Agent Skills › Runchuan-BU/BioClaw › blast-search

blast-search

GitHub

用于在BioClaw容器中运行NCBI BLAST序列相似性搜索，支持本地及远程BLAST任务，帮助用户查找相似序列、鉴定基因或蛋白以及进行同源性分析。

container/skills/blast-search/SKILL.md Runchuan-BU/BioClaw

Trigger Scenarios

用户询问如何执行BLAST搜索用户提供DNA/RNA/蛋白质序列并寻找相似序列用户要求识别未知序列用户进行同源性搜索

Install

npx skills add Runchuan-BU/BioClaw --skill blast-search -g -y

More Options

Non-standard path

npx skills add https://github.com/Runchuan-BU/BioClaw/tree/main/container/skills/blast-search -g -y

Use without installing

npx skills use Runchuan-BU/BioClaw@blast-search

指定 Agent (Claude Code)

npx skills add Runchuan-BU/BioClaw --skill blast-search -a claude-code -g -y

安装 repo 全部 skill

npx skills add Runchuan-BU/BioClaw --all -g -y

预览 repo 内 skill

npx skills add Runchuan-BU/BioClaw --list

SKILL.md

Frontmatter

{
    "name": "blast-search",
    "description": "Run BLAST sequence similarity searches. Use when the user asks to BLAST a sequence, find similar sequences, identify a gene\/protein, or do homology search. Triggers on \"blast\", \"sequence similarity\", \"homology\", \"identify sequence\"."
}

BLAST Search

Run NCBI BLAST+ searches inside the BioClaw container.

When to Use

User provides a DNA/RNA/protein sequence and wants to find similar sequences
User asks to identify an unknown sequence
User wants to check sequence conservation across species

How to Execute

1. Determine BLAST program

Input	Database	Program
Nucleotide query	Nucleotide DB	`blastn`
Protein query	Protein DB	`blastp`
Nucleotide query	Protein DB	`blastx`
Protein query	Nucleotide DB	`tblastn`

2. For local BLAST (sequences provided by user)

# Create query file
cat > /tmp/query.fa << 'EOF'
>query_sequence
ATGCGATCGATCGATCG...
EOF

# Create subject file (if user provides reference)
cat > /tmp/subject.fa << 'EOF'
>reference
ATGCGATCGATCGATCG...
EOF

# Run BLAST
blastn -query /tmp/query.fa -subject /tmp/subject.fa -outfmt 6 -evalue 1e-5

3. For remote BLAST (against NCBI databases)

Use BioPython's NCBIWWW module:

from Bio.Blast import NCBIWWW, NCBIXML
from Bio import SeqIO

# Read sequence
sequence = "ATGCGATCGATCGATCG..."

# Run remote BLAST
result_handle = NCBIWWW.qblast("blastn", "nt", sequence)
blast_records = NCBIXML.parse(result_handle)

for record in blast_records:
    for alignment in record.alignments[:10]:
        print(f"Title: {alignment.title}")
        for hsp in alignment.hsps:
            print(f"  Score: {hsp.score}, E-value: {hsp.expect}")
            print(f"  Identity: {hsp.identities}/{hsp.align_length} ({hsp.identities/hsp.align_length*100:.1f}%)")

4. Output format

Present results in a clear table:

*BLAST Results (top 10 hits)*

• Hit 1: Homo sapiens TP53 gene (98.5% identity, E=1e-45)
• Hit 2: Mus musculus Trp53 gene (89.2% identity, E=1e-38)
...