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概要と使いどころ
Use when polishing the prose of an Accounting, Organizations and Society (AOS) manuscript — sustained argumentative writing that carries theory and evidence together, a self-contained abstract, disciplined length despite the absence of a hard cap, and full anonymization for double-anonymized review. Polishes prose; it does not run the submission preflight (aos-submission).
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Use when running the final pre-submission preflight for an Accounting, Organizations and Society (AOS) manuscript — Editorial Manager files (anonymized manuscript, separate title page, declarations), Elsevier policies (competing interests, AI, ethics), and open-access decisions. Checks readiness to submit; it does not handle the post-decision response (aos-rebuttal).
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Use when deciding which aos-* sub-skill to invoke next, or when sequencing manuscript work from topic selection through rebuttal for an Accounting, Organizations and Society (AOS) manuscript. Routes — it does not replace — the specialized skills.
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Use when analyzing the material of an Accounting, Organizations and Society (AOS) manuscript — coding and interpreting qualitative field data, estimating experimental and survey models, or running theory-laden archival analyses, with an audit trail appropriate to each tradition. Analyzes and reports; it does not design the study (aos-methods).
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Use when building the novel integrative framework that an Academy of Management Annals (Annals) review must deliver — the theory-advancing "new way of seeing the field" that is the acceptance bar, not a catalog of papers. Designs the spine; it does not gather the literature (amann-literature-synthesis) or appraise evidence balance (amann-evidence-standards).
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Use when appraising the cumulative evidence and ensuring balance in an Academy of Management Annals (Annals) review — weighing conflicting findings by credibility, steelmanning rival schools, and handling the author's own work even-handedly. Audits evidence quality and fairness; it does not design the framework (amann-organizing-framework) or build exhibits (amann-tables-figures).
日本語の概要は準備中です。原文の説明を表示しています。
Use when revising an Academy of Management Annals (Annals) review for the house voice — authoritative, integrative, agenda-setting "reviews with an attitude," with a strong problem-first opening and a contribution-stating abstract. Polishes prose and structure; it does not design the framework (amann-organizing-framework) or run the submission preflight (amann-submission).
日本語の概要は準備中です。原文の説明を表示しています。
Use when organizing AAAI supplementary material, including the technical appendix, multimedia appendix, and code/data ZIPs, while respecting that AAAI supplements are due with the paper, treated as immutable after submission, must stay double-blind, and should never hide main-paper-critical evidence from reviewers who skim the appendix.
日本語の概要は準備中です。原文の説明を表示しています。
Use when judging whether a management/organization literature is an Academy of Management Annals (Annals)-scale review topic — mature, important, fragmented, and integrable into a new framework — rather than a narrow review. Decides fit and frames the review's animating problem; it does not gather the literature (amann-literature-synthesis) or write the proposal (amann-proposal-framing).
日本語の概要は準備中です。原文の説明を表示しています。
Use when responding to an Academy of Management Annals (Annals) proposal decision or full-review referee letter — framework/attitude asks, coverage gaps, balance complaints, and accessibility. Drafts the response letter and revision plan; it does not run the portal preflight (amann-submission) or redesign the framework from scratch (amann-organizing-framework).
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Analyze a website's SEO visibility, keyword rankings, traffic estimates, and competitive positioning. Uses web search probes, SimilarWeb (free tier via web), and site: queries to build an SEO profile without requiring paid tool subscriptions. Useful for competitive intel, gap analysis, and reverse-engineering a company's organic acquisition strategy.
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Find quick-win SEO content opportunities by comparing your site's existing content against competitor keyword rankings. Chains site-content-catalog and seo-domain-analyzer to build a content inventory, then identifies gaps — topics competitors rank for that you don't cover yet. Outputs a prioritized list of posts to write or update. Use when a seed/Series A team wants to start winning organic traffic without guessing.
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Pull real SEO metrics for any domain using Apify scrapers for Semrush and Ahrefs data. Gets domain authority, organic traffic estimates, keyword rankings, backlink profiles, top performing pages, and auto-discovers competitors from keyword overlap. No Semrush/Ahrefs subscription needed — uses Apify actors that scrape public pages.
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Generate 3-5 messaging variants for a value proposition, design structured A/B tests, and analyze results to determine which framing resonates most with ICP. Tests can run via LinkedIn organic posts, cold email subject line splits, or both. Pure reasoning for variant generation and analysis — the user deploys the tests through their own tools. Use when a team can't decide between messaging angles and needs data, not opinions.
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Guidelines for introducing and using nullable reference types (NRT) and System.Diagnostics.CodeAnalysis nullable attributes in C# / .NET codebases. Covers the nullability model, flow analysis, the null-forgiving operator, API design rules, the full attribute catalog (AllowNull, DisallowNull, MaybeNull, NotNull, NotNullWhen, MaybeNullWhen, NotNullIfNotNull, MemberNotNull, MemberNotNullWhen, DoesNotReturn, DoesNotReturnIf), the C# 14 field keyword, incremental migration of legacy codebases, and a code-generation checklist.
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Organize DI registrations using IServiceCollection extension methods. Group related services into composable Add* methods for clean Program.cs and reusable configuration in tests.
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Defines cell populations in flow and spectral cytometry through manual gates (rectangle, polygon, quadrant, boolean) and reproducible automated gating (openCyto gating templates, flowDensity data-driven thresholds, flowClust model-based gates), organized as a hierarchical GatingSet (flowWorkspace) and round-tripped with FlowJo via CytoML. Covers the canonical gate order (time -> debris -> singlets -> live -> lineage), FMO-vs-isotype boundary setting, gate-order dependence and recompute semantics, rare-event/MRD gating, and per-population statistics. Use when building a gating strategy, automating a manual FlowJo scheme across samples, choosing manual vs data-driven gates, or extracting population frequencies.
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Designs and analyzes in vivo CRISPR screens in animal tumor models, organoids, and immune-cell adoptive transfers. Covers bottleneck math (250x cells/sgRNA requires ~25M cells implanted; impossible for most syngeneic models, forcing focused libraries), focused library design (Manguso 2017 Nature 547:413 immune screen; Chen 2015 tumor screens), CRISPR-StAR intrinsic-control screening (Uijttewaal 2025 Nat Biotechnol 43:1848), clonal-dynamics-limited detection, tumor-explant DNA recovery, syngeneic vs xenograft vs PDX considerations, and the relationship to downstream MAGeCK / drugZ analysis. Use when designing in vivo CRISPR screens for tumor / immune / metastasis biology, choosing focused vs genome-wide for animal models, addressing bottleneck-induced clonal collapse, picking the syngeneic / xenograft / PDX model, integrating in vivo with in vitro results, or applying CRISPR-StAR for animal experiments.
日本語の概要は準備中です。原文の説明を表示しています。
Run remote BLAST searches against NCBI servers using Biopython Bio.Blast.NCBIWWW. Use when identifying unknown sequences, finding homologs, picking the correct BLAST program (blastn/blastp/blastx/tblastn/tblastx/psiblast/megablast/dc-megablast), interpreting Karlin-Altschul E-values, avoiding the max_target_seqs trap (Shah 2019), choosing composition-based statistics, or limiting searches by organism. Covers RID lifecycle, database choice (nt/nr/refseq_select/swissprot), word-size and CBS taxonomy.
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Bulk-query Ensembl BioMart (and other BioMart instances) for cross-database ID mapping, gene/transcript/exon coordinates, and ortholog tables. Use when batch-converting Ensembl IDs to other namespaces (HGNC, RefSeq, UniProt, Entrez), pulling gene coordinate tables for thousands of genes, building ortholog wide-tables across species, or replacing slow Ensembl REST loops with one-shot bulk export. Encodes BioMart's XML query format, R biomaRt vs Python pybiomart trade-off, mart-vs-dataset hierarchy, and the URL endpoint that's BioMart-specific (separate from rest.ensembl.org).
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Query the Ensembl REST API for gene/transcript/protein lookup, sequence retrieval, comparative genomics (Compara), variant effect prediction (VEP), regulatory features, and cross-species ortholog/paralog calls. Use when pulling Ensembl-native data (Ensembl Gene IDs, version-pinned releases, archive endpoints for reproducibility), gene/transcript/exon structure with stable IDs, or VEP for variant annotation. Encodes the 15 req/sec rate limit, archive (e110.rest.ensembl.org) for reproducibility, Ensembl divisions (vertebrates / plants / fungi / metazoa / bacteria), and the symbol-vs-ID stability problem.
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Extracts, filters, annotates, and exports differential expression results from DESeq2 or edgeR with proper handling of padj=NA (independent filtering, Cook's outliers, all-zero), multiple-testing correction choice (BH vs Storey q-value vs IHW vs lfsr), TREAT vs post-hoc fold-change filtering, p-value histogram diagnostics, gene annotation via org.db/biomaRt/mygene, GSEA preranked input, ORA background construction, replication reality (Schurch 2016 small-n result), and SABV/sex-stratified reporting. Use when extracting and interpreting DE results, troubleshooting padj=NA, choosing FDR method, preparing ranked lists for pathway analysis, annotating gene IDs, or comparing DESeq2 vs edgeR outputs.
日本語の概要は準備中です。原文の説明を表示しています。
Query UniProt's REST API (post-2022 endpoint at rest.uniprot.org) for protein sequences, annotations, GO terms, cross-references, ID mappings, and proteomes. Use when fetching UniProtKB entries, navigating the JSON schema, choosing between UniProtKB/UniRef/UniParc/Proteomes resources, deciding stream vs search endpoint for batch retrieval, running ID-mapping jobs with the async pattern, handling isoform suffixes, or filtering reviewed Swiss-Prot vs auto-annotated TrEMBL. Encodes the legacy URL migration (2022), the new JSON schema layout, and bulk-pull patterns.
日本語の概要は準備中です。原文の説明を表示しています。
Builds and applies 3D pharmacophore models using RDKit Pharm3D, the apo2ph4 receptor-based workflow (Heider et al. 2023), Pharmer / Pharmit for search, and PharmacoForge for protein-pocket-conditioned pharmacophore generation (Flynn et al. 2025), covering ligand-based pharmacophores from active-set alignment and receptor-based pharmacophores from binding-pocket geometry. Explicitly handles feature types, geometric tolerances, partial matching, and pharmacophore-based virtual screening. Use when identifying scaffold-hopping candidates, building shape-and-feature search queries, or transferring SAR across chemotypes.
日本語の概要は準備中です。原文の説明を表示しています。