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:
python1web_search_exa("{library} {feature} {version} 2024 2025")
For code examples:
python1get_code_context_exa("{library} {pattern} implementation example")
For specific page:
python1crawling("{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:
markdown1## Grounding Status 2| Pattern | Query | Source | Status | 3|---------|-------|--------|--------| 4| `@model_validator` | "Pydantic v2 2024" | docs.pydantic.dev | ✅ Verified | 5| `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
python1get_code_context_exa("{library} {pattern} implementation example") 2get_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:
- Add version:
"React 19 useOptimistic"vs"React useOptimistic" - Add year:
"FastAPI middleware 2024"vs"FastAPI middleware" - Add "official":
"Next.js official docs app router" - Be more specific:
"Prisma findMany where clause"vs"Prisma queries" - Try alternate terms:
"authentication"vs"auth"vs"login"
Progressive Grounding
For large implementations:
- Start: Ground the core imports/setup
- As you go: Ground each new external method before using
- 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)
python1# Check external dependencies 2web_search_exa("{library} {feature} 2024")
During implementation
python1# Just-in-time verification 2get_code_context_exa("{specific_method} example")
Before commit
Review grounding table, ensure all ❓ are resolved or documented.
Requirements
Requires Exa API key configured:
bash1claude mcp add exa -s user \ 2 -e EXA_API_KEY=your-key \ 3 -- npx -y @anthropic-labs/exa-mcp-server
Quick Reference
python1# Documentation search 2web_search_exa("{library} {feature} {version} 2024 2025") 3 4# Code examples 5get_code_context_exa("{library} {pattern} implementation example") 6 7# Specific page 8crawling("{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)
