How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does tooluniverse-expression-data-retrieval support?

tooluniverse-expression-data-retrieval works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is tooluniverse-expression-data-retrieval free to use?

Yes. tooluniverse-expression-data-retrieval is free to install and use. It is available from the open explainx.ai skill registry published by mims-harvard.

Where can I read ratings and reviews for tooluniverse-expression-data-retrieval?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install tooluniverse-expression-data-retrieval?

Run `npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval` in your terminal. You need to have run `npx skills init` once in your project first.

Productivity

tooluniverse-expression-data-retrieval▌

mims-harvard/tooluniverse · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval

0 commentsdiscussion

summary

Retrieve gene expression experiments and multi-omics datasets with disambiguation and quality assessment.

skill.md

Gene Expression & Omics Data Retrieval

Retrieve gene expression experiments and multi-omics datasets with disambiguation and quality assessment.

IMPORTANT: Always use English terms in tool calls. Respond in the user's language.

LOOK UP DON'T GUESS: Never assume which datasets exist or their accessions. Always search to confirm.

Domain Reasoning

Before retrieving, determine: organism, tissue, experimental design (case-control/time-series/dose-response). These affect which database to search and how to interpret results. RNA-seq provides wider dynamic range; microarray has extensive legacy data. Prioritize experiments with >=3 biological replicates, complete annotations, and both raw+processed data.

Workflow

Phase 0: Clarify (if ambiguous) → Phase 1: Disambiguate → Phase 2: Search & Retrieve → Phase 3: Report

Phase 0: Clarification (When Needed)

Ask ONLY if: gene name ambiguous, tissue/condition unclear, organism not specified. Skip for: specific accessions (E-MTAB-, E-GEOD-, S-BSST*), clear disease/tissue+organism, explicit platform requests.

Phase 1: Query Disambiguation

Resolve official gene symbol (HGNC for human, MGI for mouse). Note common aliases for search expansion.

User Query Type	Search Strategy
Specific accession	Direct retrieval
Gene + condition	"[gene] [condition]" + species filter
Disease only	"[disease]" + species filter
Technology-specific	Add platform keywords

Phase 2: Data Retrieval (Internal)

Search silently. Do NOT narrate the process.

# ArrayExpress search
result = tu.tools.arrayexpress_search_experiments(keywords="[gene/disease]", species="[species]", limit=20)

# Get experiment details, samples, files
details = tu.tools.arrayexpress_get_experiment(accession=accession)
samples = tu.tools.arrayexpress_get_experiment_samples(accession=accession)
files = tu.tools.arrayexpress_get_experiment_files(accession=accession)

# BioStudies for multi-omics
biostudies = tu.tools.biostudies_search(query="[keywords]", limit=10)
study = tu.tools.biostudies_get_study(accession=study_accession)
study_files = tu.tools.biostudies_get_study_files(accession=study_accession)

Fallback Chains

Primary	Fallback
ArrayExpress search	BioStudies search
arrayexpress_get_experiment	biostudies_get_study
arrayexpress_get_experiment_files	Note "Files unavailable"

Phase 3: Report Dataset Profile

Present as a Dataset Search Report. Hide search process. Include:

Search Summary: query, databases searched, result count
Top Experiments (per experiment):
- Accession, organism, type (RNA-seq/microarray), platform, sample count, date
- Description, experimental design (conditions, replicates, tissue)
- Sample groups table, data files table
- Quality assessment (●●●/●●○/●○○)
Multi-Omics Studies (from BioStudies): accession, type, data types included
Summary Table: all experiments ranked
Recommendations: best dataset for user's purpose, integration notes
Data Access: download links, database URLs

Data Quality Tiers

Tier	Symbol	Criteria
High	●●●	>=3 bio replicates, complete metadata, processed data available
Medium	●●○	2-3 replicates OR some metadata gaps
Low	●○○	No replicates, sparse metadata, or access issues
Caution	○○○	Single sample, no replication, outdated platform

Reasoning Framework

Dataset quality: Prioritize >=3 biological replicates, complete annotations, both raw+processed data. Single-replicate experiments can inform but not be sole evidence.

Platform comparison: RNA-seq = wider dynamic range, novel transcripts. Microarray = probe-limited but extensive legacy data. Cross-platform combining requires batch correction.

Metadata scoring: Rate 0-5 on: (1) sample annotations, (2) design documented, (3) pipeline described, (4) raw data deposited, (5) publication linked. Score <=2 warrants caution.

GEO vs ArrayExpress: GEO has broader coverage (older studies); ArrayExpress enforces stricter metadata. BioStudies captures multi-omics. Search both.

Synthesis Questions

Does the dataset have sufficient replication and metadata for the intended analysis?
Are there batch effects or confounding variables?
Do multiple datasets show concordant patterns, and can they be integrated?

Error Handling

Error	Response
"No experiments found"	Broaden keywords, remove species filter, try synonyms
"Accession not found"	Verify format, check if withdrawn
"Files not available"	Note: "Data files restricted by submitter"
"API timeout"	Retry once, note "(metadata retrieval incomplete)"

Tool Reference

ArrayExpress: arrayexpress_search_experiments (search), arrayexpress_get_experiment (metadata), arrayexpress_get_experiment_files (downloads), arrayexpress_get_experiment_samples (annotations)

BioStudies: biostudies_search (search), biostudies_get_study (metadata+sections), biostudies_get_study_files (files)

Additional Sources:

GEO_search_rnaseq_datasets / geo_search_datasets -- GEO (largest RNA-seq repo)
OmicsDI_search_datasets -- cross-repository aggregation (GEO+ArrayExpress+PRIDE+MassIVE)
GTEx_get_expression_summary -- baseline tissue expression (54 normal tissues, param: gene_symbol)
ENAPortal_search_studies -- sequencing studies (param: query with description="...")
CxGDisc_search_datasets -- single-cell datasets (needs exact disease ontology terms)
PubMed_search_articles -- dataset discovery via publications

Search Parameters

ArrayExpress: keywords (free text), species (scientific name), array (platform filter), limit BioStudies: query (free text), limit

how to use tooluniverse-expression-data-retrieval

How to use tooluniverse-expression-data-retrieval 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 tooluniverse-expression-data-retrieval

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/mims-harvard/tooluniverse --skill tooluniverse-expression-data-retrieval

The skills CLI fetches tooluniverse-expression-data-retrieval from GitHub repository mims-harvard/tooluniverse 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:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ── always included ────

│ • Amp

│ • Antigravity

│ • Cline

│ • Codex

│ ●Cursor(selected)

│ • Cursor

│ • Windsurf

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/tooluniverse-expression-data-retrieval

Reload or restart Cursor to activate tooluniverse-expression-data-retrieval. Access the skill through slash commands (e.g., /tooluniverse-expression-data-retrieval) 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.

Additional Resources

›View source code on GitHub ›Skills CLI documentation ›Learn more about Cursor ›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

✓

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

✓

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

✓

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

✓

Save 3-5 hours/week on communication overhead

Implementation Guide▌

Prerequisites

›Claude Desktop or compatible AI client
›Access to product documentation and roadmap tools (Jira, Notion, etc.)
›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
›Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

1.Install product management skill
2.Start with user story generation for known feature
3.Progress to competitive analysis: research 2-3 competitors
4.Use for roadmap prioritization: apply RICE/ICE scoring
5.Draft stakeholder communications and refine based on feedback
6.Build template library for recurring PM tasks
7.Share effective prompts with product team

Common Pitfalls

⚠Not validating competitive research—verify facts before sharing
⚠Accepting user stories without involving engineering team
⚠Over-relying on frameworks without qualitative judgment
⚠Not customizing outputs to company culture and communication style
⚠Skipping stakeholder validation of generated requirements

Best Practices▌

✓ Do

+Validate research and competitive analysis with real data
+Collaborate with engineering when generating technical requirements
+Customize frameworks and templates to your company context
+Use skill for first drafts, refine with stakeholder input
+Document successful prompt patterns for PM tasks
+Combine AI efficiency with human judgment and intuition

✗ Don't

−Don't publish competitive analysis without fact-checking
−Don't finalize user stories without engineering review
−Don't make prioritization decisions solely on AI scoring
−Don't skip customer validation of generated requirements
−Don't ignore company-specific context and culture

💡 Pro Tips

★Provide context: company goals, constraints, customer feedback
★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
★Use skill for 70% generation + 30% customization to company needs

When to Use This▌

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path▌

1Basic: user stories, feature specs, status updates
2Intermediate: competitive analysis, prioritization frameworks, PRDs
3Advanced: product strategy, go-to-market planning, OKR setting
4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)

No comments yet — start the thread.

general reviews

Ratings

4.8★★★★★73 reviews

★★★★★Ren Harris· Dec 28, 2024
tooluniverse-expression-data-retrieval reduced setup friction for our internal harness; good balance of opinion and flexibility.
★★★★★Ren Liu· Dec 28, 2024
Useful defaults in tooluniverse-expression-data-retrieval — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
★★★★★Dhruvi Jain· Dec 24, 2024
tooluniverse-expression-data-retrieval reduced setup friction for our internal harness; good balance of opinion and flexibility.
★★★★★Hassan Johnson· Dec 24, 2024
tooluniverse-expression-data-retrieval is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
★★★★★Michael Mensah· Dec 20, 2024
tooluniverse-expression-data-retrieval fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
★★★★★Hassan Smith· Dec 16, 2024
I recommend tooluniverse-expression-data-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
★★★★★Michael Wang· Dec 16, 2024
tooluniverse-expression-data-retrieval has been reliable in day-to-day use. Documentation quality is above average for community skills.
★★★★★Michael Okafor· Nov 27, 2024
We added tooluniverse-expression-data-retrieval from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Rahul Santra· Nov 23, 2024
We added tooluniverse-expression-data-retrieval from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
★★★★★Sakura Rahman· Nov 19, 2024
I recommend tooluniverse-expression-data-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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