Location Context

Get comprehensive context about a location including nearby places, area description, and optional weather. Use when you need to understand what's around a l...

Security Scan

The skill's code and instructions match its stated purpose (calling the Camino location API with a CAMINO_API_KEY); there are small documentation mismatches but no signs of unrelated credential access or hidden exfiltration.

Purpose & Capability

Skill name/description match behavior: the script and docs call api.getcamino.ai/context and return location context. The only mismatch is documentation/metadata: the runtime script requires curl and jq but the registry metadata lists no required binaries; otherwise credentials and endpoints align with purpose.

Instruction Scope

SKILL.md and scripts limit actions to: obtaining/using CAMINO_API_KEY, calling Camino API endpoints (trial and /context), and printing JSON. They instruct adding the key to ~/.claude/settings.json (a config path not declared in metadata) and show npx install steps; they do not request unrelated files or other secrets. This is scoped to the stated purpose, but the documentation should declare the config path and required binaries.

Install Mechanism

There is no formal install spec inside the skill bundle (instruction-only), but SKILL.md suggests using npx to pull a GitHub repo or clawhub to install. Fetching code from a GitHub repo via npx is common but carries the usual risks of executing remote code; the included script itself is small and benign.

Credentials

Only CAMINO_API_KEY is required and used. The script uses that key solely to authenticate requests to api.getcamino.ai. No unrelated credentials or broad secrets are requested.

Persistence & Privilege

always is false and the skill is user-invocable; it does not request persistent/privileged system changes. It suggests adding the API key to Claude Code settings (user config) which is a normal mechanism for storing credentials for a skill.

Assessment

This skill appears to do exactly what it says: it sends the provided location JSON and your CAMINO_API_KEY to api.getcamino.ai and returns the response. Before installing or using it: (1) Confirm you're comfortable sending location coordinates to api.getcamino.ai and review their privacy policy; (2) prefer using a trial or limited key when testing; (3) note the script requires curl and jq even though the registry metadata doesn't list them—install those first; (4) be cautious when running npx/clawhub commands that pull code from GitHub—inspect the remote repo if you plan to install many companion skills; (5) adding the key to ~/.claude/settings.json grants the agent access to that key, so only add keys you trust the skill to use.

Installation

Companion Skills: This is part of the Camino AI location intelligence suite. Install all available skills (query, places, relationship, context, route, journey, real-estate, hotel-finder, ev-charger, school-finder, parking-finder, fitness-finder, safety-checker, travel-planner) for comprehensive coverage.

# Install all skills from repo
npx skills add https://github.com/barneyjm/camino-skills

# Or install specific skills
npx skills add https://github.com/barneyjm/camino-skills --skill context

Via clawhub:

npx clawhub@latest install context
# or: pnpm dlx clawhub@latest install context
# or: bunx clawhub@latest install context

Context - Location Analysis

Get comprehensive context about a location including nearby places, area description, and optional weather.

Setup

Instant Trial (no signup required): Get a temporary API key with 25 calls:

curl -s -X POST -H "Content-Type: application/json" \
  -d '{"email": "[e-mail]"}' \
  https://api.getcamino.ai/trial/start

Returns: {"api_key": "camino-xxx...", "calls_remaining": 25, ...}

For 1,000 free calls/month, sign up at https://app.getcamino.ai/skills/activate.

Add your key to Claude Code:

Add to your ~/.claude/settings.json:

{
  "env": {
    "CAMINO_API_KEY": "your-api-key-here"
  }
}

Restart Claude Code.

Usage

Via Shell Script

# Get context about a location
./scripts/context.sh '{
  "location": {"lat": 40.7589, "lon": -73.9851},
  "radius": 500
}'

# With specific context for tailored insights
./scripts/context.sh '{
  "location": {"lat": 40.7589, "lon": -73.9851},
  "radius": 500,
  "context": "lunch options"
}'

# Include weather data
./scripts/context.sh '{
  "location": {"lat": 40.7589, "lon": -73.9851},
  "include_weather": true,
  "weather_forecast": "hourly"
}'

Via curl

curl -X POST -H "X-API-Key: $CAMINO_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"location": {"lat": 40.7589, "lon": -73.9851}, "radius": 500, "context": "lunch options"}' \
  "https://api.getcamino.ai/context"

Parameters

Field	Type	Required	Default	Description
location	object	Yes	-	Coordinate with lat/lon
radius	int	No	500	Search radius in meters
context	string	No	-	Context for tailored insights (e.g., "outdoor dining")
time	string	No	-	Temporal query format
include_weather	bool	No	false	Include weather data
weather_forecast	string	No	"daily"	"daily" or "hourly"

Response Format

{
  "area_description": "Busy commercial district in Midtown Manhattan...",
  "relevant_places": {
    "restaurants": [...],
    "cafes": [...],
    "transit": [...]
  },
  "location": {"lat": 40.7589, "lon": -73.9851},
  "search_radius": 500,
  "total_places_found": 47,
  "context_insights": "For lunch, you have many options including..."
}

Examples

Tourist context

./scripts/context.sh '{
  "location": {"lat": 48.8584, "lon": 2.2945},
  "radius": 1000,
  "context": "tourist visiting Paris"
}'

Business meeting location

./scripts/context.sh '{
  "location": {"lat": 40.7589, "lon": -73.9851},
  "radius": 500,
  "context": "business meeting",
  "include_weather": true
}'

Outdoor activity planning

./scripts/context.sh '{
  "location": {"lat": 37.7749, "lon": -122.4194},
  "context": "outdoor activities",
  "include_weather": true,
  "weather_forecast": "hourly"
}'

Use Cases

• Trip planning: Understand what's around a destination before visiting
• Meeting locations: Find suitable venues for different types of meetings
• Local recommendations: Provide context-aware suggestions based on user needs
• Weather-aware planning: Include weather data for outdoor activity planning