ors-meta

Plugin ors-meta from marketplace pradyumnasagar in pradyumnasagar/open-research-skills. Commands read from the repo's manifest — 13 days ago.

Skills (128)

• agent-handoff

  Pass work between ORS skills with a Material Passport — a structured JSON envelope that captures inputs, outputs, decisions, and provenance so a downstream skill can resume without re-deriving context. Use when one skill produces output that another skill must consume, especially across category bou

• cross-reference-mapper

  Discover and maintain `## Cross-references` between ORS skills. Given a new or edited skill, suggest related skills (same category, shared tags, complementary workflows). Verify all xref slugs resolve to existing SKILL.md files. Use when adding a new skill, when sibling skills move, or when an audit

• integrity-audit

  7-mode AI failure-mode checklist applied before publishing any ORS artifact (skill, manuscript section, dataset card, agent output). Catches: fabricated citations, silent failures, scope creep, missing provenance, unsupervised writes, version drift, hallucinated APIs. Use as the final pass before an

• release-management

  Version, changelog, and marketplace workflow for ORS skills. Semver discipline, breaking-change protocol, marketplace.json update, README refresh, and the v0.X.Y → v1.0.0 graduation criteria. Use when bumping a skill version, publishing a release, or upgrading the ORS package version.

• roadmap-author

  Author a new ORS skill from scratch using the v0.4.0 schema. Produces a valid SKILL.md (frontmatter + metadata + sections) following spec/skill-format.md, guided by spec/author-guide.md, validated by scripts/validate-skills.py. Use when a user says 'add a new skill', 'create a skill for X', or 'I wa

• batch-processing

  Process many FASTA/FASTQ/GenBank files in batch — merge, split, convert, summarize, organize — using Biopython 1.83+.

• bowtie2-alignment

  Align short reads to a reference with Bowtie2 — the standard aligner for ChIP-seq, ATAC-seq, and other short-fragment applications where sensitivity for short indels matters less than speed.

• bwa-alignment

  Align Illumina short reads to a reference genome with BWA-MEM — including index, MEM algorithm, paired-end, alt-contig handling, and 2026 best practices.

• bwa-mem2-alignment

  Use BWA-MEM2 — the SIMD-accelerated BWA-MEM replacement — for 2-3x speedup on human genome alignment with identical results to BWA-MEM.

• codon-usage

  Compute codon usage frequencies, RSCU, CAI, and tRNA adaptation — for gene expression prediction, heterologous expression design, and comparative genomics.

• compressed-sequence-files

  Read and write gzip, bzip2, and BGZF-compressed FASTA/FASTQ using Python stdlib and Biopython — including indexable BGZF.

• fastq-quality-scores

  Access, filter, and trim Phred quality scores in FASTQ reads using Biopython 1.83+ — including per-position profiles and encoding auto-detection.

• filter-sequences

  Filter FASTA/FASTQ records by length, identity, regex on headers, GC window, complexity, and custom predicates — streaming with Biopython 1.83+.

• format-conversion

  Convert between sequence and annotation formats using Biopython SeqIO.convert and custom writers — including batch, lossy, and round-trip-safe patterns.

• hisat2-alignment

  Splice-aware RNA-seq alignment with HISAT2 — fast, memory-efficient, and the default in many bulk RNA-seq pipelines alongside STAR.

• motif-search

  Find patterns, motifs, and binding sites in DNA/RNA/protein sequences — using regex, IUPAC patterns, position weight matrices, and modern motif databases (JASPAR 2024, CIS-BP).

• paired-end-fastq

  Keep R1/R2 reads in lockstep — synchronize iteration, filter pairs together, interleave, and deinterleave — using Biopython and the 2026 best practices.

• pysam-genomics

  Programmatically read, modify, filter, and write BAM/CRAM/VCF files using pysam 0.22+ — the Python interface to htslib for NGS I/O, variant calling, and custom pipelines.

• read-write-sequences

  Read and write FASTA, FASTQ, GenBank, EMBL using Biopython SeqIO — including indexed random access, conversion, and 2026 best practices.

• reverse-complement

  Compute reverse complements, complements, and strand-aware operations on DNA/RNA — including IUPAC ambiguity support, batch processing, and the orientation trap.

• sam-bam-basics

  Understand the SAM format header, alignment records, FLAGs, MAPQ, CIGAR, and coordinate conventions — the foundation for all downstream BAM analysis.

• samtools-bam-processing

  Process BAM files with samtools — sort, index, merge, flagstat, mark duplicates, fixmate, depth, filter, and stream — the standard CLI toolkit for 2026.

• seq-objects

  Master the Seq, MutableSeq, and SeqRecord objects — slicing, immutability, ambiguity codes, alphabets, and the 2026 Biopython alphabet deprecation reality.

• sequence-properties

  Compute GC content, molecular weight, melting temperature, isoelectric point, and instability index for DNA, RNA, and protein sequences.

• sequence-slicing

  Slice, subset, and extract regions from sequences and SeqRecords — including feature extraction, fuzzy ends, and the location algebra behind GenBank features.

• sequence-statistics

  Compute length, GC, N50, L50, and per-file summaries for FASTA/FASTQ — including the N50 trick and modern streaming stats with Polars.

• star-alignment

  Splice-aware RNA-seq alignment with STAR — the gold-standard aligner for novel junction discovery, with 2-pass mapping and genome-generation strategies for 2026.

• transcription-translation

  Transcribe DNA to RNA (and back), translate coding sequences to protein using NCBI codon tables, and pick the right genetic code for mitochondria, plastids, or non-standard organisms.

• academic-cv

  Build an academic CV for US/EU faculty or postdoc applications, with proper section ordering, professional service, mentoring statements, and NSF/NIH biosketch cross-reference. Use when applying to tenure-track or postdoctoral positions.

• faculty-interview

  Prepare for an academic job interview: job talk, chalk talk, 1:1 meetings with PIs and deans, dean's talk, dinner etiquette, thank-you emails, and start-up package negotiation (funds, lab space, equipment, moving, partner accommodation). Use when invited for an on-site or virtual on-site for a facul

• fellowship-application

  Apply for predoctoral fellowships (Hertz, NDSEG, NSF GRFP, Ford, AAAS Mass Media) and the Packard postdoctoral fellowship. Covers personal statement, research statement, transcript curation, grad school list, referee coordination, and submission timing. Use when applying for a major external fellows

• industry-transition

  Translate a PhD into an industry resume, navigate technical screens and system design for ML roles, and compare biotech, big-pharma, ML-for-bio, science writing, and consulting paths. Includes startup vs established company trade-offs. Use when a PhD student or postdoc is preparing for a job search

• negotiation

  Negotiate academic and industry offers: startup packages, postdoc salaries, industry offers and counter-offers, dual-career accommodation, equity vs salary trade-offs, BATNA analysis, and the difference between written and verbal offers. Use when preparing for, conducting, or evaluating a negotiatio

• tenure-dossier

  Assemble a tenure case from research statement, teaching portfolio, external letters, internal documentation, mentoring record, service, and counter-narrative for low-citation fields. Use when preparing a tenure case packet for a US/EU tenure review.

• admet-prediction

  Predicts ADMET properties using ADMETlab 3.0 (119 endpoints with uncertainty), ADMET-AI, DeepChem MolNet, and chemprop D-MPNN with explicit handling of OECD QSAR principles, applicability domain assessment, calibration, hERG/CYP/AMES gold-standard endpoints, and PAINS / Lipinski / Ro5 / Veber / BBB

• conformer-generation

  Generates 3D conformer ensembles using RDKit ETKDGv3 with knowledge-enhanced distance geometry, MMFF94/UFF force-field optimization, CREST + GFN2-xTB semi-empirical refinement, and macrocycle-aware torsion preferences. Provides explicit decision rules for single vs ensemble conformer use, RMSD pruni

• covalent-design

  Designs covalent inhibitors and warheads targeting cysteine (most common, ~98% of covalent drugs), lysine, serine, threonine, tyrosine, and aspartate residues, with explicit handling of warhead reactivity (acrylamide, chloroacetamide, vinyl sulfone, sulfonyl fluoride, fluorosulfate, aldehyde, borona

• docking-rescoring

  Performs ML-based protein-ligand pose prediction and scoring using DiffDock-L (diffusion-based), Boltz-1 / Boltz-2 (foundation model with affinity), Chai-1, AlphaFold3 ligand, EquiBind, TANKBind, NeuralPLexer, and hybrid workflows (DiffDock pose + GNINA rescore + PoseBusters QC). Explicit handling o

• free-energy-calculations

  Performs alchemical free-energy calculations including relative binding free energy (RBFE / FEP+) and absolute binding free energy (ABFE) via OpenFE, FEP+, GROMACS, AMBER pmemd, and OpenMM with explicit lambda window scheduling, soft-core potentials, REST2 enhanced sampling, MBAR/BAR analysis, and c

• generative-design

  Designs novel molecules using REINVENT 4 (de novo, scaffold decoration, linker design, R-group, molecular optimization), MolMIM, Diffusion-based generators (DiGress, DiffSMol), and JT-VAE with explicit handling of multi-parameter optimization (MPO), goal-directed scoring functions, transfer/reinforc

• molecular-descriptors

  Calculates molecular fingerprints (ECFP/Morgan, FCFP, MACCS, RDKit, AtomPair, TopologicalTorsion, Avalon, MAP4, MHFP6) and physicochemical descriptors (Lipinski, QED, TPSA, Crippen LogP, 3D shape) with explicit choice tables, bit vs count semantics, and partial-charge model selection. Use when featu

• molecular-io

  Reads, writes, and converts molecular file formats (SMILES, InChI, SDF V2000/V3000, MOL2, PDB, MMTF) using RDKit and Open Babel with rigorous handling of aromaticity perception, stereochemistry, implicit/explicit hydrogens, kekulization, and salt/fragment separation. Use when loading chemical librar

• molecular-standardization

  Standardizes molecular structures using ChEMBL chembl_structure_pipeline and RDKit rdMolStandardize covering sanitization, salt/solvent stripping, neutralization, tautomer canonicalization, stereochemistry standardization, mixture handling, and isotope normalization. Explicitly compares ChEMBL pipel

• pharmacophore-modeling

  Builds and applies 3D pharmacophore models using RDKit Pharm3D, the apo2ph4 receptor-based workflow, Pharmer / Pharmit (search), and PharmacoForge (diffusion-based generation), covering ligand-based pharmacophore (from active set alignment) and receptor-based pharmacophore (from binding pocket geome

• pose-validation

  Validates docked / generated protein-ligand poses using PoseBusters physical-validity tests, strain energy quantification, geometric checks (planarity, vdW overlap, bond/angle distortion), and pose-energy reasonableness. Filters AI-docking outputs (DiffDock, EquiBind, NeuralPLexer) where ~50% of pos

• protac-degraders

  Designs PROTACs, molecular glues, and bivalent degraders with explicit handling of E3 ligase choice (VHL, CRBN, IAP, MDM2, KEAP1), linker design (length, composition, rigidity), ternary complex prediction (PRosettaC, DeepTernary, AlphaFold3 with constraints), cooperativity (alpha), DC50 / Dmax chara

• qsar-modeling

  Builds QSAR / QSPR models using chemprop D-MPNN, MolFormer, Uni-Mol, ChemBERTa, random forest baselines, and Gaussian processes with explicit handling of OECD 5 principles, applicability domain (kNN, leverage, conformal prediction, Mahalanobis), scaffold-balanced splits, ensemble uncertainty, calibr

• retrosynthesis

  Performs retrosynthetic planning using AiZynthFinder (MCTS, template-based), Chemformer (template-free transformer), ASKCOS, and emerging RetroSynFormer with explicit handling of route scoring, building-block availability (eMolecules, Enamine, Mcule), forward prediction validation (Molecular Transfo

• scaffold-analysis

  Analyzes chemical libraries by scaffold using Bemis-Murcko scaffolds, generic frameworks, cyclic skeletons, matched molecular pair (MMP) analysis via mmpdb, R-group decomposition, Free-Wilson analysis, scaffold hopping, and chemotype-aware ML train/test splits. Use when identifying chemotype cluster

• shape-similarity

  Performs 3D shape-based similarity searching using ROCS (OpenEye), USRCAT (ultra-fast), Open3DAlign (RDKit), ESPSim (electrostatic), and ShaEP with explicit handling of Tanimoto-Combo (shape + color), shape vs ECFP4 complementarity, conformer-ensemble searching, alignment optimization, and scaffold

• similarity-searching

  Performs molecular similarity searching using Tanimoto, Tversky, Dice, and cosine coefficients on bit/count fingerprints with explicit choice rules for symmetric vs asymmetric measures, scaffold-hopping vs lead-optimization regimes, activity-cliff diagnosis, and large-library nearest-neighbor method

• substructure-search

  Searches molecular libraries for substructure matches using SMARTS patterns with explicit handling of recursive SMARTS, ring membership, aromaticity dialect, vector binding, atom map indices, and reactive/PAINS/REOS/Brenk/Aldridge filter catalogs. Use when filtering compounds by pharmacophore featur

• virtual-screening

  Performs structure-based virtual screening using AutoDock Vina, SMINA, GNINA (CNN scoring), and DiffDock-L hybrid workflows with explicit choice rules across rigid vs flexible docking, cross-docking vs self-docking, binding-site detection (P2Rank, fpocket), receptor preparation (PDB2PQR, PROPKA), li

• snakemake-workflow-engine

  Python-based workflow manager for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake resolves execution order and parallelism. Runs local, SLURM, LSF, AWS, GCP via profiles; per-rule conda/Singularity envs. For NGS pipelines, ML training, and multi-step file proce

• ai-disclosure

  Use when writing, reviewing, or editing the AI/LLM usage disclosure in a research manuscript, grant, or submission — covers venue-specific policies (Nature, Science, Cell, NEJM, Lancet, ICML, NeurIPS, AAAI, ACL), COPE position statement, ICMJE recommendations, prompt disclosure, and what is permitte

• data-privacy

  Use when designing or reviewing the privacy plan for a study that uses human data — covers HIPAA Safe Harbor vs Expert Determination, GDPR for research, de-identification, datathons, federated learning, differential privacy basics, single-IRB (sIRB), Certificates of Confidentiality, and the interact

• image-integrity

  Use when preparing, reviewing, or auditing research images (Western blots, gels, microscopy, EM, multi-panel figures) for submission — covers manipulation detection by proofreader tools and human review, figure assembly best practices, raw data retention, journal image-checking policies (e.g., Natur

• irb-protocol

  Use when writing, reviewing, or revising an Institutional Review Board (IRB) protocol for human-subjects research — anchors the protocol to the Belmont Report, the Common Rule (45 CFR 46), and the specific subparts for vulnerable populations.

• ai-detection-awareness

  Use when you or your institution are using, evaluating, or responding to AI-detection tools (GPTZero, Turnitin, Copyleaks, Originality.ai, Pangram) — how detectors work, their failure modes, the limits of paraphrasing tools, and the move toward process-based assessment.

• ai-disclosure-statement

  Use when drafting or auditing an AI/LLM disclosure statement for a manuscript, preprint, grant, or venue — what to include, where to put it, and how to meet major journal and conference policies.

• scientific-voice-style

  Use when developing or auditing a distinctive scientific writing voice that survives AI-generation — voice as a signal of authorship, common AI tells to avoid, and craft habits that build a recognisable authorial register.

• text-humanizing-editorial

  Use when editing AI-assisted or AI-generated text so that it reads as written by a knowledgeable human — workflow from AI draft to authorial voice, what to keep, what to rewrite, and the line that humanizing must not cross.

• cellprofiler-pipelines

  Use CellProfiler 5.x to build reproducible pipelines for cell/nuclei segmentation, illumination correction, feature extraction, and high-content screening assays including CellPainting.

• image-analysis-best-practices

  Apply best practices for microscopy image analysis: pixel-size calibration, channel bleed-through, exposure and dynamic range, controls, publication figures, color-blind safe palettes, and proper statistical handling of n=cells vs n=images vs n=animals.

• imagej-fiji-macro

  Record, write, and run ImageJ/Fiji macros for batch processing, ROI handling, intensity measurement, colocalization, time-lapse, FRET, and plugin installation in life-sciences microscopy.

• qupath-pathology

  Use QuPath 0.5.x for whole-slide image import, annotation, cell detection, pixel classification, deep-learning workflows (StarDist, Cellpose), and multiplexed analysis in digital pathology.

• eln-chemotion

  Chemotion open electronic lab notebook for chemists via REST API. Molecule editor, reactions, samples, spectra (NMR/IR/MS), inventory. Open-source alternative to ChemAxon/Accelrys for synthetic chemistry. For biology workflows use eln-elabftw; for assay pipelines use eln-openbis.

• eln-elabftw

  eLabFTW open-source electronic lab notebook via REST API. Self-hosted ELN/LIMS alternative to Benchling and LabArchives: experiments, database entries, inventory, equipment booking, experiments linking. Use for free, open lab notebook management. For chemistry-focused work use eln-chemotion; for ass

• eln-openbis

  openBIS open LIMS/ELN for life-sciences facilities via REST and Python API. Sample tracking across collections, spaces, datasets, vocabularies; integration with instruments and high-throughput pipelines. Open-source alternative to LabWare, Benchling LIMS. For notebook-style workflows use eln-elabftw

• opentrons-ot2-protocols

  Opentrons Python Protocol API v2 for OT-2 and Flex robots. Liquid handling protocols for PCR, ELISA, plate stamping, magnetic bead cleanup. Hardware modules: thermocycler, heater-shaker, magnetic, temperature. Simulate with opentrons_simulate before robot runs. For vendor-agnostic protocols use pyla

• protocolsio-protocol-repository

  Search and download published wet-lab protocols from protocols.io REST API. Find 90,000+ community protocols by keyword, DOI, or filter; extract steps, reagents, materials, timing, equipment. Free for public protocols. Use to build automation with opentrons-protocol-api or record runs in an ELN.

• pylabrobot-vendor-agnostic

  PyLabRobot hardware-agnostic Python liquid-handler library for Hamilton STAR, Tecan Freedom EVO, Opentrons OT-2, and simulator. Write protocols once, run on any robot. Async-first API. Plate reformatting, cherry-picking, serial dilutions. Use for vendor-agnostic workflows; use opentrons-ot2-protocol

• citation-management

  Set up and use reference managers (Zotero, Mendeley, EndNote) with citation styles, group libraries, PDF annotation, DOI/PMID workflows, and BibTeX export for reproducible research.

• literature-search

  Design reproducible, multi-database literature searches for biomedical and scientific questions. Covers PubMed/Web of Science/Scopus/Embase/IEEE/ACM/AGRICOLA/ERIC/PsycINFO, open indexes (OpenAlex, Semantic Scholar, Google Scholar), MeSH, Boolean operators, snowballing, citation alerts, and PRISMA-S

• paper-lookup

  Look up and resolve academic papers by DOI, PMID, arXiv ID, or title using Crossref, PubMed, OpenAlex, Semantic Scholar, and check retractions, preprints, and forward citations.

• scoping-review

  Map evidence landscapes in emerging fields using Arksey-O'Malley and JBI scoping review frameworks. Includes charting, narrative synthesis, consultation exercise, and gap identification without formal quality assessment.

• systematic-review

  Conduct rigorous systematic reviews and meta-analyses following PRISMA 2020, including risk-of-bias assessment, heterogeneity analysis, publication bias evaluation, and evidence grading with GRADE.

• alphafold-structure-prediction

  Run AlphaFold 2/3 and Boltz-1 for protein structure prediction, including MSA generation with MMseqs2/JackHMMER, pLDDT/PAE interpretation, multimer prediction, and querying the AlphaFold Database (AFDB).

• deep-learning-genomics

  Use CNNs (DeepBind, Basset), RNNs, and transformers (DNABERT, HyenaDNA, Evo, Nucleotide Transformer) for genomic sequence analysis. Use when predicting TF binding, chromatin profiles, splicing, or noncoding variant effects from raw sequence.

• protein-language-models

  Use ESM-2, ESMFold, ProtTrans, AlphaFold 2/3, Boltz-1, RoseTTAFold and OmegaFold for protein embeddings, zero-shot mutational-effect prediction, and 3D structure prediction. Use when scoring variants without a structure, designing mutant libraries, or predicting conformations.

• scrnaseq-deep-learning
• mentorship-goal-setting
• mentorship-onboarding
• teaching-course-design
• teaching-syllabus
• code-release
• fair-data
• licensing
• preprints
• preregistration
• grant-review
• manuscript-review
• reviewer-response
• scholar-evaluation
• bio-sketch
• darpa-baa
• erc
• fellowships
• foundation-grants
• grant-proposal-craft
• indian-grant-ecosystem
• nih-k-series
• nih-r01
• nsf-standard
• specific-aims
• comm-conference-talk
• comm-elevator-pitch
• comm-podcast
• comm-poster
• comm-press-release
• brainstorming
• critical-thinking
• failure-handling
• hypothesis-generation
• perspective-tour
• color-and-accessibility
• figure-design
• poster-design
• schematics-diagrams
• slides-design
• ai-disclosure-writing
• cover-letter
• manuscript-structure
• rebuttal-letter
• response-to-reviewers
• thesis-defense-viva
• thesis-methods-reproducibility
• thesis-structure

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