Opendevbrowser Shopping

Shopping Skill

Use this skill for deterministic shopping runs, conservative deal comparison, and decision-ready review of generated shopping artifacts.

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.

Runtime Artifact Contract

Successful shopping bundles preserve separate user and audit surfaces:

• deals.md: primary deterministic buying brief with a Buying Readiness Gate, Recommendation, Best Candidate Offers, Market Baseline, Warnings and Constraints, Excluded or Constrained Offers, and Evidence Appendix.
• buyingReadiness in JSON output: first-class buying authority gate with status values pass, partial, or fail.
• offers.json: raw structured offer evidence.
• comparison.csv: tabular provider, title, price, shipping, deal score, availability, and URL comparison, with appended currency and total-status audit fields.
• meta.json: workflow diagnostics, selected providers, alerts, failures, and filter diagnostics.
• deals-context.json: agent handoff context with query, report-derived highlights, raw offers, and meta.

compact and context modes summarize the report guidance. json mode returns raw offers, buyingReadiness, and meta.

Decision Model

Use the runtime buying brief as the source of truth for purchase guidance:

1. Read the Buying Readiness Gate in deals.md or buyingReadiness.status in JSON output. Transport success and emitted offers are not enough for purchase guidance.

• pass: evidence supports bounded buying guidance for the current shortlist.
• partial: offers are usable as a constrained shortlist, but evidence gaps limit confidence.
• fail: no confident purchase recommendation is allowed.

2. Review warnings before naming a candidate.

• Freshness warnings include stale, inferred, or missing price timestamps.
• Availability warnings include unknown or out-of-stock offers.
• Relevance warnings include weak query fit or suspicious titles.
• Duplicate warnings mean same-title or same-product offers appear across multiple URLs.
• Advisory region warnings mean requested regional comparison is not authoritative.

3. Check raw artifacts when decisions matter.

• Audit prices and URLs in offers.json and comparison.csv.
• Audit workflow failures, alerts, and filter constraints in meta.json.
• Do not claim seller trust, return policy, warranty, condition, shipping certainty, or price history unless the raw offer attributes and report text explicitly include them.

Market Baseline And Savings

The runtime Market Baseline section is conservative:

• It computes average, median, and lowest total only from a deterministic same-currency sample.
• It reports market baseline unavailable when sample size or currency coverage is insufficient.
• It reports anchor/list discount only when explicit anchor, list, original, or MSRP evidence is present.
• It does not invent savings from a sale label, hidden list price, unrelated currency, or missing price-history source.

The helper script scripts/analyze-market.sh can be used for offline analysis of exported offers, but it is not automatically invoked by opendevbrowser shopping run. Treat script output as supplemental unless it is copied into the final evidence review with its inputs.

Parallel Multitab Alignment

• Apply shared concurrency policy from ../opendevbrowser-best-practices/SKILL.md ("Parallel Operations").
• Validate shopping workflow browser-mode sweeps with auto, extension, and managed when browser-backed provider paths are exercised.
• For lower-level attach parity, separately validate direct connect or CDP attach sessions where shopping uses browser action tools.
• 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.

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 or missing anchor price detection
• ISSUE-12: stale price and unsupported claim controls

Canonical Workflow

1. Run shopping search across selected providers.
2. Open deals.md first and classify readiness as pass, partial, or fail.
3. Inspect warnings for freshness, availability, relevance, duplicate pressure, market baseline, workflow alerts, and advisory region limits.
4. Audit raw evidence in offers.json, comparison.csv, and meta.json before giving buying advice.
5. Use helper scripts only as optional offline analysis over exported raw artifacts.

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 candidate offers
• if meta.alerts includes reasonCode=region_unenforced, do not present the output as a trustworthy regional comparison

Candidate Decision Rules

Use confident wording only when the report gate allows it:

• Do not override a fail gate with a buying recommendation.
• Treat partial as a constrained shortlist, not a final answer.
• Treat out-of-stock, weak-relevance, suspicious-title, stale-freshness, duplicate-pressure, and advisory-region warnings as constraints.
• Prefer candidates with observed fresh price evidence, usable title, strong query fit, available stock, and an available same-currency market baseline.
• State when market baseline, anchor/list discount, seller trust, returns, warranty, condition, or price history are unavailable.

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