.jsonCommon Verified Tracks (hg38)
- ENCODE:
encRegTfbsClustered(TF Clusters) - JASPAR:
jaspar2026,jaspar2024(Predicted TFBS) - ReMap:
ReMapTFs(ChIP-seq Atlas)
[!CAUTION] Tracks like
jasparorReMapwithout years are often "container" tracks and will fail with a 400 error. Always use the specific subtrack name (e.g.,jaspar2026).
Listing Available Tracks
To list available tracks (such as different versions of JASPAR, or purely to discover what tracks exist for a particular genome assembly):
uv run scripts/list_tracks.py --search "jaspar" --output /tmp/jaspar_tracks.jsonYou can also filter by functional group:
uv run scripts/list_tracks.py --group "regulation" --output /tmp/regulation_tracks.jsonAnti-Patterns
- DON'T query mammalian (
--collection mammal) constraint if you are explicitly looking for deep evolutionary roots across all vertebrates. Use the defaultvertebratecollection. - DON'T use this skill for determining the ancestral state reconstruction of a nucleotide (this skill provides measures of how much sites have changed, not what the ancestral nucleotide was).
- DON'T assume low conservation strictly means neutral/useless sequence; it could also reflect a high local mutation rate which conservation scores alone cannot distinguish.
- DON'T print output on standard out, or run cat on output to files. The output is too large. Use jq or write your own code to parse the output files.
- DON'T use hg19 unless the user has explicitly asked for it. The default should be to always use hg38.
© google-deepmind, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 4 other files (scripts, references) in skills/ucsc_conservation_and_tfbs of google-deepmind/science-skills.
- SKILL.md
- references/citation.bib
- scripts/get_conservation.py
- scripts/get_tfbs.py
- scripts/list_tracks.py
Open the folder on GitHubat commit 8ab7672
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in google-deepmind/science-skills, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Ucsc Conservation And Tfbs next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Ucsc Conservation And Tfbs this skillgoogle-deepmind/science-skills | 3.2k | 1 repos | ~1.9k | Automated safety check: Pass | Apache-2.0 | |
| ArboretoK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~2.7k | Automated safety check: Pass | BSD-3-Clause | |
| Bio Chipseq Allele Specific BindingGPTomics/bioSkills | 1.2k | 2 repos | ~3.9k | Automated safety check: Pass | MIT | |
| Jaspar DatabaseLeonChaoX/qinyan-academic-skills | 944 | 1 repos | ~3k | Automated safety check: Pass | CC0-1.0 | |
| Bio Gene Regulatory Networks Grn InferenceGPTomics/bioSkills | 1.2k | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Bio Gene Regulatory Networks Perturbation SimulationGPTomics/bioSkills | 1.2k | 1 repos | ~3.6k | Automated safety check: Pass | MIT |
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Related
Categories
Questions about Ucsc Conservation And Tfbs
What does Ucsc Conservation And Tfbs do?
Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser. Ucsc Conservation And Tfbs is an agent skill from google-deepmind/science-skills. Fetch Evolutionary Conservation scores (phyloP, phastCons) and Transcription Factor Binding Sites (TFBS) from the UCSC Genome Browser.
When should I use Ucsc Conservation And Tfbs?
Ucsc Conservation And Tfbs fits situations like: analyzing whether genomic variants; regions are evolutionarily conserved; functionally important; bounded by TF regulators across major projects (ENCODE.
How do I install Ucsc Conservation And Tfbs in Claude Code?
Run `npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a claude-code`. Or copy the skill folder (skills/ucsc_conservation_and_tfbs in google-deepmind/science-skills) into .claude/skills/ucsc-conservation-and-tfbs in your project. Claude Code loads it when a task matches its description.
How do I install Ucsc Conservation And Tfbs in Codex?
Run `npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a codex`. Or copy the skill folder (skills/ucsc_conservation_and_tfbs in google-deepmind/science-skills) into .agents/skills/ucsc-conservation-and-tfbs in your project. Codex loads it when a task matches its description.
Can I use Ucsc Conservation And Tfbs in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add google-deepmind/science-skills --skill ucsc-conservation-and-tfbs -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/ucsc-conservation-and-tfbs, .gemini/skills/ucsc-conservation-and-tfbs, .github/skills/ucsc-conservation-and-tfbs and .opencode/skills/ucsc-conservation-and-tfbs in your project.
What does Ucsc Conservation And Tfbs need to run?
Going by SKILL.md and its folder, Ucsc Conservation And Tfbs needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.
Does Ucsc Conservation And Tfbs access the network?
SKILL.md names 1 domain. As links in the text: genome.ucsc.edu. This is read from the text; nothing was executed.
Is Ucsc Conservation And Tfbs safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does Ucsc Conservation And Tfbs use?
Ucsc Conservation And Tfbs is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Ucsc Conservation And Tfbs use?
About 1.9k tokens (SKILL.md is roughly 7.7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 203 tokens, read only when the agent opens those files.
What are the alternatives to Ucsc Conservation And Tfbs?
Skills that share tags, products or a category with Ucsc Conservation And Tfbs: Arboreto (K-Dense-AI/scientific-agent-skills, 48k stars), Bio Chipseq Allele Specific Binding (GPTomics/bioSkills, 1.2k stars), Jaspar Database (LeonChaoX/qinyan-academic-skills, 944 stars) and Bio Gene Regulatory Networks Grn Inference (GPTomics/bioSkills, 1.2k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Ucsc Conservation And Tfbs?
google-deepmind (a GitHub organization) maintains it in google-deepmind/science-skills, which has 3,233 GitHub stars. The repository holds 40 skills in this directory. The repository was last updated on October 9, 2026.
Source: google-deepmind/science-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.