project-summary

Read the file PROJECT_INVENTORY.md from the project root and present a formatted summary including:

1. •Overview — What this MCP server does (1-2 sentences)
2. •Available Tools — List all MCP tools grouped by category (NCBI Datasets CLI, BioPython Analysis, Ensembl REST API, UniProt REST API, ClinVar, PDB/RCSB, InterPro, STRING, KEGG, NCBI BLAST, PubMed, Ensembl Regulation, AlphaFold, gnomAD, GTEx, HPO, Genome Coordinates, Reactome, Gene Ontology Enrichment, COSMIC, OMIM, Expression Atlas, NCBI Gene Links, ENCODE, Primer Design, PharmGKB, Disease Ontology, Paper Retrieval / Citation), with a one-line description of each
3. •Quick-Start Examples — Show 7-8 practical usage examples such as:
   • •Looking up a gene: datasets_summary_gene with symbol BRCA1 and taxon human
   • •Aligning two sequences: sequence_align with two protein sequences
   • •Ensembl gene lookup: ensembl_lookup_gene with symbol TP53
   • •Searching UniProt: uniprot_search for BRCA1 in human
   • •ClinVar search: clinvar_search for pathogenic BRCA1 variants
   • •PDB search: pdb_search for TP53 structures
   • •STRING interactions: string_get_interactions for TP53
   • •BLAST search: blast_search with a protein sequence
   • •PubMed search: pubmed_search for CRISPR gene therapy papers
   • •AlphaFold prediction: alphafold_get_prediction for P04637
4. •Custom Skills — Mention all seven skills: /project-summary, /gene-report <gene> (comprehensive multi-database gene report), /variant-report <target> (variant annotation report), /protein-report <protein> (protein-centric report with structure, PTMs, interactions, expression), /pathway-report <pathway> (pathway deep-dive with Reactome data, member genes, clinical variants, literature), /drug-target-report <target> (druggability assessment with structures, binding sites, disease rationale, COSMIC mutations), and /lab-notebook <subcommand> (research session lab notebook — start, annotate, update, report, status)
   • •Also mention the six agents: /literature-agent <topic> (PubMed literature search and summary), /comparative-genomics-agent <gene> <species...> (multi-species gene comparison with alignments), /clinical-variant-agent <variant> (full variant workup), /gene-list-agent <genes> (functional analysis of a gene list), /structure-agent <target> (structural biology deep-dive with all PDB structures, AlphaFold, variant mapping), /statistical-methods-agent <paper> (paper statistical analysis — fetches full text, inventories every statistical method, critiques assumptions and appropriateness)
5. •Setup Notes — Brief setup requirements (datasets CLI for NCBI tools, httpx + biopython installed via pip)

Keep the output concise and well-formatted with markdown.