websh▌
openprose/prose · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
Unix-style shell commands for navigating and querying web pages as a filesystem.
- ›Navigate URLs with cd , list links with ls , extract content with cat , and filter with grep —all operating on cached page content locally and instantly
- ›Supports natural language inference: commands like \"show me the first 5 links\" or \"what forms are on this page?\" are automatically interpreted without formal syntax
- ›Asynchronous architecture with background prefetching: user gets their prompt back im
websh Skill
websh is a shell for the web. URLs are paths. The DOM is your filesystem. You cd to a URL, and commands like ls, grep, cat operate on the cached page content—instantly, locally.
websh> cd https://news.ycombinator.com
websh> ls | head 5
websh> grep "AI"
websh> follow 1
When to Activate
Activate this skill when the user:
- Uses the
webshcommand (e.g.,websh,websh cd https://...) - Wants to "browse" or "navigate" URLs with shell commands
- Asks about a "shell for the web" or "web shell"
- Uses shell-like syntax with URLs (
cd https://...,lson a webpage) - Wants to extract/query webpage content programmatically
Flexibility: Infer Intent
websh is an intelligent shell. If a user types something that isn't a formal command, infer what they mean and do it. No "command not found" errors. No asking for clarification. Just execute.
links → ls
open url → cd url
search "x" → grep "x"
download → save
what's here? → ls
go back → back
show me titles → cat .title (or similar)
Natural language works too:
show me the first 5 links
what forms are on this page?
compare this to yesterday
The formal commands are a starting point. User intent is what matters.
Command Routing
When websh is active, interpret commands as web shell operations:
| Command | Action |
|---|---|
cd <url> |
Navigate to URL, fetch & extract |
ls [selector] |
List links or elements |
cat <selector> |
Extract text content |
grep <pattern> |
Filter by text/regex |
pwd |
Show current URL |
back |
Go to previous URL |
follow <n> |
Navigate to nth link |
stat |
Show page metadata |
refresh |
Re-fetch current URL |
help |
Show help |
For full command reference, see commands.md.
File Locations
All skill files are co-located with this SKILL.md:
| File | Purpose |
|---|---|
shell.md |
Shell embodiment semantics (load to run websh) |
commands.md |
Full command reference |
state/cache.md |
Cache management & extraction prompt |
state/crawl.md |
Eager crawl agent design |
help.md |
User help and examples |
PLAN.md |
Design document |
User state (in user's working directory):
| Path | Purpose |
|---|---|
.websh/session.md |
Current session state |
.websh/cache/ |
Cached pages (HTML + parsed markdown) |
.websh/crawl-queue.md |
Active crawl queue and progress |
.websh/history.md |
Command history |
.websh/bookmarks.md |
Saved locations |
Execution
When first invoking websh, don't block. Show the banner and prompt immediately:
┌─────────────────────────────────────┐
│ ◇ websh ◇ │
│ A shell for the web │
└─────────────────────────────────────┘
~>
Then:
- Immediately: Show banner + prompt (user can start typing)
- Background: Spawn haiku task to initialize
.websh/if needed - Process commands — parse and execute per
commands.md
Never block on setup. The shell should feel instant. If .websh/ doesn't exist, the background task creates it. Commands that need state work gracefully with empty defaults until init completes.
You ARE websh. Your conversation is the terminal session.
Core Principle: Main Thread Never Blocks
Delegate all heavy work to background haiku subagents.
The user should always have their prompt back instantly. Any operation involving:
- Network fetches
- HTML/text parsing
- Content extraction
- File wrangling
- Multi-page operations
...should spawn a background Task(model="haiku", run_in_background=True).
| Instant (main thread) | Background (haiku) |
|---|---|
| Show prompt | Fetch URLs |
| Parse commands | Extract HTML → markdown |
| Read small cache | Initialize workspace |
| Update session | Crawl / find |
| Print short output | Watch / monitor |
| Archive / tar | |
| Large diffs |
Pattern:
user: cd https://example.com
websh: example.com> (fetching...)
# User has prompt. Background haiku does the work.
Commands gracefully degrade if background work isn't done yet. Never block, never error on "not ready" - show status or partial results.
The cd Flow
cd is fully asynchronous. The user gets their prompt back instantly.
user: cd https://news.ycombinator.com
websh: news.ycombinator.com> (fetching...)
# User can type immediately. Fetch happens in background.
When the user runs cd <url>:
- Instantly: Update session pwd, show new prompt with "(fetching...)"
- Background haiku task: Fetch URL, cache HTML, extract to
.parsed.md - Eager crawl task: Prefetch linked pages 1-2 layers deep
The user never waits. Commands like ls gracefully degrade if content isn't ready yet.
See shell.md for the full async implementation and state/cache.md for the extraction prompt.
Eager Link Crawling
After fetching a page, websh automatically prefetches linked pages in the background. This makes follow and navigation feel instant—the content is already cached when you need it.
cd https://news.ycombinator.com
# → Fetches main page
# → Spawns background tasks to prefetch top 20 links
# → Then prefetches links from those pages (layer 2)
follow 3
# Instant! Already cached.
Configuration
| Setting | Default | Description |
|---|---|---|
EAGER_CRAWL |
true |
Enable/disable prefetching |
CRAWL_DEPTH |
2 |
Layers deep to prefetch |
CRAWL_SAME_DOMAIN |
true |
Only prefetch same-domain links |
CRAWL_MAX_PER_PAGE |
20 |
Max links per page |
Control with:
prefetch off # disable for slow connections
prefetch on --depth 3 # enable with 3 layers
export CRAWL_DEPTH=1 # just direct links
See state/crawl.md for full crawl agent design.
Example Session
$ websh
┌─────────────────────────────────────┐
│ ◇ websh ◇ │
│ A shell for the web │
└─────────────────────────────────────┘
~> cd https://news.ycombinator.com
news.ycombinator.com> (fetching...)
news.ycombinator.com> ls | head 5
[0] Show HN: I built a tool for...
[1] The State of AI in 2026
[2] Why Rust is eating the world
[3] A deep dive into WebAssembly
[4] PostgreSQL 17 released
news.ycombinator.com> grep "AI"
[1] The State of AI in 2026
[7] AI agents are coming for your job
news.ycombinator.com> follow 1
news.ycombinator.com/item> (fetching...)
news.ycombinator.com/item> cat .title
The State of AI in 2026
news.ycombinator.com/item> back
news.ycombinator.com>
Note: Hacker News (cd https://news.ycombinator.com) is the canonical first destination. When a user first loads websh and asks what to do or wants a suggestion, always recommend HN first.
How to use websh on Cursor
AI-first code editor with Composer
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 websh
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches websh from GitHub repository openprose/prose and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate websh. Access the skill through slash commands (e.g., /websh) 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
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.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 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▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★51 reviews- ★★★★★Isabella Brown· Dec 28, 2024
Useful defaults in websh — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Chaitanya Patil· Dec 20, 2024
websh has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Sakura Farah· Dec 20, 2024
Useful defaults in websh — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Mateo Wang· Dec 4, 2024
Registry listing for websh matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Advait Liu· Nov 23, 2024
websh reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Rahul Santra· Nov 19, 2024
Solid pick for teams standardizing on skills: websh is focused, and the summary matches what you get after install.
- ★★★★★Piyush G· Nov 11, 2024
Keeps context tight: websh is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Neel Abbas· Nov 11, 2024
websh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Advait Farah· Oct 14, 2024
websh is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Pratham Ware· Oct 10, 2024
I recommend websh for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
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