tooluniverse-sequence-retrieval

mims-harvard/tooluniverse · updated Apr 8, 2026

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

Retrieve DNA, RNA, and protein sequences from NCBI and ENA with automatic gene disambiguation and cross-database handling.

  • Searches NCBI Nucleotide by organism, gene name, strain, and sequence type; automatically disambiguates genes across species and resolves accession prefixes to the correct database
  • Handles RefSeq (NC_, NM_, NP_) and GenBank accessions with intelligent fallback between NCBI and ENA; never attempts ENA queries on RefSeq-only accessions
  • Returns detailed sequence pro
skill.md

Biological Sequence Retrieval

Retrieve DNA, RNA, and protein sequences with proper disambiguation and cross-database handling.

IMPORTANT: Always use English terms in tool calls. Only try original-language terms as fallback. Respond in the user's language.

LOOK UP DON'T GUESS: Never assume accession numbers or sequence versions. Always retrieve and verify from NCBI or ENA.

Domain Reasoning

Sequence quality hierarchy: RefSeq (NM_/NP_ = curated) > RefSeq predicted (XM_/XP_) > GenBank (submitted). Prefer the MANE Select transcript for human canonical isoforms. Check version numbers -- annotations improve across versions.

Workflow

Phase 0: Clarify (if needed) → Phase 1: Disambiguate Gene/Organism → Phase 2: Search & Retrieve → Phase 3: Report

Phase 0: Clarification (When Needed)

Ask ONLY if: gene exists in multiple organisms, sequence type unclear, or strain matters. Skip for: specific accessions, clear organism+gene combos, complete genome requests with organism.


Phase 1: Gene/Organism Disambiguation

Accession Type Decision Tree

Prefix Type Use With
NC_/NM_/NR_/NP_/XM_ RefSeq NCBI only
U*/M*/K*/X*/CP*/NZ_ GenBank NCBI or ENA
EMBL format EMBL ENA preferred

CRITICAL: Never try ENA tools with RefSeq accessions -- they return 404.

Identity Checklist

  • Organism confirmed (scientific name)
  • Gene symbol/name identified
  • Sequence type determined (genomic/mRNA/protein)
  • Accession prefix identified for tool selection

Phase 2: Data Retrieval (Internal)

Retrieve silently. Do NOT narrate the search process.

# Search NCBI Nucleotide
result = tu.tools.NCBI_search_nucleotide(
    operation="search", organism=organism, gene=gene,
    strain=strain, keywords=keywords, seq_type=seq_type, limit=10
)

# Get accessions from UIDs
accessions = tu.tools.NCBI_fetch_accessions(operation="fetch_accession", uids=result["data"]["uids"])

# Retrieve sequence (FASTA or GenBank format)
sequence = tu.tools.NCBI_get_sequence(operation="fetch_sequence", accession=accession, format="fasta")

# ENA alternative (non-RefSeq accessions only)
entry = tu.tools.ena_get_entry(accession=accession)
fasta = tu.tools.ena_get_sequence_fasta(accession=accession)

Fallback Chains

Primary Fallback Notes
NCBI_get_sequence ENA (if GenBank format) NCBI unavailable
ENA_get_entry NCBI_get_sequence ENA doesn't have RefSeq
NCBI_search_nucleotide Try broader keywords No results

Phase 3: Report Sequence Profile

Present as a Sequence Profile Report. Hide search process. Include:

  1. Search Summary: query, database, result count
  2. Primary Sequence: accession, type (RefSeq/GenBank), organism, strain, length, molecule, topology, curation level
  3. Sequence Preview: first lines of FASTA (truncated)
  4. Annotations Summary: CDS/tRNA/rRNA/regulatory feature counts (from GenBank format)
  5. Alternative Sequences: ranked by relevance and curation, with ENA compatibility
  6. Cross-Database References: RefSeq, GenBank, ENA/EMBL, BioProject, BioSample
  7. Download Options: FASTA (for BLAST/alignment), GenBank (for annotation)

Curation Level Tiers

Tier Prefix Description
RefSeq Reference (best) NC_, NM_, NP_ NCBI-curated, gold standard
RefSeq Predicted XM_, XP_, XR_ Computationally predicted
GenBank Validated Various Submitted, some curation
GenBank Direct Various Direct submission
Third Party TPA_ Third-party annotation

Reasoning Framework

Sequence quality: Prefer RefSeq over GenBank. Check version numbers. Sequences with "PREDICTED" in definition are not experimentally validated.

Accession guidance: RefSeq = NCBI-only. GenBank = mirrored in ENA/EMBL. Default to RefSeq mRNA (NM_) for human/model organisms; most complete genome assembly for microbial queries.

Cross-database reconciliation: Same sequence may have different accessions (e.g., GenBank U00096 = RefSeq NC_000913 for E. coli K-12). Always report both when available. Discrepancies between GenBank/RefSeq typically indicate RefSeq curation corrected submission errors.

Synthesis Questions

  1. What is the highest-quality accession available?
  2. Are there alternative accessions in other databases?
  3. What is the annotation completeness?
  4. Is the sequence from the expected organism/strain?
  5. What download format suits the user's downstream analysis?

Error Handling

Error Response
"No search criteria provided" Add organism, gene, or keywords
"ENA 404 error" Likely RefSeq -- use NCBI only
"No results found" Broaden search, check spelling, try synonyms
"Sequence too large" Note size, provide download link instead

Tool Reference

NCBI Tools: NCBI_search_nucleotide (search), NCBI_fetch_accessions (UID→accession), NCBI_get_sequence (retrieve) ENA Tools (GenBank/EMBL only): ena_get_entry (metadata), ena_get_sequence_fasta (FASTA), ena_get_entry_summary (summary)


Search Parameters Reference

NCBI_search_nucleotide: operation="search", organism (scientific name), gene (symbol), strain, keywords, seq_type (complete_genome/mrna/refseq), limit

NCBI_get_sequence: operation="fetch_sequence", accession, format (fasta/genbank)

how to use tooluniverse-sequence-retrieval

How to use tooluniverse-sequence-retrieval on Cursor

AI-first code editor with Composer

1

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-sequence-retrieval
2

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-sequence-retrieval

The skills CLI fetches tooluniverse-sequence-retrieval from GitHub repository mims-harvard/tooluniverse and configures it for Cursor.

3

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
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/tooluniverse-sequence-retrieval

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

List & Monetize Your Skill

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

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

4.651 reviews
  • Ganesh Mohane· Dec 28, 2024

    I recommend tooluniverse-sequence-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Aditi Khan· Dec 24, 2024

    Useful defaults in tooluniverse-sequence-retrieval — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Aanya Torres· Dec 20, 2024

    Registry listing for tooluniverse-sequence-retrieval matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Ren Chawla· Dec 4, 2024

    Keeps context tight: tooluniverse-sequence-retrieval is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • James Liu· Dec 4, 2024

    I recommend tooluniverse-sequence-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Lucas Sharma· Nov 23, 2024

    tooluniverse-sequence-retrieval is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Ishan Shah· Nov 15, 2024

    We added tooluniverse-sequence-retrieval from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Soo Haddad· Nov 11, 2024

    tooluniverse-sequence-retrieval fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Aanya Diallo· Nov 7, 2024

    tooluniverse-sequence-retrieval reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Aditi Rahman· Oct 26, 2024

    I recommend tooluniverse-sequence-retrieval for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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