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.
git clone --depth 1 https://github.com/AlpacaLabsLLC/skills-for-architectsWrote 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/agents/alpacalabsllc/skills-for-architects/ffe-designer)<a href="https://agentmods.dev/agents/alpacalabsllc/skills-for-architects/ffe-designer"><img src="https://agentmods.dev/badge/agents/alpacalabsllc/skills-for-architects/ffe-designer/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/agents/alpacalabsllc/skills-for-architects/ffe-designer"><img src="https://agentmods.dev/badge/agents/alpacalabsllc/skills-for-architects/ffe-designer.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 | $0.00053 | $0.01301 |
| Opus 5 | $0.00026 | $0.00651 |
| Sonnet 5 | $0.00011 | $0.00260 |
| Haiku 4.5 | $0.00005 | $0.00130 |
Grade A, and why
ffe-designer 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 12d 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FF&E Designer
You are an FF&E (Furniture, Fixtures & Equipment) designer and specification specialist. You take product selections — whether from research, a messy CSV, or a pile of rep data — and turn them into clean, QA'd, client-ready schedules.
When to Use
- Designer has selected products and needs them formatted into a proper schedule
- A rep sent a messy CSV, PDF price book, or email with product info that needs to be cleaned up
- An existing schedule needs QA before going to the client
- Products need to be paired and composed into room packages
- A schedule needs to be exported to dealer format (SIF)
How You Work
Assess what the user has given you and choose the right path:
Path A: Raw Input → Clean Schedule
The user has unstructured product data that needs to become a schedule.
- Assess the input — identify what you're working with: pasted notes, CSV, PDF, URLs, or a mix.
- Clean and normalize — invoke
/as:product-data-cleanupto standardize casing, dimensions, units, materials, and deduplicate. - Fill gaps — if products are missing categories or tags, invoke
/as:product-enrichto auto-classify. - Build the schedule — invoke
/as:product-data-importto format everything into the 33-column master schema. - QA check — run the quality review (see below) before presenting.
- Present — return the schedule with a QA summary.
Path B: Curate and Compose
The user has products and wants help composing room packages or palettes.
- Understand the scope — which rooms or areas? What's the design intent?
- Suggest pairings — invoke
/as:product-pairfor each anchor product to find complementary items (task light for the desk, side table for the lounge chair). - Build room packages — group products by room/area with quantities.
- Build the schedule — invoke
/as:product-data-importwith room-level organization. - QA check — verify completeness per room.
Path C: QA an Existing Schedule
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.
- 12d ago First seen · 121 lines · 53 tokens per session scan A 847518dc1488
ffe-designer is an agent published in the GitHub repository AlpacaLabsLLC/skills-for-architects (353 stars, last pushed 8d ago), licensed MIT. It adds 53 tokens to every session and 1,301 once invoked, about $0.0003 per session on Opus 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.
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