Initialize the productivity system and open the dashboard. Use when setting up the plugin for the first time, bootstrapping working memory from your existing task list, or decoding the shorthand (nicknames, acronyms, project codenames) you use in your todos.
npx skills add https://github.com/anthropics/knowledge-work-plugins --skill start
> If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Initialize the task and memory systems, then open the unified dashboard.
Check the working directory for:
TASKS.md — task listCLAUDE.md — working memorymemory/ — deep memory directorydashboard.html — the visual UIIf TASKS.md doesn't exist: Create it with the standard template (see task-management skill). Place it in the current working directory.
If dashboard.html doesn't exist: Copy it from ${CLAUDE_PLUGIN_ROOT}/skills/dashboard.html to the current working directory.
If CLAUDE.md and memory/ don't exist: This is a fresh setup — after opening the dashboard, begin the memory bootstrap workflow (see below). Place these in the current working directory.
Do NOT use open or xdg-open — in Cowork, the agent runs in a VM and shell open commands won't reach the user's browser. Instead, tell the user: "Dashboard is ready at dashboard.html. Open it from your file browser to get started."
If everything was already initialized:
Dashboard open. Your tasks and memory are both loaded.
- /productivity:update to sync tasks and check memory
- /productivity:update --comprehensive for a deep scan of all activity
If memory hasn't been bootstrapped yet, continue to step 5.
Only do this if CLAUDE.md and memory/ don't exist yet.
The best source of workplace language is the user's actual task list. Real tasks = real shorthand.
Ask the user:
Where do you keep your todos or task list? This could be:
- A local file (e.g., TASKS.md, todo.txt)
- An app (e.g. Asana, Linear, Jira, Notion, Todoist)
- A notes file
I'll use your tasks to learn your workplace shorthand.
Once you have access to the task list:
For each task item, analyze it for potential shorthand:
For each item, decode it interactively:
Task: "Send PSR to Todd re: Phoenix blockers"
I see some terms I want to make sure I understand:
1. **PSR** - What does this stand for?
2. **Todd** - Who is Todd? (full name, role)
3. **Phoenix** - Is this a project codename? What's it about?
Continue through each task, asking only about terms you haven't already decoded.
After task list decoding, offer:
Do you want me to do a comprehensive scan of your messages, emails, and documents?
This takes longer but builds much richer context about the people, projects, and terms in your work.
Or we can stick with what we have and add context later.
If they choose comprehensive scan:
Gather data from available MCP sources:
Build a braindump of people, projects, and terms found. Present findings grouped by confidence:
From everything gathered, create:
CLAUDE.md (working memory, ~50-80 lines):
# Memory
## Me
[Name], [Role] on [Team].
## People
| Who | Role |
|-----|------|
| **[Nickname]** | [Full Name], [role] |
## Terms
| Term | Meaning |
|------|---------|
| [acronym] | [expansion] |
## Projects
| Name | What |
|------|------|
| **[Codename]** | [description] |
## Preferences
- [preferences discovered]
memory/ directory:
memory/glossary.md — full decoder ring (acronyms, terms, nicknames, codenames)memory/people/{name}.md — individual profilesmemory/projects/{name}.md — project detailsmemory/context/company.md — teams, tools, processesProductivity system ready:
- Tasks: TASKS.md (X items)
- Memory: X people, X terms, X projects
- Dashboard: open in browser
Use /productivity:update to keep things current (add --comprehensive for a deep scan).
Expert startup business analyst specializing in market sizing, financial modeling, competitive analysis, and strategic planning for early-stage companies. Use PROACTIVELY when the user asks about market opportunity, TAM/SAM/SOM, financial projections, unit economics, competitive landscape, team planning, startup metrics, or business strategy for pre-seed through Series A startups.
This skill should be used when the user asks to "plan team structure", "determine hiring needs", "design org chart", "calculate compensation", "plan equity allocation", or requests organizational design and headcount planning for a startup.
End-to-end bulk RNA-seq orchestrator — takes raw FASTQ reads through QC and trimming (FastQC, fastp/Trim Galore), alignment and quantification (STAR, Salmon, featureCounts), assembles a gene-level counts matrix, then hands off to differential expression (pydeseq2), pathway/GSEA enrichment (pathway-enrichment), and publication figures (scientific-visualization). Use whenever the user has bulk RNA-seq reads or quant output and wants a complete, reproducible differential-expression workflow — e.g. "analyze my RNA-seq", "FASTQ to DESeq2", "run nf-core/rnaseq", "STAR/Salmon quantification", "build a counts matrix for DESeq2", or "go from reads to differentially expressed genes and enriched pathways". Routes between an nf-core/rnaseq (Nextflow) path and a standalone STAR/Salmon path, and covers experimental design, strandedness, and QC gates. For single-cell RNA-seq use the scanpy skill instead.
Generate project status reports from Jira issues and publish to Confluence. When an agent needs to: (1) Create a status report for a project, (2) Summarize project progress or updates, (3) Generate weekly/daily reports from Jira, (4) Publish status summaries to Confluence, or (5) Analyze project blockers and completion. Queries Jira issues, categorizes by status/priority, and creates formatted reports for delivery managers and executives.
Evaluates market bubble risk through quantitative data-driven analysis using the revised Minsky/Kindleberger framework v2.1. Prioritizes objective metrics (Put/Call, VIX, margin debt, breadth, IPO data) over subjective impressions. Features strict qualitative adjustment criteria with confirmation bias prevention. Supports practical investment decisions with mandatory data collection and mechanical scoring. Use when user asks about bubble risk, valuation concerns, or profit-taking timing.
Google Workflow: Today's meetings + open tasks as a standup summary.
Read event data from a Google Sheets spreadsheet and create Google Calendar entries for each row.
Create professional, dark-themed SVG diagrams of any type — architecture diagrams, flowcharts, sequence diagrams, structural diagrams, mind maps, timelines, illustrative/conceptual diagrams, and more. Use this skill whenever the user asks for any kind of technical or conceptual diagram, visualization of a system, process flow, data flow, component relationship, network topology, decision tree, org chart, state machine, or any visual representation of structure/logic/process. Also trigger when the user says "画个图" "画一个架构图" "diagram" "flowchart" "sequence diagram" "draw me a ..." or uploads content and asks to visualize it. Output is always a standalone .svg file.
Take anthropics/knowledge-work-plugins-productivity-start from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.