Smithery Logo
MCPsSkillsDocsPricing
Login
Smithery Logo

Accelerating the Agent Economy

Resources

DocumentationPrivacy PolicySystem Status

Company

PricingAboutBlog

Connect

© 2026 Smithery. All rights reserved.

    Mburdo

    ground

    Mburdo/ground
    Security
    46

    About

    SKILL.md

    Install

    Install via Skills CLI

    or add to your agent
    • Claude Code
      Claude Code
    • Codex
      Codex
    • OpenClaw
      OpenClaw
    • Cursor
      Cursor
    • Amp
      Amp
    • GitHub Copilot
      GitHub Copilot
    • Gemini CLI
      Gemini CLI
    • Kilo Code
      Kilo Code
    • Junie
      Junie
    • Replit
      Replit
    • Windsurf
      Windsurf
    • Cline
      Cline
    • Continue
      Continue
    • OpenCode
      OpenCode
    • OpenHands
      OpenHands
    • Roo Code
      Roo Code
    • Augment
      Augment
    • Goose
      Goose
    • Trae
      Trae
    • Zencoder
      Zencoder
    • Antigravity
      Antigravity
    ├─
    ├─
    └─

    About

    Verify external libraries, APIs, and frameworks against current documentation...

    SKILL.md

    Ground — External Documentation

    Verify external dependencies against current documentation before implementation. Direct execution.

    Design rationale: This skill executes directly rather than spawning subagents because grounding is a simple query + verification sequence (~300 tokens), not substantial analytical work. Per Lita research: "Simple agents achieve 97% of complex system performance with 15x less code."

    When This Applies

    Signal Action
    About to write import for external lib Ground first
    Using API/SDK methods Verify current syntax
    Framework-specific patterns Check version compatibility
    Auth/security code Always verify current best practices
    User says "ground" or "verify" Run full grounding check
    New library or major version Deep grounding

    Default: When uncertain about external APIs, ground.


    Tool Reference

    Exa MCP Tools

    Tool Purpose
    web_search_exa(query) General documentation search
    get_code_context_exa(query) Code examples from GitHub/tutorials
    crawling(url) Extract content from specific URLs

    Decision Tree

    Where does truth live?
    
    EXTERNAL DOCS ──► /ground (this skill)
                     "What's the current API for X?"
    
    CODEBASE ───────► /explore (warp-grep)
                     "How does X work in our code?"
    
    HISTORY ────────► /recall (cm + cass)
                     "How did we do this before?"
    
    TASKS ──────────► bv --robot-*
                     "What should I work on?"
    

    Execution Flow

    Execute these steps directly. No subagents needed.

    Step 1: Identify What Needs Grounding

    Categories that need verification:

    Category Why Risk
    Imports/Initialization Syntax changes between versions High
    API Methods Methods get renamed/deprecated High
    Configuration Options/flags evolve Medium
    Async Patterns Async APIs vary significantly Medium
    Auth/Security Security best practices change Critical
    Data Validation Validators/schemas evolve Medium

    Step 2: Construct Query

    Formula:

    {library_name} {specific_feature} {version_if_known} 2024 2025
    

    Examples:

    FastAPI Pydantic v2 model_validator 2024 2025
    Next.js 14 app router server components
    React useOptimistic hook 2024
    Prisma findMany where clause 2024
    

    Strengthening queries:

    • Add version number if known
    • Add year for recency (2024, 2025)
    • Add "official" or "docs" for authoritative sources
    • Add "migration" if moving between versions

    Step 3: Execute Search

    For documentation:

    web_search_exa("{library} {feature} {version} 2024 2025")
    

    For code examples:

    get_code_context_exa("{library} {pattern} implementation example")
    

    For specific page:

    crawling("{url}")
    

    Step 4: Verify Results

    Criterion Pass If
    Source Official docs or reputable repo
    Freshness Updated within 12 months
    Version Matches your dependency
    Completeness Full import + usage pattern
    Status Not deprecated

    Step 5: Record Grounding Status

    Track in your work:

    ## Grounding Status
    | Pattern | Query | Source | Status |
    |---------|-------|--------|--------|
    | `@model_validator` | "Pydantic v2 2024" | docs.pydantic.dev | ✅ Verified |
    | `useOptimistic` | "React 19 2024" | react.dev | ✅ Verified |
    

    Status values:

    • ✅ Verified — Matches current docs
    • ⚠️ Changed — API changed, updated approach
    • ❌ Deprecated — Found alternative
    • ❓ Unverified — Couldn't confirm, flagged

    Query Patterns

    Current API Documentation

    "{library} {method} documentation 2024"
    "{library} {feature} API reference"
    "{library} official docs {feature}"
    

    Migration Between Versions

    "{library} v{old} to v{new} migration"
    "{library} {version} breaking changes"
    "{library} upgrade guide {version}"
    

    Code Examples

    get_code_context_exa("{library} {pattern} implementation example")
    get_code_context_exa("{library} {use_case} tutorial")
    

    Security/Auth Patterns

    "{auth_method} best practices 2024"
    "{library} authentication {pattern} security"
    "OAuth PKCE {language} 2024"
    

    Error Resolution

    "{library} {error_message} fix"
    "{library} {error_type} troubleshooting"
    

    Grounding Depth Levels

    Depth When What to Check
    Quick Familiar pattern, just confirming One query, verify method exists
    Standard Normal implementation Query + check for deprecation warnings
    Deep Security/auth, new library, major version Multiple queries, read changelog, check issues

    Version Sensitivity Signals

    Ground more carefully when you see:

    Signal Risk
    Major version in deps (v1 → v2) Breaking changes likely
    Library < 2 years old API still evolving
    "experimental" or "beta" in docs May change without notice
    Security-related code Best practices evolve
    AI training data gap Libs released after training cutoff

    Failure Handling

    Issue Response
    No results Broaden query, try alternate terms
    Conflicting info Official docs > GitHub > tutorials
    Only outdated info Mark ❓, proceed with caution, add TODO
    Can't verify Flag for human review

    Query Anti-Patterns

    Bad Query Problem Better Query
    "how to use {library}" Too vague "{library} {specific_feature} 2024"
    "{library} tutorial" May be outdated "{library} {feature} official docs"
    "best {library}" Opinion, not docs "{library} {pattern} documentation"
    "{library}" alone No specificity Add feature + version + year

    Query Strengthening

    If initial query returns poor results:

    1. Add version: "React 19 useOptimistic" vs "React useOptimistic"
    2. Add year: "FastAPI middleware 2024" vs "FastAPI middleware"
    3. Add "official": "Next.js official docs app router"
    4. Be more specific: "Prisma findMany where clause" vs "Prisma queries"
    5. Try alternate terms: "authentication" vs "auth" vs "login"

    Progressive Grounding

    For large implementations:

    1. Start: Ground the core imports/setup
    2. As you go: Ground each new external method before using
    3. Before commit: Review grounding table, verify nothing ❓

    Don't try to ground everything upfront — ground just-in-time as you encounter external deps.


    Integration with Workflow

    Before implementing (via /advance)

    # Check external dependencies
    web_search_exa("{library} {feature} 2024")
    

    During implementation

    # Just-in-time verification
    get_code_context_exa("{specific_method} example")
    

    Before commit

    Review grounding table, ensure all ❓ are resolved or documented.


    Requirements

    Requires Exa API key configured:

    claude mcp add exa -s user \
      -e EXA_API_KEY=your-key \
      -- npx -y @anthropic-labs/exa-mcp-server
    

    Quick Reference

    # Documentation search
    web_search_exa("{library} {feature} {version} 2024 2025")
    
    # Code examples
    get_code_context_exa("{library} {pattern} implementation example")
    
    # Specific page
    crawling("{url}")
    

    Query formula:

    {library} {feature} {version} 2024 2025
    

    Anti-Patterns

    Don't Why Do Instead
    Skip grounding for external APIs Training data may be stale Ground before using
    Use tutorials over docs Tutorials get outdated Prefer official docs
    Ignore version mismatches Breaking changes exist Verify version compatibility
    Ground everything upfront Wastes time Ground just-in-time
    Skip grounding for "familiar" libs APIs change Quick verify is still worth it

    See Also

    • /recall — Past session patterns
    • /explore — Codebase search
    • /advance — Bead workflow (includes grounding step)
    Recommended Servers
    Context7
    Context7
    Astro Docs
    Astro Docs
    Exa Search
    Exa Search
    Repository
    mburdo/knowledge_and_vibes
    Files