design/content-writing/brand-voice-enforcement/SKILL.md
This skill applies brand guidelines to content creation. It should be used when the user asks to "write an email", "draft a proposal", "create a pitch deck", "write a LinkedIn post", "draft a presentation", "write a Slack message", "draft sales content", or any content creation request where brand voice should be applied. Also triggers on "on-brand", "brand voice", "enforce voice", "apply brand guidelines", "brand-aligned content", "write in our voice", "use our brand tone", "make this sound like us", "rewrite this in our tone", or "this doesn't sound on-brand". Not for generating guidelines from scratch (use guideline-generation) or discovering brand materials (use discover-brand).
npx skillsauth add harsh040506/claude-code-unified-skill-plugin-library brand-voice-enforcementInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Apply existing brand guidelines to all sales and marketing content generation. Load the user's brand guidelines, apply voice constants and tone flexes to the content request, validate output, and explain brand choices.
Find the user's brand guidelines using this sequence. Stop as soon as you find them:
Session context — Check if brand guidelines were generated earlier in this session (via /brand-voice:generate-guidelines). If so, they are already in the conversation. Use them directly. Session-generated guidelines are the freshest and reflect the user's most recent intent.
Local guidelines file — Check for .claude/brand-voice-guidelines.md inside the user's working folder. Do NOT use a relative path from the agent's current working directory — in Cowork, the agent runs from a plugin cache directory, not the user's project. Resolve the path relative to the user's working folder. If no working folder is set, skip this step.
Ask the user — If none of the above found guidelines, tell the user: "I couldn't find your brand guidelines. You can:
/brand-voice:discover-brand to find brand materials across your platforms/brand-voice:generate-guidelines to create guidelines from documents or transcriptsWait for the user to provide guidelines before proceeding.
Also read .claude/brand-voice.local.md for enforcement settings (even if guidelines came from another source):
strictness: strict | balanced | flexiblealways-explain: whether to always explain brand choicesBefore writing, identify:
Voice is the brand's personality — it stays constant across all content:
Refer to references/voice-constant-tone-flexes.md for the "voice constant, tone flexes" model.
Tone adapts by content type and audience. Use the tone-by-context matrix from guidelines to set:
Create content that:
For complex or long-form content, delegate to the content-generation agent (defined in agents/content-generation.md).
For high-stakes content, delegate to the quality-assurance agent (defined in agents/quality-assurance.md) for validation.
After generating content:
When always-explain is true in settings, include brand application notes with every response.
When the user's request conflicts with brand guidelines:
Default to adapting guidelines with an explanation of the tradeoff.
Open questions are unresolved brand positioning decisions flagged during guideline generation, stored in the guidelines under an "Open Questions" section. When generating content, check if the brand guidelines contain open questions:
references/voice-constant-tone-flexes.md — The "voice constant, tone flexes" mental model, "We Are / We Are Not" table structure, and tone-by-context matrix explanationreferences/before-after-examples.md — Before/after content examples per content type showing enforcement in practicetesting
Performs quality control on single-cell RNA-seq data (.h5ad or .h5 files) using scverse best practices with MAD-based filtering and comprehensive visualizations. Use when users request QC analysis, filtering low-quality cells, assessing data quality, or following scverse/scanpy best practices for single-cell analysis.
tools
Deep learning for single-cell analysis using scvi-tools. This skill should be used when users need (1) data integration and batch correction with scVI/scANVI, (2) ATAC-seq analysis with PeakVI, (3) CITE-seq multi-modal analysis with totalVI, (4) multiome RNA+ATAC analysis with MultiVI, (5) spatial transcriptomics deconvolution with DestVI, (6) label transfer and reference mapping with scANVI/scArches, (7) RNA velocity with veloVI, or (8) any deep learning-based single-cell method. Triggers include mentions of scVI, scANVI, totalVI, PeakVI, MultiVI, DestVI, veloVI, sysVI, scArches, variational autoencoder, VAE, batch correction, data integration, multi-modal, CITE-seq, multiome, reference mapping, latent space.
testing
This skill should be used when scientists need help with research problem selection, project ideation, troubleshooting stuck projects, or strategic scientific decisions. Use this skill when users ask to pitch a new research idea, work through a project problem, evaluate project risks, plan research strategy, navigate decision trees, or get help choosing what scientific problem to work on. Typical requests include "I have an idea for a project", "I'm stuck on my research", "help me evaluate this project", "what should I work on", or "I need strategic advice about my research".
development
Run nf-core bioinformatics pipelines (rnaseq, sarek, atacseq) on sequencing data. Use when analyzing RNA-seq, WGS/WES, or ATAC-seq data—either local FASTQs or public datasets from GEO/SRA. Triggers on nf-core, Nextflow, FASTQ analysis, variant calling, gene expression, differential expression, GEO reanalysis, GSE/GSM/SRR accessions, or samplesheet creation.