mtaNYC MTA transit — real-time subway arrivals, bus predictions, service alerts, and route info for the New York City subway and bus system. Use when the user a...
Install via ClawdBot CLI:
clawdbot install brianleach/mtaGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
eval(Calls external URL not in known-safe list
https://github.com/brianleach/mta-skillAI Analysis
The skill interacts with official, public MTA APIs for its stated transit information purpose. The only external call to an unauthorized domain is the GitHub homepage link, which is a common reference for open-source projects. The 'eval()' warning is concerning but appears in a limited, documented context for parsing protobuf data.
Audited Apr 16, 2026 · audit v1.0
Generated Mar 22, 2026
Commuters in New York City can use this skill to check real-time subway arrivals at specific stations like Times Square or Grand Central, helping them plan trips efficiently. It supports queries for lines such as 1/2/3 or A/C/E, providing updates every 30 seconds without requiring an API key. This is ideal for daily travelers needing to minimize wait times and avoid delays.
Residents relying on NYC bus routes like M1 or B52 can access real-time bus predictions and vehicle monitoring by setting up a free MTA_BUS_API_KEY. The skill allows users to find nearby bus stops, track arrivals at specific stops, and monitor entire routes, supporting efficient public transit navigation in the city. This is useful for those in areas with limited subway access or for planning multi-modal trips.
Travelers and commuters can use this skill to check MTA service alerts for subway and bus systems, including delays, planned work, and weekend changes. It pulls data from real-time feeds without an API key, helping users stay informed about disruptions and adjust their routes accordingly. This scenario is critical for minimizing travel disruptions in a dynamic urban environment.
Visitors to New York City can utilize this skill to discover subway and bus routes, find nearby stops based on coordinates, and get detailed route info like terminals and colors. By running commands to search for stops or refresh GTFS static data, users can navigate the complex MTA system more easily, enhancing their sightseeing and travel experiences in the city.
Users can inquire about MTA fares, MetroCard, and OMNY payment systems through this skill, leveraging its integration with MTA data sources. While not explicitly detailed in commands, the skill's context allows for answering such questions based on static GTFS feeds and real-time alerts, helping commuters understand costs and payment options for NYC public transit.
Offer basic subway and alert data for free to attract developers, while charging for enhanced bus API access or higher rate limits. This model leverages the skill's open-source nature and MTA's free feeds, generating revenue through premium subscriptions for advanced features like real-time bus tracking and custom integrations. It targets app developers and transit startups.
License the skill as a white-label solution for businesses such as hotels, travel agencies, or corporate campuses to integrate NYC transit data into their apps or websites. Provide customization options and support services, monetizing through one-time setup fees and ongoing maintenance contracts. This model capitalizes on the skill's comprehensive data coverage and ease of use.
Sell aggregated and analyzed transit data from the skill's feeds to urban planners, government agencies, or researchers. Offer insights on ridership patterns, delay trends, and service efficiency, using the real-time and static GTFS data. Revenue comes from data subscription packages and custom report generation, targeting entities focused on urban mobility improvements.
💬 Integration Tip
Ensure the MTA_BUS_API_KEY is set up for bus functionalities, and run the refresh-gtfs command initially to download necessary static data for optimal performance.
Scored Jun 17, 2026
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