Skip to content
Agentmart
Submit a tool

briscoes-nz

Query Briscoes NZ homewares product search, sale/deal snapshots, SKU detail, and store-finder.

Skill by thecolab-ai

IndexedMIT★ 34
Write a review

Chalk Labs

Need help deploying briscoes-nz?

Chalk Labs sets up agents like this inside real teams: connected to your tools, tested on your data, with a human in the loop where it matters.

Book a call

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/thecolab-ai-briscoes-nz

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Query Briscoes NZ homewares product search, sale/deal snapshots, SKU detail, and store-finder. Use for Briscoes product lookup, prices, sale products, or store locations. No cart or account.

Use cases: sales

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Nov 1, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found
Runs as
Python package

Network hosts it talks to 2

  • briscoes.co.nz · found in code
  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/briscoes-nz

What's inside

Skill name
briscoes-nz
Description
Query Briscoes NZ homewares product search, sale/deal snapshots, SKU detail, and store-finder. Use for Briscoes product lookup, prices, sale products, or store locations. No cart or account.
License
MIT
Compatibility
Requires Python 3.10+ and network access for live data
Metadata
thecolab.auth: none · thecolab.pack: nz-commercial-web · thecolab.risk: low · thecolab.health: healthy · thecolab.writes: false · thecolab.browser: false · thecolab.category: retail · thecolab.cache_ttl: 24h · thecolab.data_class: public · thecolab.maintainer: @adam91holt · thecolab.skill_type: html-readonly · thecolab.source_url: https://www.briscoes.co.nz · thecolab.access_mode: html-readonly · thecolab.source_type: commercial · thecolab.source_owner: Briscoe Group · thecolab.last_verified: 2026-07-19 · thecolab.schema_version: 1 · thecolab.allowed_domains: aucs34.ksearchnet.com,www.briscoes.co.nz
Instructions
71 lines in SKILL.md · view on GitHub

Before installing

  • Ships executable scripts

Files (7)

  • SKILL.md
  • api-notes.md · references/
  • source-notes.md · references/
  • cli.py · scripts/
  • smoke_test.py · scripts/
  • test_contract.py · scripts/
  • contract.json · tests/fixtures/

SKILL.md (first lines)

# Briscoes NZ

## Goal

Query live Briscoes NZ product and store data through a small deterministic CLI with human-readable and JSON output, without browser automation or account login.

## Use this when

- A user asks for Briscoes NZ product prices or sale/deal products
- A user wants to search Briscoes products by keyword
- A user has a Briscoes SKU and wants product details
- A user wants Briscoes store locations or contact details
- A workflow needs lightweight machine-readable Briscoes public product or store data

## Do not use this for

- Non-Briscoes retailers or Briscoes Group brands other than Briscoes NZ
- Authenticated account, rewards, personalised, cart, checkout, order, gift registry, or payment actions
- Redistributing scraped Briscoes product data as a dataset
- Historical pricing or price-change claims unless another dataset provides history

## Preferred workflow

1. Run `scripts/cli.py` with the narrowest subcommand that answers the task
2. Use `search` for keyword price/product lookup
3. Use `specials` for sale/deal-flagged products; this is a search-derived view verified against Magento product pricing, not a dedicated Briscoes specials API
4. Use `product` when an exact SKU is known and full Magento price-range detail matters
5. Use `stores --region` to narrow store-finder results by city, region, suburb, or name
6. Use `--json` for agent chaining, comparisons, alerts, or structured reports
7. Mention that prices are live Briscoes online snapshots and the source is unofficial

## CLI

Run with:

```bash
python3 skills/briscoes-nz/scripts/cli.py <command> [flags]
```

### Commands

- `search <query> [--limit N] [--page N] [--json]` - product search with current prices
- `product <sku> [--json]` - fetch exact SKU detail
- `stores [--region text] [--json]` - list public Briscoes store-finder locations
- `specials [query] [--limit N] [--page N] [--json]` - sale/deal-flagged products verified to have a sale price below regular price, optionally filtered by query

Examples:

```bash
python3 skills/briscoes-nz/scripts/cli.py search towel --limit 10
python3 skills/briscoes-nz/scripts/cli.py search "cast iron" --limit 5 --json
python3 skills/briscoes-nz/scripts/cli.py product 1129433 --json
python3 skills/briscoes-nz/scripts/cli.py stores --region auckland --json
python3 skills/briscoes-nz/scripts/cli.py specials bedding --limit 10 --json
```

## Resources

- CLI entrypoint: `scripts/cli.py`
- Live smoke test: `scripts/smoke_test.py`
- API and stability notes: `references/api-notes.md`

## Notes

- No API key secret, username, password, account cookie, or browser automation is required for supported read-only operations
- Briscoes uses an Adobe Commerce/Magento PWA backed by Klevu for product search/listing
- `search` uses Klevu search data; `specials` uses Klevu discovery plus Magento price verification; `product` and `stores` use Briscoes Magento GraphQL
- Endpoint shapes can change; verify with a small live query before relying on large workflows
- Keep usage narrow and respectful

From thecolab-ai/.skills, MIT.

More from thecolab-ai/.skills

Signals

Stars
34
Forks
7
Open issues
10
Last commit (this folder)
Jul 19, 2026 (3 months ago)

From GitHub (fetched Oct 24, 2026).

Details

License
MIT
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from thecolab-ai

Done for you

Rather not set it up yourself?

Chalk Labs scopes, builds and runs agents for your team: the task audit, the eval harness, the integrations and the weekly ops report. Fixed scope, priced before we start.

See how we build AI agents →Read the case studies

Chalk Labs is a two-founder AI and growth studio. We build AI agents, CRMs and MVPs for Web3 and AI companies, and have shipped 50+ product and token launches.

launches shipped
50+
launches shipped
media placements
500+
media placements
founders on every account
2
founders on every account

Press we've placed: Forbes · CoinDesk · Decrypt · Cointelegraph · The Block

Rahil Jain, Co-founder, Chalk Labs. Ex-Goldman Sachs engineer. You talk to the person who builds it.

Get briscoes-nz running in your business

Tell us what you want to automate. A founder replies within one working day with a plan, not a pitch deck.

Goes to the Chalk Labs founders, not the newsletter. Privacy

Need help deploying briscoes-nz?

CallGet help
Cite this page

briscoes-nz skill. Agent Mart. https://agentmart.dev/skills/thecolab-ai-briscoes-nz (last updated 2026-10-24)