opendevbrowser-shopping - SKILL.md Agent Skill

name: opendevbrowser-shopping description: Deterministic multi-provider shopping and deal-comparison workflow. version: 2.1.0

Shopping Skill

Use this skill for robust deal hunting across providers with market-baseline validation and savings analysis.

Reliable defaults:

before daemon-backed shopping run workflows, run opendevbrowser status --daemon --output-format json and continue only when data.fingerprintCurrent === true
start with explicit providers for reproducible reruns
prefer --browser-mode managed unless relay-backed session state is required
treat --region as advisory unless workflow output reports meta.selection.region_authoritative=true

Pack Contents

artifacts/deal-hunting-workflows.md
assets/templates/deals-context.json
assets/templates/deals-table.md
assets/templates/market-analysis.json
assets/templates/deal-thresholds.json
scripts/run-shopping.sh
scripts/normalize-offers.sh
scripts/render-deals.sh
scripts/analyze-market.sh
scripts/run-deal-hunt.sh
scripts/validate-skill-assets.sh
Shared robustness matrix: ../opendevbrowser-best-practices/artifacts/browser-agent-known-issues-matrix.md

Fast Start

./skills/opendevbrowser-shopping/scripts/validate-skill-assets.sh
./skills/opendevbrowser-shopping/scripts/run-shopping.sh "wireless earbuds" context best_deal
./skills/opendevbrowser-shopping/scripts/run-deal-hunt.sh "wireless earbuds" "shopping/amazon,shopping/walmart"

Supporting Surfaces

Use browser replay (screencast-start / screencast-stop) when offer churn, price changes, or challenge timing needs temporal evidence.
Use desktop observation only for read-only evidence around sibling desktop surfaces; provider collection stays browser-first.
Use --challenge-automation-mode off|browser|browser_with_helper for bounded browser-scoped computer use on provider challenge branches; it is not desktop automation.

Deal-Hunting Model

Use a two-layer check for each offer:

Provider discount check

Compare listed total to provider anchor price (MSRP/list/original) when available.
Capture absolute savings and percentage savings.

Market baseline check

Compare listed total against cross-provider market average and median.
Flag offers that are truly cheaper than market, not just marked "on sale".

Parallel Multitab Alignment

Apply shared concurrency policy from ../opendevbrowser-best-practices/SKILL.md ("Parallel Operations").
Validate shopping workflows across managed, extension, and cdpConnect when browser-backed provider paths are exercised.
Keep one session per worker for parallel offer collection and avoid session-level target contention.
For browser-backed release proof and mode sweeps, follow the canonical direct-run evidence policy in ../opendevbrowser-best-practices/SKILL.md.

Savings Math

Per offer:

total_price = item_price + shipping
anchor_savings_abs = max(anchor_price - total_price, 0)
anchor_savings_pct = anchor_savings_abs / anchor_price * 100

Per market group (same currency):

market_avg = average(total_price)
market_median = median(total_price)
market_savings_abs = market_avg - offer_total
market_savings_pct = market_savings_abs / market_avg * 100

This captures both:

high-percentage discounts (for example 50% off)
high-absolute savings (for example $500 saved)

Robustness Coverage (Known-Issue Matrix)

Matrix source: ../opendevbrowser-best-practices/artifacts/browser-agent-known-issues-matrix.md

ISSUE-06: rate-limit/backoff handling while collecting offers
ISSUE-09: dedupe and pagination drift controls in offer collection
ISSUE-10: currency normalization and same-currency grouping
ISSUE-11: weak/missing anchor price detection
ISSUE-12: stale price and unsupported claim controls

Canonical Workflow

Run shopping search across selected providers.
Normalize offers into stable records.
Compute market analysis with analyze-market.sh.
Render markdown/json summary for user decision.

opendevbrowser shopping run --query "<query>" --providers shopping/amazon,shopping/walmart --mode json --output-format json
opendevbrowser shopping run --query "wireless ergonomic mouse" --providers shopping/bestbuy,shopping/ebay --budget 150 --browser-mode managed --mode json --output-format json
opendevbrowser shopping run --query "27 inch 4k monitor" --providers shopping/bestbuy,shopping/ebay --budget 350 --sort lowest_price --browser-mode managed --mode json --output-format json

Diagnostics rules:

inspect meta.primaryConstraintSummary before classifying a zero-offer run as a provider failure
inspect meta.offerFilterDiagnostics to see whether zero price, budget, or region-currency filters removed the candidate offers
if meta.alerts includes reasonCode=region_unenforced, do not present the output as a trustworthy regional comparison

Classification Heuristics

Default tags from analysis script:

high_percent when anchor discount percent exceeds threshold.
high_absolute when anchor discount absolute exceeds threshold.
high_value when both are true.
market_beating when offer is materially below market average.

Threshold defaults are in assets/templates/deal-thresholds.json.

Confidence model:

score combines sample size, anchor coverage, and freshness coverage.
warnings call out low-sample, missing-anchor, and stale/missing timestamp risk.

Good Deal Decision Rules

Mark as strong only when at least one is true:

anchor discount is material and market gap is positive
market price is materially below average/median even without anchor

Avoid false positives:

anchor discount exists but market total is not competitive
low total due to unavailable stock or hidden constraints

References

FTC Guides Against Deceptive Pricing (16 CFR 233): https://www.ecfr.gov/current/title-16/chapter-I/subchapter-B/part-233
NIST SP 1181 (unit pricing and value comparison): https://www.nist.gov/publications/unit-pricing-guide
Schema.org Offer (price metadata): https://schema.org/Offer