jaspar-database▌
google-deepmind/science-skills · updated Jun 4, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
### Jaspar Database
- ›name: "jaspar-database"
- ›description: "Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene sym..."
| name | jaspar-database |
| description | > Query the JASPAR database for Transcription Factor (TF) binding profiles. Use when retrieving Position Frequency Matrices (PFMs) or Position Weight Matrices (PWMs) for specific TFs, resolving gene symbols to JASPAR Matrix IDs, or getting TF metadata. Supports multiple output formats (MEME, TRANSFAC, PFM, JASPAR, YAML). |
JASPAR Skill
JASPAR is the definitive open-access database for Transcription Factor (TF) binding profiles, stored as Position Frequency Matrices (PFMs).
Use this skill to map abstract sequence motifs or genomic regions to specific biological regulators (e.g., "what TFs bind here?" or "what is the motif for CTCF?").
Prerequisites
uv: Read theuvskill and follow its Setup instructions to ensureuvis installed and on PATH.- User Notification: If LICENSE_NOTIFICATION.txt does not already exist in this skill directory then (1) prominently notify the user to check the terms at https://jaspar.elixir.no/ and https://jaspar.elixir.no/api/, then (2) create the file recording the notification text and timestamp.
Core Rules
CRITICAL: You MUST respect the JASPAR API Terms of Use by adhering to the following:
- 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.
- Maximum API Window Size: The genomic window for a single API query MUST
NOT exceed 100,000 bp (100kb). The
jaspar_api.pyscript automatically chunks larger requests for you to bypass this limitation when querying larger regions. - Valid Matrix IDs:
get_tf_motif,get_tf_metadata, andget_tf_pwmrequire a stable JASPAR Matrix ID (e.g.,MA0488.2). If a user provides a gene symbol (e.g.,JUN), you must resolve it first usingresolve_tf_id. - Taxonomy Required: Resolving IDs requires a
tax_idto ensure targeted searches. Common IDs: Human=9606, Mouse=10090. - Notification: If this skill is used, ensure this is mentioned in the output.
Utility Scripts
Run all commands using the bundled Python script:
1. Resolve TF to Matrix ID
Maps a transcription factor name to a stable Matrix ID. Required step before fetching motifs if only a gene name is provided.
uv run scripts/jaspar_api.py resolve_tf_id --name "JUN" --tax-id 9606
2. Get TF Motif (PFM)
Retrieves the raw Position Frequency Matrix for a specific TF. Supports
--format flag.
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_motif --matrix-id "MA0488.2" --format meme
3. Get TF Metadata
Retrieves TF class, family, and links to external databases (e.g., UniProt).
Supports --format flag.
uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_metadata --matrix-id "MA0488.2" --format yaml
4. Compute PWM (Position Weight Matrix)
Fetches the PFM for a matrix and converts it to log-odds scores (PWM).
uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2"
uv run scripts/jaspar_api.py get_tf_pwm --matrix-id "MA0488.2" --pseudocount 0.1
5. Infer Matrix from Protein Sequence
Infers potential JASPAR matrix profiles from a raw transcription factor protein sequence.
uv run scripts/jaspar_api.py infer_from_sequence --sequence "QAQLLPSHHVG"
6. Get TF Flexible Model (TFFM)
Retrieves metadata for a JASPAR TF Flexible Model. (Note: The JASPAR TFFM endpoints occasionally experience 500 Internal Server errors).
uv run scripts/jaspar_api.py get_tffm --tffm-id "TFFM0001.1"
Output Formats
The get_tf_motif and get_tf_metadata commands accept an optional --format
flag. Supported formats: json (default), jsonp, jaspar, meme,
transfac, pfm, yaml.
Anti-Patterns
- DON'T pass gene symbols (e.g.,
JUN) toget_tf_motif. You must pass theMA...Matrix ID. - DON'T forget the
--tax-idwhen resolving a TF name. - DON'T use this skill for determining tissue-specific epigenetic availability (JASPAR shows potential binding, not actual tissue expression context).
- DON'T use this skill to model how a specific protein mutation affects binding.
How to use jaspar-database on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add jaspar-database
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches jaspar-database from GitHub repository google-deepmind/science-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate jaspar-database. Access the skill through slash commands (e.g., /jaspar-database) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
Task Automation & Efficiency
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Knowledge Enhancement
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Quality Improvement
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client with skill support
- ›Clear understanding of task or problem to solve
- ›Willingness to iterate and refine outputs
Time Estimate
15-45 minutes depending on use case complexity
Installation Steps
- 1.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 5.Integrate into regular workflow if valuable
Common Pitfalls
- ⚠Expecting perfect results without iteration
- ⚠Not providing enough context in prompts
- ⚠Using skill for tasks outside its intended scope
- ⚠Accepting outputs without review and validation
Best Practices▌
✓ Do
- +Start with clear, specific prompts
- +Provide relevant context and constraints
- +Review and refine all outputs before using
- +Iterate to improve output quality
- +Document successful prompt patterns
✗ Don't
- −Don't use without understanding skill limitations
- −Don't skip validation of outputs
- −Don't share sensitive information in prompts
- −Don't expect skill to replace human judgment
💡 Pro Tips
- ★Be specific about desired format and style
- ★Ask for multiple options to choose from
- ★Request explanations to understand reasoning
- ★Combine AI efficiency with human expertise
When to Use This▌
✓ Use When
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid When
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
Learning Path▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.7★★★★★57 reviews- ★★★★★Anika Anderson· Dec 16, 2024
Keeps context tight: jaspar-database is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Sofia Iyer· Dec 16, 2024
jaspar-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Pratham Ware· Dec 12, 2024
jaspar-database is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Valentina White· Dec 12, 2024
I recommend jaspar-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Dhruvi Jain· Dec 8, 2024
jaspar-database has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Oshnikdeep· Nov 27, 2024
Solid pick for teams standardizing on skills: jaspar-database is focused, and the summary matches what you get after install.
- ★★★★★Li Gonzalez· Nov 7, 2024
I recommend jaspar-database for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Zaid Li· Nov 7, 2024
Registry listing for jaspar-database matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Camila Iyer· Nov 3, 2024
Keeps context tight: jaspar-database is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Anaya Torres· Oct 26, 2024
jaspar-database reduced setup friction for our internal harness; good balance of opinion and flexibility.
showing 1-10 of 57