Implements cookie-based authentication bridging MCP tools and browser automation, with agents obtaining auth cookies via MCP then using them for web requests
Provides complete Node.js stack templates using Express, SQLite, @longrun/turtle for MCP, and @atxp packages for agent identity and optional payments
Includes query-string cookie bootstrap pattern for agent browsers that cannot set HTTP-
Fetches clawdirect-dev from napoleond/clawdirect and configures it for Cursor.
3
Select Cursor when prompted
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
◆ Which agents do you want to install to?
│
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4
Verify installation
Confirm successful installation by checking the skill directory location:
.cursor/skills/clawdirect-dev
Restart Cursor to activate clawdirect-dev. Access via /clawdirect-dev in your agent's command palette.
⚠
Security 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 environment. Always review source, verify the publisher, and test in isolation before production.
Browser: Agents use browser automation tools to visit your website, click buttons, fill forms, and navigate—just like humans do
MCP tools: Agents call your MCP endpoints directly for programmatic actions (authentication, payments, etc.)
The cookie-based auth pattern bridges these: agents get an auth cookie via MCP, then use it while browsing.
Important: Agent browsers often cannot set HTTP-only cookies directly. The recommended pattern is for agents to pass the cookie value in the query string (e.g., ?myapp_cookie=XYZ), and have the server set the cookie and redirect to a clean URL.
import Database from'better-sqlite3';import crypto from'crypto';constDB_PATH= process.env.DB_PATH||'./data.db';let db: Database.Database;exportfunctiongetDb(): Database.Database {if(!db){ db =newDatabase(DB_PATH); db.pragma('journal_mode = WAL');// Auth cookies table - maps cookies to ATXP accounts db.exec(` CREATE TABLE IF NOT EXISTS auth_cookies (
cookie_value TEXT PRIMARY KEY,
atxp_account TEXT NOT NULL,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
)
`);// Add your app's tables here}return db;}exportfunctioncreateAuthCookie(atxpAccount:string):string{const cookieValue = crypto.randomBytes(32).toString('hex');getDb().prepare(` INSERT INTO auth_cookies (cookie_value, atxp_account)
VALUES (?, ?)
`).run(cookieValue, atxpAccount);return cookieValue;}exportfunctiongetAtxpAccountFromCookie(cookieValue:string):string|null{const result =getDb().prepare(` SELECT atxp_account FROM auth_cookies WHERE cookie_value = ?
`).get(cookieValue)as{ atxp_account:string}|undefined;return result?.atxp_account ||null;}
Step 3: MCP Tools with Cookie Tool
Create src/tools.ts:
import{ defineTool }from'@longrun/turtle';import{ z }from'zod';import{ requirePayment, atxpAccountId }from'@atxp/server';import BigNumber from'bignumber.js';import{ createAuthCookie }from'./db.js';// Cookie tool - agents call this to get browser authexportconst cookieTool =defineTool('myapp_cookie',// Replace 'myapp' with your app name'Get an authentication cookie for browser use. Set this cookie to authenticate when using the web interface.', z.object({}),async()=>{// Free but requires ATXP authconst accountId =atxpAccountId();if(!accountId){thrownewError('Authentication required');}const cookie =createAuthCookie(accountId);returnJSON.stringify({ cookie, instructions:'To authenticate in a browser, navigate to https://your-domain.com?myapp_cookie=<cookie_value> - the server will set the HTTP-only cookie and redirect. Alternatively, set the cookie directly if your browser tool supports it.'});});// Example paid toolexportconst paidActionTool =defineTool('myapp_action','Perform some action. Cost: $0.10', z.object({ input: z.string().describe('Input for the action')}
✓
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
›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
Steps
1Install product management skill
2Start with user story generation for known feature
3Progress to competitive analysis: research 2-3 competitors
4Use for roadmap prioritization: apply RICE/ICE scoring
5Draft stakeholder communications and refine based on feedback
6Build template library for recurring PM tasks
7Share 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
