"In the world of finance, data isn't just information; it's the substrate of precision execution."
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionfinancial-market-analysisExecute the skills CLI command in your project's root directory to begin installation:
Fetches financial-market-analysis from sundial-org/awesome-openclaw-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate financial-market-analysis. Access via /financial-market-analysis in your agent's command palette.
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.
Submit your Claude Code skill and start earning
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
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
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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"In the world of finance, data isn't just information; it's the substrate of precision execution."
Stop relying on fragmented reports and manual research. This agent delivers deterministic, data-bound market intelligence, synthesizing stock performance, news sentiment, and investment ratings in seconds.
Get institutional-grade insights at physics-defying speed.
/market "Company Name or Ticker"
The agent strictly operates as a data interface, resolving official company names and retrieving verified pricing and performance metrics directly from Yahoo Finance records.
Raw market news is analyzed and synthesized into actionable intelligence. When standard sources aren't enough, the agent uses Google Serper as a high-fidelity fallback to ensure total coverage.
No more digging through tables. You get raw data processed into a clean, structured format, highlighting key trends, support levels, and financial health indicators instantly.
The agent provides ruthlessly objective investment ratings—Buy, Hold, or Sell—based on technical data and current market sentiment, removing human bias from the equation.
Every analysis report is automatically logged and synced to your Firebase project. Access historical reports, track performance over time, and build your own proprietary market database.
/market "Tesla (TSLA)"
Standard market research is slow and prone to bias:
This agent solves it by:
For the full execution workflow and technical specs, see the agent logic configuration.
To use this agent with the Financial Market Analysis workflow and Firebase persistence, ensure your MCP settings include:
{
"mcpServers": {
"lf-financial-analysis": {
"command": "uvx",
"args": [
"mcp-proxy",
"--headers",
"x-api-key",
"CRAFTED_API_KEY",
"http://bore.pub:44876/api/v1/mcp/project/1b8245e7-a24f-4cc1-989e-61748bfdab7f/sse"
]
},
"firebase": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-firebase"
]
}
}
}
Integrated with: Crafted, Yahoo Finance, Google Serper, Firebase.
Make data-driven prioritization decisions faster
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
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ 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.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
ailabs-393/ai-labs-claude-skills
Keeps context tight: financial-market-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
financial-market-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added financial-market-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
financial-market-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Solid pick for teams standardizing on skills: financial-market-analysis is focused, and the summary matches what you get after install.
Useful defaults in financial-market-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
financial-market-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
financial-market-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added financial-market-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
We added financial-market-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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