A specialized knowledge layer providing contextual intelligence for visiting, living, and working in London.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install london
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install london using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is London Intelligence & Navigation?
The London skill transforms an AI agent into a local expert, offering deep technical and cultural insights into the UK capital. It is designed to assist diverse user personas—from tech workers and entrepreneurs to students and tourists—by providing structured data on everything from the tech ecosystem to neighborhood safety. By utilizing Openclaw Skills, users can access hyper-local knowledge that goes beyond generic search results, offering specific salary benchmarks, rent expectations, and transport nuances.
This skill acts as a comprehensive reference system, organizing London's complexity into actionable modules. Whether you are planning a 7-day itinerary or calculating the total compensation for a senior software engineer role in Shoreditch, this skill provides the context-aware data necessary for informed decision-making.
London Intelligence & Navigation Use Cases
- Relocating to London as a tech professional by analyzing rent in Zone 2 versus Zone 3 and comparing it against senior SWE salary benchmarks.
- Crafting efficient 1, 3, or 7-day tourist itineraries that prioritize local favorites like Borough Market over expensive tourist traps like the London Eye.
- Matching families or young professionals to specific neighborhoods based on lifestyle profiles, such as Greenwich for families or Hackney for nightlife.
- Navigating the London transit system effectively using contactless payment rules and essential local service apps like Citymapper.
How London Intelligence & Navigation Works
- The agent first identifies the user's specific role (tourist, resident, or professional) and their temporal context (planning vs. already on-site).
- It cross-references the query against a modular library of Markdown files covering food, safety, transport, and career specifics.
- The skill applies core heuristic rules regarding safety (phone snatching awareness) and transit (contactless vs. Oyster) to provide practical advice.
- It generates a response that synthesizes current economic data, such as Tube daily caps and average 1BR rent, to ensure technical accuracy.
- The agent utilizes Openclaw Skills logic to recommend specific 'Do vs. Skip' actions for maximum efficiency and cost-savings.
London Intelligence & Navigation Setup
To integrate this skill into your environment, ensure your agent has access to the skill's file structure. No external binaries are required.
# Example of how an agent might initialize the London skill context
# No installation command is needed as this is a knowledge-based skill
# Simply ensure the .md files are indexed in your Openclaw Skills directory
London Intelligence & Navigation Data Schema & Taxonomy
The skill organizes data into functional modules for high-speed retrieval:
| Data Category | Relevant Files | Key Metrics Included |
|---|---|---|
| Visitors | visitor-*.md |
Itineraries, Lodging, Attractions |
| Living | neighborhoods-*.md |
Zone-specific pros/cons, Rent costs |
| Career | tech.md, startup.md |
Salary benchmarks, Industry hubs |
| Practical | transport.md, cost.md |
Tube caps, ULEZ rules, Council tax |
| Safety | safety.md |
Risk zones, common scams |
London Intelligence & Navigation Advanced Features
- Multi-persona context switching allows the agent to pivot from advising a student on budget markets to advising an entrepreneur on the Shoreditch startup scene.
- Real-time economic benchmarking for salary negotiations and housing budget planning based on current Zone 1-3 market rates.
- Automated neighborhood matching engine that filters London's 32 boroughs based on professional profile and budget constraints.
- Built-in 'Tourist Trap' filter that programmatically redirects users to free high-value alternatives like Sky Garden instead of paid attractions.
SKILL.md
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