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Install in OpenClaw
/install india-location-normalizer
Description
Normalize Indian real-estate location text into canonical city and locality fields (Mumbai and Pune v1) with confidence and unresolved flags. Use when leads...
README (SKILL.md)
India Location Normalizer
Resolve messy India locality aliases into canonical location fields without side effects.
Quick Triggers
- Normalize Mumbai/Pune location aliases from extracted leads.
- Map PCMC and Hinjewadi variants to canonical localities.
- Resolve Mumbai shorthand like
Scruz,Khar,Andheri W,Turner Road,Carter Road. - Standardize locality names before scoring or storage.
Recommended Chain
message-parser -> lead-extractor -> india-location-normalizer -> sentiment-priority-scorer
Target KPI for production tuning: improve canonical Mumbai/Pune locality resolution versus extractor-only baseline.
Execute Workflow
- Accept lead-location payload from Supervisor.
- Validate input against
references/location-normalizer-input.schema.json. - Use
references/india-location-aliases-v1.jsonas the authoritative lookup map. - Match in this order:
- exact alias match (case-insensitive)
- token-normalized alias match (trim punctuation, collapse spaces)
- conservative fuzzy match only when clearly unambiguous
- Return one normalized location record per input lead with:
citylocality_canonicalmicro_marketmatched_aliasconfidenceunresolved_flag
- Validate output against
references/location-normalizer-output.schema.json.
Enforce Boundaries
- Never parse raw chat exports.
- Never extract non-location entities.
- Never write to Google Sheets, databases, or files.
- Never send messages or trigger external channels.
- Never auto-resolve low-confidence ambiguous aliases.
Handle Ambiguity
- If multiple localities match equally, set
unresolved_flag: true. - If no confident match exists, preserve input in
matched_aliasand mark unresolved. - Prefer false-negative over false-positive for city/locality assignment.
Usage Guidance
This skill is internally consistent and low-risk: it only uses bundled lookup and schema files to normalize Mumbai/Pune location aliases and asks for no credentials or installs. Before enabling in production, verify (1) the full alias JSON included in the bundle is the expected, up-to-date authoritative list (the excerpt in the listing was truncated), (2) your Supervisor/enforcer actually prevents outbound actions (the SKILL.md says 'never write' or 'never send', but enforcement depends on your runtime policies), and (3) run representative test leads to confirm the conservative fuzzy-match behavior and confidence scoring meet your tolerance for false negatives. If you need normalization for other cities, expect the skill to require additional, explicit alias data.
Capability Analysis
Type: OpenClaw Skill
Name: india-location-normalizer
Version: 1.0.1
The OpenClaw AgentSkills bundle is classified as benign. The `SKILL.md` file clearly defines the skill's purpose as normalizing Indian real-estate location data and, critically, includes an 'Enforce Boundaries' section that explicitly forbids high-risk behaviors such as writing to files or databases, sending messages, or triggering external channels. All other files are either metadata, configuration, or static JSON data/schemas, with no executable code or instructions that suggest malicious intent or introduce vulnerabilities. The skill is designed to be a pure function, processing input against local reference data without side effects.
Capability Assessment
Purpose & Capability
The name/description (India locality normalization for Mumbai and Pune) match the included artifacts: a city/locality alias JSON and input/output JSON schemas. There are no unrelated env vars, binaries, or install steps requested.
Instruction Scope
SKILL.md gives a narrow, well-defined runtime flow: accept a lead payload, validate input schema, consult the included aliases JSON, apply exact/normalized/fuzzy matching rules, produce a single normalized record validated against the included output schema, and avoid side effects. The instructions do not reference external endpoints, unrelated files, or open-ended data collection.
Install Mechanism
No install spec and no code files are present — the skill is instruction-only and uses only local reference files bundled with the skill. This is the lowest-risk install profile.
Credentials
The skill requests no environment variables, credentials, or config paths. That matches the described functionality (local lookup + validation) and is proportionate.
Persistence & Privilege
always is false and the skill does not request system-wide persistence or modification of other skills. Autonomous invocation is allowed (platform default) but the skill's instructions explicitly forbid external side effects, keeping its privilege footprint minimal.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install india-location-normalizer - After installation, invoke the skill by name or use
/india-location-normalizer - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.1
Expanded Mumbai alias map with Scruz Khar Turner Road and related localities
v1.0.0
- Initial release of india-location-normalizer skill for standardizing Indian real-estate location text.
- Canonicalizes city and locality fields for Mumbai and Pune, including common aliases (e.g., Goregaon, Baner, PCMC).
- Adds confidence scoring and unresolved flags to each normalized result.
- Follows strict input/output schema validation and limits scope to location normalization only.
- Designed for integration after lead extraction and before sentiment scoring in workflow chains.
Metadata
Frequently Asked Questions
What is India Location Normalizer RE-India?
Normalize Indian real-estate location text into canonical city and locality fields (Mumbai and Pune v1) with confidence and unresolved flags. Use when leads... It is an AI Agent Skill for Claude Code / OpenClaw, with 504 downloads so far.
How do I install India Location Normalizer RE-India?
Run "/install india-location-normalizer" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is India Location Normalizer RE-India free?
Yes, India Location Normalizer RE-India is completely free (open-source). You can download, install and use it at no cost.
Which platforms does India Location Normalizer RE-India support?
India Location Normalizer RE-India is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created India Location Normalizer RE-India?
It is built and maintained by Vishal (@vishalgojha); the current version is v1.0.1.
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