ClawHub

Catalog SKU Matcher India

v1.0.0

Match and normalize product listings across Indian ecommerce catalogs with variant-aware rules, confidence scoring, false-match prevention, and review queues...

⭐ 0· 150·0 current·0 all-time
byASP@anugotta

Install

OpenClaw Prompt Flow

Install with OpenClaw

Best for remote or guided setup. Copy the exact prompt, then paste it into OpenClaw for anugotta/catalog-sku-matcher-india.

Previewing Install & Setup.
Prompt PreviewInstall & Setup
Install the skill "Catalog SKU Matcher India" (anugotta/catalog-sku-matcher-india) from ClawHub.
Skill page: https://clawhub.ai/anugotta/catalog-sku-matcher-india
Keep the work scoped to this skill only.
After install, inspect the skill metadata and help me finish setup.
Use only the metadata you can verify from ClawHub; do not invent missing requirements.
Ask before making any broader environment changes.

Command Line

CLI Commands

Use the direct CLI path if you want to install manually and keep every step visible.

OpenClaw CLI

Bare skill slug

openclaw skills install catalog-sku-matcher-india

ClawHub CLI

Package manager switcher

npx clawhub@latest install catalog-sku-matcher-india
Security Scan
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high confidence
✓
Purpose & Capability
Name, description, and provided files (matching rules, scoring, examples, setup, validation) all align: the skill is focused on catalog SKU matching and normalization and does not request unrelated capabilities or resources.
✓
Instruction Scope
SKILL.md and the supplemental docs contain only matching strategies, rulebooks, scoring, setup and validation checklists. There are no instructions to read system files, access environment variables, call external endpoints, or transmit data outside the matching workflow.
✓
Install Mechanism
No install spec and no code files — this is instruction-only, so nothing is downloaded or executed on install and nothing is written to disk by the skill itself.
✓
Credentials
No required environment variables, credentials, or config paths are declared. The requested resources are minimal and proportional to an instruction-only matching guide.
✓
Persistence & Privilege
Flags show always:false and default agent invocation behavior. The skill does not request persistent presence or modification of other skills or system-wide settings.
Assessment
This skill is a set of guidelines and rule files (no code or installs), so the immediate risk is low. Before using in production: (1) implement the rules in your own audited code rather than blindly executing external code, (2) build and run labeled validation sets as the setup and validation checklists recommend, (3) keep conservative auto-match thresholds and human review for ambiguous cases, (4) ensure any real data you feed into an implementation complies with privacy and marketplace TOS, and (5) if you add connectors that fetch catalogs, review those connectors for credential use and external endpoints (those are the places that can introduce risk).

Like a lobster shell, security has layers — review code before you run it.

Runtime requirements

🧩 Clawdis
latestvk97dcrvnc3kp5y51cczt5x410183650g
150downloads
0stars
1versions
Updated 1mo ago
v1.0.0
MIT-0
ASP@anugotta
latest
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Catalog SKU Matcher India

Purpose

Build reliable cross-store product matching for Indian catalogs so price comparison is accurate.

Disclaimer

This skill provides matching and normalization guidance only. It does not guarantee perfect match accuracy for all catalogs or seller data quality.

Use at your own risk. The skill author/publisher/developer is not liable for direct or indirect loss, incorrect match decisions, trading losses, or other damages arising from use or misuse of this guidance.

Matching strategy

Use a layered approach:

  1. Hard identifiers

    • model number / GTIN / MPN / ISBN where available

  2. Variant normalization

    • brand
    • model family
    • storage/RAM
    • color
    • size/pack quantity
    • condition (new/refurbished/used)

  3. Soft similarity

    • token similarity on cleaned title
    • key-attribute overlap
    • seller metadata sanity checks

  4. Confidence score

    • high: auto-match
    • medium: human review queue
    • low: reject

False-match guardrails

  • Never match different storage/RAM variants as same SKU.
  • Never match bundles/accessories to standalone products.
  • Never ignore refurbished/used condition differences.
  • Require manual review when two or more variant fields are missing.

Output format

When matching listings, return:

  1. canonical SKU candidate
  2. matched listings with confidence level
  3. rejected candidates with reason codes
  4. manual review queue entries

Setup

Read setup.md and define normalization dictionaries first.

Validation

Run validation-checklist.md on labeled test sets before production.

References

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