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resource-scout▌

nicepkg/ai-workflow · updated Apr 8, 2026

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$npx skills add https://github.com/nicepkg/ai-workflow --skill resource-scout
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summary

Search and discover existing Claude Code skills and MCP servers before building custom solutions.

skill.md

Resource Scout

Search and discover existing Claude Code skills and MCP servers before building custom solutions.

Quick Search Strategy

For Skills:

  1. WebSearch: site:skillsmp.com [topic] or claude skill [topic]
  2. Check GitHub: awesome-claude-skills [topic]
  3. Browse: skillhub.club, claudeskills.info

For MCP:

  1. WebSearch: MCP server [tool/service name]
  2. Check: glama.ai/mcp/servers, mcpmarket.com
  3. Official: github.com/modelcontextprotocol/servers

Skill Search Workflow

Step 1: Define Need

Before searching, clarify:

  • What task needs to be accomplished?
  • What tools/services are involved?
  • Is it a common pattern (git, testing, API) or domain-specific?

Step 2: Search Marketplaces

Primary sources (largest catalogs):

Source URL Best For
SkillsMP skillsmp.com 71000+ skills, long-tail search
SkillHub.club skillhub.club AI-evaluated, quality filter
Claude Skills Hub claudeskills.info UI-friendly browsing

Search patterns:

# On SkillsMP
[domain] skill          → "marketing skill", "database skill"
[framework] claude      → "react claude", "fastapi claude"
[task] automation       → "deployment automation"

Step 3: Search GitHub

Curated lists:

  • github.com/keyuyuan/skillhub-awesome-skills - 精选清单
  • github.com/VoltAgent/awesome-claude-skills - 生态大全
  • github.com/ComposioHQ/awesome-claude-skills - 大量通用技能

Ready-to-use repositories:

  • github.com/alirezarezvani/claude-skills - Content/Marketing
  • github.com/gked2121/claude-skills - Workflow思维
  • github.com/Microck/ordinary-claude-skills - 超大集合
  • github.com/sickn33/antigravity-awesome-skills - 结构化

Search command:

# Use WebSearch tool
site:github.com "claude skill" [topic]
site:github.com "SKILL.md" [topic]

Step 4: Evaluate & Install

When skill found:

  1. Check last update date (prefer recent)
  2. Review SKILL.md for quality
  3. Check if has scripts/references
  4. Install with skill-downloader or manual copy

MCP Server Search Workflow

Step 1: Identify Integration Need

Common patterns:

  • Database access → postgres, mysql, sqlite MCP
  • GitHub workflow → github MCP
  • Cloud services → AWS, GCP, Azure MCPs
  • Communication → slack, discord MCPs
  • File systems → filesystem MCP

Step 2: Search Official Sources

Primary:

  • Official registry: registry.modelcontextprotocol.io
  • Official repo: github.com/modelcontextprotocol/servers

Directories:

Source URL Features
Glama glama.ai/mcp/servers Stars, downloads, updates
MCP Market mcpmarket.com Skills + MCP combined
mcpservers.org mcpservers.org Categorized
PulseMCP pulsemcp.com/servers Daily updates
Smithery smithery.ai Registry/distribution

Step 3: Search GitHub

# Use WebSearch tool
site:github.com "mcp server" [service]
site:github.com "@modelcontextprotocol" [service]

Awesome lists:

  • github.com/punkpeye/awesome-mcp-servers
  • github.com/wong2/awesome-mcp-servers

Step 4: Verify & Configure

When MCP found:

  1. Check compatibility (stdio vs HTTP)
  2. Review required environment variables
  3. Test connection locally
  4. Add to .claude/settings.json

Search by Category

Development Tools

Skills: "code review skill", "git commit skill", "testing skill"
MCP: "github mcp", "gitlab mcp", "jira mcp"

Databases

Skills: "database skill", "sql skill", "migration skill"
MCP: "postgres mcp", "mysql mcp", "mongodb mcp"

Content & Marketing

Skills: "content creator skill", "seo skill", "social media skill"
MCP: "wordpress mcp", "notion mcp"

Cloud & DevOps

Skills: "deployment skill", "kubernetes skill", "terraform skill"
MCP: "aws mcp", "gcp mcp", "azure mcp"

AI & Data

Skills: "data analysis skill", "ml skill"
MCP: "openai mcp", "huggingface mcp"

Complete Source Reference

See references/sources.md for full directory of all skill and MCP sources with detailed descriptions.

Best Practices

  1. Search before build - Always check existing resources first
  2. Prefer maintained - Choose skills with recent updates
  3. Check quality - Review SKILL.md structure and content
  4. Consider combining - Multiple simple skills > one complex custom
  5. Verify security - Review MCP permissions and token scopes
how to use resource-scout

How to use resource-scout 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 resource-scout
2

Execute installation command

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

$npx skills add https://github.com/nicepkg/ai-workflow --skill resource-scout

The skills CLI fetches resource-scout from GitHub repository nicepkg/ai-workflow 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/resource-scout

Reload or restart Cursor to activate resource-scout. Access the skill through slash commands (e.g., /resource-scout) 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)
  • No comments yet — start the thread.
general reviews

Ratings

4.7★★★★★38 reviews
  • ★★★★★Min Perez· Dec 28, 2024

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

  • ★★★★★Ganesh Mohane· Dec 20, 2024

    Registry listing for resource-scout matched our evaluation — installs cleanly and behaves as described in the markdown.

  • ★★★★★William Okafor· Dec 12, 2024

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

  • ★★★★★Soo Malhotra· Dec 4, 2024

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

  • ★★★★★Sakura Kapoor· Nov 23, 2024

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

  • ★★★★★Ren Okafor· Nov 19, 2024

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

  • ★★★★★Jin Dixit· Nov 15, 2024

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

  • ★★★★★Henry Thompson· Nov 3, 2024

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

  • ★★★★★William Sanchez· Oct 22, 2024

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

  • ★★★★★Luis Jain· Oct 14, 2024

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

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