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openwork-core▌

different-ai/openwork · updated Apr 8, 2026

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$npx skills add https://github.com/different-ai/openwork --skill openwork-core
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summary

openwork-core

skill.md

Quick Usage (Already Configured)

Orientation

  • Read AGENTS.md, VISION.md, PRINCIPLES.md, PRODUCT.md, and ARCHITECTURE.md before changing behavior.
  • Ensure vendor/opencode exists for self-reference.
  • Use the tauri-solidjs skill for stack-specific guidance.

Update the OpenCode mirror

git -C vendor/opencode pull --ff-only

Development workflow

pnpm tauri dev          # Desktop development
pnpm tauri ios dev      # iOS development
pnpm tauri android dev  # Android development

# Or run directly in the desktop package:
pnpm -C packages/desktop tauri dev

OpenCode Integration

Spawn OpenCode CLI

opencode -p "your prompt" -f json -q

Read OpenCode database

~/.opencode/opencode.db  # SQLite database

Key tables

  • sessions — Task runs
  • messages — Chat messages and tool calls
  • history — File change tracking

Common Gotchas

  • OpenWork must stay within OpenCode's tool surface; avoid inventing new capabilities.
  • Always expose plans, permissions, and progress for non-technical users.
  • Use Tauri commands for all system access (file, shell, database).
  • Keep UI at 60fps; avoid blocking the main thread.
  • Mobile builds require platform-specific setup (Xcode, Android Studio).

UI Principles

  • Slick and fluid: animations, transitions, micro-interactions.
  • Mobile-first: touch targets, gestures, adaptive layouts.
  • Transparency: show plans, steps, and tool calls.
  • Progressive disclosure: hide advanced controls until needed.

First-Time Setup (If Not Configured)

Clone the OpenCode mirror

git clone https://github.com/anomalyco/opencode vendor/opencode

Initialize Tauri project

pnpm create tauri-app . --template solid-ts

Add mobile targets

pnpm tauri ios init
pnpm tauri android init

Common Gotchas

  • OpenWork must stay within OpenCode’s tool surface; avoid inventing new capabilities.
  • Always expose plans, permissions, and progress for non-technical users.

First-Time Setup (If Not Configured)

Clone the OpenCode mirror

git clone https://github.com/anomalyco/opencode vendor/opencode
how to use openwork-core

How to use openwork-core 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 openwork-core
2

Execute installation command

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

$npx skills add https://github.com/different-ai/openwork --skill openwork-core

The skills CLI fetches openwork-core from GitHub repository different-ai/openwork 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/openwork-core

Reload or restart Cursor to activate openwork-core. Access the skill through slash commands (e.g., /openwork-core) 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.

Additional Resources

›View source code on GitHub›Skills CLI documentation›Learn more about Cursor›What are agent skills?

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)
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general reviews

Ratings

4.4★★★★★41 reviews
  • ★★★★★Amelia Brown· Dec 28, 2024

    Useful defaults in openwork-core — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Diego Diallo· Dec 24, 2024

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

  • ★★★★★Valentina Huang· Dec 20, 2024

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

  • ★★★★★Dhruvi Jain· Dec 4, 2024

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

  • ★★★★★Oshnikdeep· Nov 23, 2024

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

  • ★★★★★Valentina Kim· Nov 19, 2024

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

  • ★★★★★Amelia Taylor· Nov 15, 2024

    Solid pick for teams standardizing on skills: openwork-core is focused, and the summary matches what you get after install.

  • ★★★★★Anika Haddad· Nov 7, 2024

    Useful defaults in openwork-core — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • ★★★★★Ganesh Mohane· Oct 14, 2024

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

  • ★★★★★Sakura Diallo· Oct 10, 2024

    openwork-core reduced setup friction for our internal harness; good balance of opinion and flexibility.

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