business/enterprise-search/task-management/SKILL.md
Simple task management using a shared TASKS.md file. Reference this when the user asks about their tasks, wants to add/complete tasks, or needs help tracking commitments.
npx skillsauth add harsh040506/claude-code-unified-skill-plugin-library task-managementInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Tasks are tracked in a simple TASKS.md file that both you and the user can edit.
Always use TASKS.md in the current working directory.
A visual dashboard is available for managing tasks and memory. On first interaction with tasks:
dashboard.html exists in the current working directory${CLAUDE_PLUGIN_ROOT}/skills/dashboard.html to the current working directory/productivity:start to set up the full system."The task board:
TASKS.md fileWhen creating a new TASKS.md, use this exact template (without example tasks):
# Tasks
## Active
## Waiting On
## Someday
## Done
Task format:
- [ ] **Task title** - context, for whom, due date- [x] ~~Task~~ (date)When user asks "what's on my plate" / "my tasks":
When user says "add a task" / "remind me to":
- [ ] **Task** formatWhen user says "done with X" / "finished X":
[ ] to [x]~~task~~When user asks "what am I waiting on":
When summarizing meetings or conversations, offer to add extracted tasks:
Ask before adding - don't auto-add without confirmation.
testing
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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.
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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.