business/enterprise-search/memory-management/SKILL.md
Two-tier memory system that makes Claude a true workplace collaborator. Decodes shorthand, acronyms, nicknames, and internal language so Claude understands requests like a colleague would. CLAUDE.md for working memory, memory/ directory for the full knowledge base.
npx skillsauth add harsh040506/claude-code-unified-skill-plugin-library memory-managementInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
Memory makes Claude your workplace collaborator - someone who speaks your internal language.
Transform shorthand into understanding:
User: "ask todd to do the PSR for oracle"
↓ Claude decodes
"Ask Todd Martinez (Finance lead) to prepare the Pipeline Status Report
for the Oracle Systems deal ($2.3M, closing Q2)"
Without memory, that request is meaningless. With memory, Claude knows:
CLAUDE.md ← Hot cache (~30 people, common terms)
memory/
glossary.md ← Full decoder ring (everything)
people/ ← Complete profiles
projects/ ← Project details
context/ ← Company, teams, tools
CLAUDE.md (Hot Cache):
memory/glossary.md (Full Glossary):
memory/people/, projects/, context/:
User: "ask todd about the PSR for phoenix"
1. Check CLAUDE.md (hot cache)
→ Todd? ✓ Todd Martinez, Finance
→ PSR? ✓ Pipeline Status Report
→ Phoenix? ✓ DB migration project
2. If not found → search memory/glossary.md
→ Full glossary has everyone/everything
3. If still not found → ask user
→ "What does X mean? I'll remember it."
This tiered approach keeps CLAUDE.md lean (~100 lines) while supporting unlimited scale in memory/.
CLAUDE.md in current working directorymemory/ subdirectoryUse tables for compactness. Target ~50-80 lines total.
# Memory
## Me
[Name], [Role] on [Team]. [One sentence about what I do.]
## People
| Who | Role |
|-----|------|
| **Todd** | Todd Martinez, Finance lead |
| **Sarah** | Sarah Chen, Engineering (Platform) |
| **Greg** | Greg Wilson, Sales |
→ Full list: memory/glossary.md, profiles: memory/people/
## Terms
| Term | Meaning |
|------|---------|
| PSR | Pipeline Status Report |
| P0 | Drop everything priority |
| standup | Daily 9am sync |
→ Full glossary: memory/glossary.md
## Projects
| Name | What |
|------|------|
| **Phoenix** | DB migration, Q2 launch |
| **Horizon** | Mobile app redesign |
→ Details: memory/projects/
## Preferences
- 25-min meetings with buffers
- Async-first, Slack over email
- No meetings Friday afternoons
memory/glossary.md - The decoder ring:
# Glossary
Workplace shorthand, acronyms, and internal language.
## Acronyms
| Term | Meaning | Context |
|------|---------|---------|
| PSR | Pipeline Status Report | Weekly sales doc |
| OKR | Objectives & Key Results | Quarterly planning |
| P0/P1/P2 | Priority levels | P0 = drop everything |
## Internal Terms
| Term | Meaning |
|------|---------|
| standup | Daily 9am sync in #engineering |
| the migration | Project Phoenix database work |
| ship it | Deploy to production |
| escalate | Loop in leadership |
## Nicknames → Full Names
| Nickname | Person |
|----------|--------|
| Todd | Todd Martinez (Finance) |
| T | Also Todd Martinez |
## Project Codenames
| Codename | Project |
|----------|---------|
| Phoenix | Database migration |
| Horizon | New mobile app |
memory/people/{name}.md:
# Todd Martinez
**Also known as:** Todd, T
**Role:** Finance Lead
**Team:** Finance
**Reports to:** CFO (Michael Chen)
## Communication
- Prefers Slack DM
- Quick responses, very direct
- Best time: mornings
## Context
- Handles all PSRs and financial reporting
- Key contact for deal approvals over $500k
- Works closely with Sales on forecasting
## Notes
- Cubs fan, likes talking baseball
memory/projects/{name}.md:
# Project Phoenix
**Codename:** Phoenix
**Also called:** "the migration"
**Status:** Active, launching Q2
## What It Is
Database migration from legacy Oracle to PostgreSQL.
## Key People
- Sarah - tech lead
- Todd - budget owner
- Greg - stakeholder (sales impact)
## Context
$1.2M budget, 6-month timeline. Critical path for Horizon project.
memory/context/company.md:
# Company Context
## Tools & Systems
| Tool | Used for | Internal name |
|------|----------|---------------|
| Slack | Communication | - |
| Asana | Engineering tasks | - |
| Salesforce | CRM | "SF" or "the CRM" |
| Notion | Docs/wiki | - |
## Teams
| Team | What they do | Key people |
|------|--------------|------------|
| Platform | Infrastructure | Sarah (lead) |
| Finance | Money stuff | Todd (lead) |
| Sales | Revenue | Greg |
## Processes
| Process | What it means |
|---------|---------------|
| Weekly sync | Monday 10am all-hands |
| Ship review | Thursday deploy approval |
Always decode shorthand before acting on requests:
1. CLAUDE.md (hot cache) → Check first, covers 90% of cases
2. memory/glossary.md → Full glossary if not in hot cache
3. memory/people/, projects/ → Rich detail when needed
4. Ask user → Unknown term? Learn it.
Example:
User: "ask todd to do the PSR for oracle"
CLAUDE.md lookup:
"todd" → Todd Martinez, Finance ✓
"PSR" → Pipeline Status Report ✓
"oracle" → (not in hot cache)
memory/glossary.md lookup:
"oracle" → Oracle Systems deal ($2.3M) ✓
Now Claude can act with full context.
When user says "remember this" or "X means Y":
Glossary items (acronyms, terms, shorthand):
People:
Projects:
Preferences: Add to CLAUDE.md Preferences section
When user asks "who is X" or "what does X mean":
Use /productivity:start to initialize by scanning your chat, calendar, email, and documents. Extracts people, projects, and starts building the glossary.
todd-martinez.md, project-phoenix.md)| Type | CLAUDE.md (Hot Cache) | memory/ (Full Storage) | |------|----------------------|------------------------| | Person | Top ~30 frequent contacts | glossary.md + people/{name}.md | | Acronym/term | ~30 most common | glossary.md (complete list) | | Project | Active projects only | glossary.md + projects/{name}.md | | Nickname | In Key People if top 30 | glossary.md (all nicknames) | | Company context | Quick reference only | context/company.md | | Preferences | All preferences | - | | Historical/stale | ✗ Remove | ✓ Keep in memory/ |
Promote to CLAUDE.md when:
Demote to memory/ only when:
This keeps CLAUDE.md fresh and relevant.
testing
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.