update

anthropics/knowledge-work-plugins · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/anthropics/knowledge-work-plugins --skill update
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summary

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

skill.md

Update Command

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Keep your task list and memory current. Two modes:

  • Default: Sync tasks from external tools, triage stale items, check memory for gaps
  • --comprehensive: Deep scan chat, email, calendar, docs — flag missed todos and suggest new memories

Usage

/productivity:update
/productivity:update --comprehensive

Default Mode

1. Load Current State

Read TASKS.md and memory/ directory. If they don't exist, suggest /productivity:start first.

2. Sync Tasks from External Sources

Check for available task sources:

  • Project tracker (e.g. Asana, Linear, Jira) (if MCP available)
  • GitHub Issues (if in a repo): gh issue list --assignee=@me

If no sources are available, skip to Step 3.

Fetch tasks assigned to the user (open/in-progress). Compare against TASKS.md:

External task TASKS.md match? Action
Found, not in TASKS.md No match Offer to add
Found, already in TASKS.md Match by title (fuzzy) Skip
In TASKS.md, not in external No match Flag as potentially stale
Completed externally In Active section Offer to mark done

Present diff and let user decide what to add/complete.

3. Triage Stale Items

Review Active tasks in TASKS.md and flag:

  • Tasks with due dates in the past
  • Tasks in Active for 30+ days
  • Tasks with no context (no person, no project)

Present each for triage: Mark done? Reschedule? Move to Someday?

4. Decode Tasks for Memory Gaps

For each task, attempt to decode all entities (people, projects, acronyms, tools, links):

Task: "Send PSR to Todd re: Phoenix blockers"

Decode:
- PSR → ✓ Pipeline Status Report (in glossary)
- Todd → ✓ Todd Martinez (in people/)
- Phoenix → ? Not in memory

Track what's fully decoded vs. what has gaps.

5. Fill Gaps

Present unknown terms grouped:

I found terms in your tasks I don't have context for:

1. "Phoenix" (from: "Send PSR to Todd re: Phoenix blockers")
   → What's Phoenix?

2. "Maya" (from: "sync with Maya on API design")
   → Who is Maya?

Add answers to the appropriate memory files (people/, projects/, glossary.md).

6. Capture Enrichment

Tasks often contain richer context than memory. Extract and update:

  • Links from tasks → add to project/people files
  • Status changes ("launch done") → update project status, demote from CLAUDE.md
  • Relationships ("Todd's sign-off on Maya's proposal") → cross-reference people
  • Deadlines → add to project files

7. Report

Update complete:
- Tasks: +3 from project tracker (e.g. Asana), 1 completed, 2 triaged
- Memory: 2 gaps filled, 1 project enriched
- All tasks decoded ✓

Comprehensive Mode (--comprehensive)

Everything in Default Mode, plus a deep scan of recent activity.

Extra Step: Scan Activity Sources

Gather data from available MCP sources:

  • Chat: Search recent messages, read active channels
  • Email: Search sent messages
  • Documents: List recently touched docs
  • Calendar: List recent + upcoming events

Extra Step: Flag Missed Todos

Compare activity against TASKS.md. Surface action items that aren't tracked:

## Possible Missing Tasks

From your activity, these look like todos you haven't captured:

1. From chat (Jan 18):
   "I'll send the updated mockups by Friday"
   → Add to TASKS.md?

2. From meeting "Phoenix Standup" (Jan 17):
   You have a recurring meeting but no Phoenix tasks active
   → Anything needed here?

3. From email (Jan 16):
   "I'll review the API spec this week"
   → Add to TASKS.md?

Let user pick which to add.

Extra Step: Suggest New Memories

Surface new entities not in memory:

## New People (not in memory)
| Name | Frequency | Context |
|------|-----------|---------|
| Maya Rodriguez | 12 mentions | design, UI reviews |
| Alex K | 8 mentions | DMs about API |

## New Projects/Topics
| Name | Frequency | Context |
|------|-----------|---------|
| Starlight | 15 mentions | planning docs, product |

## Suggested Cleanup
- **Horizon project** — No mentions in 30 days. Mark completed?

Present grouped by confidence. High-confidence items offered to add directly; low-confidence items asked about.

Notes

  • Never auto-add tasks or memories without user confirmation
  • External source links are preserved when available
  • Fuzzy matching on task titles handles minor wording differences
  • Safe to run frequently — only updates when there's new info
  • --comprehensive always runs interactively
how to use update

How to use update on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add update
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/anthropics/knowledge-work-plugins --skill update

The skills CLI fetches update from GitHub repository anthropics/knowledge-work-plugins and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/update

Reload or restart Cursor to activate update. Access the skill through slash commands (e.g., /update) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.472 reviews
  • Jin Anderson· Dec 28, 2024

    I recommend update for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Neel Haddad· Dec 24, 2024

    We added update from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kofi Desai· Dec 24, 2024

    update reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Neel Nasser· Dec 20, 2024

    Keeps context tight: update is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Min Kim· Dec 16, 2024

    update is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Chaitanya Patil· Dec 8, 2024

    Keeps context tight: update is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Kofi Chawla· Dec 8, 2024

    update fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Piyush G· Nov 27, 2024

    update has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Min Huang· Nov 19, 2024

    update reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Min Sanchez· Nov 19, 2024

    We added update from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

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