Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Alfredvc/rema1000-cli --skill rema-discoverygit clone --depth 1 https://github.com/Alfredvc/rema1000-cliWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/alfredvc/rema1000-cli/rema-discovery)<a href="https://agentmods.dev/skills/alfredvc/rema1000-cli/rema-discovery"><img src="https://agentmods.dev/badge/skills/alfredvc/rema1000-cli/rema-discovery/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/alfredvc/rema1000-cli/rema-discovery"><img src="https://agentmods.dev/badge/skills/alfredvc/rema1000-cli/rema-discovery.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00044 | $0.00861 |
| Opus 5.5 | $0.00018 | $0.00344 |
| Sonnet 5.5 | $0.00009 | $0.00172 |
| Haiku 4.5 | $0.00004 | $0.00086 |
Grade A, and why
rema-discovery scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
rema-discovery
Workflow for discovering offers, campaigns, stores, and account information via the rema CLI.
Check Bonus Balance and Profile
Quick check (bonus balance + home store only):
rema customer minimal --json
Full profile:
rema customer get --json
Change home store:
rema customer update --home-store <workplace-id>
Browse Current Offers
rema offers list --json
Returns available offers, bonus missions, and non-activated price cuts. Use --fields to filter — the response can be large.
View Weekly Sales Campaigns (Superpriser)
Full campaign with product details:
rema campaigns list --type SP --json
Campaign metadata only (no product details):
rema campaigns list --type SP --no-offers --json
Campaign without feed data:
rema campaigns list --type SP --no-feed --json
Campaign type SP is "Superpriser" — the weekly flyer with discounted products.
Find Stores
Search by name, zipcode, or store number:
rema stores search "Grunerlokka" --json
rema stores search 7033 --json
Get store details by workplace ID:
rema stores get 1011141087892 --json
Get weekly opening hours by store number:
rema stores hours 3198 --json
Note the two different ID types:
workplace-id(long numeric, e.g.,1011141087892) — used withstores getstore-number(short numeric, e.g.,3198) — used withstores hours
Both are returned by stores search.
View Transaction History
List recent transactions (store, date, totals, payments):
rema transactions list --json
Returns headers including transactions[].id, storeName, purchaseDate, amount, bonusPoints, and transactionPayments[]. This is enough for most receipt-metadata queries.
Fetch line items (products purchased) for one transaction:
rema transactions get <transaction-id> --json
The get response contains:
rows[]— each purchased line withproductDescription,unitPrice,amount,pieces,volume/unit(EAorKg),deposit,discount, and bonus earned.prodtxt3is the GTIN when known.transactionPayments[]— payment breakdown (duplicated fromlist).bonusPointsTotal/bonusPointsTotalDecimal— bonus earned on this transaction.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 115 lines · 44 tokens per session scan A 05b7f2da1464
rema-discovery is a skill published in the GitHub repository Alfredvc/rema1000-cli (13 stars, last pushed 6mo ago), licensed MIT. It adds 44 tokens to every session and 861 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
rema-discovery compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| rema-discoveryAlfredvc/rema1000-cli | Skill | 13 | 6mo ago | MIT | A | 44 | Claude Code, Codex |
| amazon-reviews-api-skillbrowser-act/skills | Skill | 6.3k | 3d ago | MIT | A | 124 | Claude Code, Codex |
| amazon-competitor-analyzerbrowser-act/skills | Skill | 6.3k | 3d ago | MIT | A | 48 | Claude Code, Codex |
| asc-subscription-localizationrorkai/app-store-connect-cli-skills | Skill | 1.1k | today | MIT | A | 60 | Claude Code |
| external-purchasesrshankras/claude-code-apple-skills | Skill | 867 | today | MIT | A | 76 | Claude Code |
| food-orderBitterbot-AI/bitterbot-desktop | Skill | 2.5k | today | MIT | A | 53 | Claude Code, Codex |
| Product Photoshoot Workflowjau123/MeiGen-AI-Design-MCP | Skill | 1.8k | yesterday | MIT | A | 111 | Claude Code |