india-location-normalizerNormalize Indian real-estate location text into canonical city and locality fields (Mumbai and Pune v1) with confidence and unresolved flags. Use when leads...
Install via ClawdBot CLI:
clawdbot install vishalgojha/india-location-normalizerGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://json-schema.org/draft/2020-12/schemaAudited Apr 17, 2026 · audit v1.0
Generated Mar 1, 2026
Real estate agencies receive leads with informal location mentions like 'Goregaon' or 'Andheri W' from online forms. This skill normalizes these into canonical Mumbai localities, enabling accurate lead routing to the correct sales teams and improving follow-up efficiency.
Customer support platforms handling queries from Indian users often encounter location aliases such as 'PCMC' or 'Hinjewadi' in service requests. By normalizing these to Pune localities, support teams can quickly assign tickets based on geographic zones, reducing resolution times.
Property listing websites aggregate data from multiple sources, leading to inconsistent locality names like 'Baner' or 'Wakad'. This skill standardizes entries into canonical forms, ensuring clean, searchable databases and enhancing user experience through accurate location filters.
Market research firms collect survey data with varied location inputs from Indian respondents. Normalizing aliases such as 'Scruz' to 'Santacruz' in Mumbai allows for precise demographic analysis and trend identification across standardized geographic segments.
Logistics companies process delivery addresses containing shorthand like 'Khar' or 'Turner Road' in Mumbai. This skill resolves these to canonical localities, improving route planning accuracy and reducing misdeliveries in dense urban areas.
Offer this skill as part of a SaaS platform for real estate or customer service tools, charging monthly fees based on usage volume. It integrates seamlessly into existing workflows, providing value through improved data accuracy and operational efficiency.
Deploy the skill as a standalone API, allowing developers to call it for location normalization in their applications. Monetize through pay-per-request or subscription models, targeting tech companies in India needing clean location data.
Provide consulting services to integrate this skill into clients' existing AI pipelines, such as lead management or data processing systems. Offer customization for additional cities or features, generating revenue from project-based fees and ongoing support.
💬 Integration Tip
Ensure input data is pre-processed by a lead extractor to isolate location text, and validate against the provided JSON schemas to maintain data integrity.
Scored Apr 19, 2026
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