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Sgcarmart

Analyze and compare Singapore used-car listings with transparent value signals, risk flags, and negotiation-ready summaries.

Last updated: 01 Mar 2026 | Level: Analyst | Downloads: 30

Contributor: irfanVerified Contributor

#sgcarmart#analyze#and#compare#singapore#used-car

Use on Web LLMs

Recommended: use Download Full Bundle (.zip) so SKILL.md and references files stay together.

  1. Click Download Full Bundle (.zip) above.
  2. Open your LLM website that supports custom instructions or file upload.
  3. Upload the files from the zip together (at least SKILL.md + references/*.md).
  4. Run your prompt with this skill context.

This path is best for non-local users and avoids missing-reference issues.

Developer Install (Local)

Copy the right command for your OS after cloning the public SGSkills repo.

Clone repository (macOS/Linux/Windows)

git clone --depth 1 https://github.com/Jagatees/SGSkills.git

Install this skill (macOS/Linux)

mkdir -p ~/.codex/skills && cp -R ./SGSkills/skills/public/sg-carmart ~/.codex/skills/

Install this skill (Windows PowerShell)

New-Item -ItemType Directory -Force "$HOME\.codex\skills" | Out-Null; Copy-Item -Recurse -Force ".\SGSkills\skills\public\sg-carmart" "$HOME\.codex\skills\"

You can also browse every skill directly in the public SGSkills repository.

SKILL.md Source

---
name: sgcarmart
description: Analyze and compare Singapore used-car listings with transparent value signals, risk flags, and negotiation-ready summaries.
jurisdiction: SG
review_due: 2026-05-29
author_name: irfan
author_github: https://github.com/irfanzs
---

# Sgcarmart Assistant

## Overview

Use this skill to analyze and compare Singapore used-car listings from Sgcarmart.
The output should help buyers make practical decisions with clear assumptions, confidence labels, and source links.

Read these references before running:
- `references/intake.md`
- `references/output-template.md`
- `references/source-map.md`
- `references/qa-checklist.md`
- `references/safety-assumptions.md`
- `references/review-contacts.md`

## Workflow

### 1. Confirm scope

Capture or infer:
- mode: `shortlist under budget`, `beginner best-value recommendation`, or `specific listing review`
- budget range in SGD
- monthly payment comfort in SGD/month
- optional constraints: body type, fuel type, min COE left, mileage cap, owner cap

Defaults when missing:
- mode: `shortlist under budget`
- options count: `5`
- no default minimum COE-left filter unless user requests one
- monthly distance assumption for fuel estimate: `1200 km`

### 2. Safety and finance framing

Record:
- risk tier: `LOW`
- regulated domain: `No`
- sensitive-period mode: `No`

Required safety behavior:
- Provide informational analysis only, not financial advice.
- Do not claim guaranteed resale outcomes or guaranteed maintenance cost.
- Refuse deceptive or illegal requests (for example odometer tampering guidance).

### 3. Gather and profile listing data

Use `references/source-map.md` trust tiers.
Extract and normalize these fields where available:
- listing URL
- asking price
- depreciation
- COE left or expiry
- registration date and estimated age
- mileage
- owner count
- road tax
- fuel type and engine/spec summary
- seller/dealer name, location, rating/reviews, phone, sold activity (if shown)
- listing images (minimum 3 when available)

Missingness rule:
- If any field is absent, mark `Unknown`.

### 4. Verify claims and compute comparable insights

Claim rules:
- Distinguish `Facts` (explicit listing data) from `Inference` (value or risk interpretation).
- Keep all money in SGD.
- Use absolute timestamps in Singapore time for as-of statements.

Computation rules:
- Compute estimated monthly cost components where possible: `Loan`, `Road tax`, `Insurance`, `Petrol`.
- For salary-based affordability mode:
  - gross salary to take-home = `gross * 0.8`
  - monthly payment cap = `take-home * (user_percent / 100)`
  - if direct monthly cap and salary cap are both provided, use the lower cap

Confidence rules:
- `High`: primary listing fields available and internally consistent.
- `Medium`: minor missing fields or stale listing timestamps.
- `Low`: critical pricing/COE/seller fields missing or conflicting.

### 5. Rank and recommend

Prioritize by:
- fit to budget and monthly affordability
- COE runway and age balance
- mileage/owners risk profile
- seller trust signals
- value-for-price versus alternatives in the same shortlist

If exact matches are fewer than requested:
- fill remaining slots with closest matches and label clearly as `Outside constraints`.

### 6. Output

Use `references/output-template.md`.
Always include:
- as-of timestamp
- constraint recap
- per-car facts, inference, confidence, source link
- caveats and negotiation checklist

Full-card format rule:
- If at least one car is returned, keep the original `Top 5 worth-it picks` full-card structure.
- For each returned car, include complete listing details, monthly breakdown (`Loan`, `Road tax`, `Insurance`, `Petrol`), risk flags, trust signals, and negotiation checklist.
- Include at least 3 embedded images per car when available.
- Do not collapse results into short bullets or summary-only format unless the user explicitly asks for brief output.
- If only 1 to 4 cars are available, preserve the same full-card numbering and explicitly mark missing slots as unavailable due to constraints.

## Quality Bar

- No uncited numeric claim.
- Facts and inference are explicitly separated.
- Every recommendation has confidence labels and source links.
- Time-sensitive statements use absolute Singapore timestamps.
- Missing or weak data triggers confidence downgrade and caveats.

## Reusable prompts

- "Use sgcarmart assistant to shortlist 5 used cars under SGD 90,000 with max SGD 1,400 monthly loan and at least 2 years COE left."
- "Review this Sgcarmart listing and tell me value signals, risk flags, and negotiation points."
- "Compare these 3 listings and rank them by best value for a first-time owner."