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 agentmods add skills/noibu/ai-plugin/product-analysisnpx skills add Noibu/ai-plugin --skill product-analysisgit clone --depth 1 https://github.com/Noibu/ai-pluginWrote 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/noibu/ai-plugin/product-analysis)<a href="https://agentmods.dev/skills/noibu/ai-plugin/product-analysis"><img src="https://agentmods.dev/badge/skills/noibu/ai-plugin/product-analysis.svg" alt="Measured on agentmods" 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 | $0.00064 | $0.01457 |
| Opus 5 | $0.00032 | $0.00728 |
| Sonnet 5 | $0.00013 | $0.00291 |
| Haiku 4.5 | $0.00006 | $0.00146 |
Grade A, and why
product-analysis 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 5d 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 — 99 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Noibu Product & Collection Performance Analysis
Surfaces which products and collections are winning or losing, and why — built from Noibu session and page data.
How it works
- Quick answer (one focused question) → run 1–2 queries, answer directly, offer to go deeper.
- Full analysis (broad request, bare invocation, or "yes" to the offer) → the workflow below.
Setup — before any query
Work quietly. Resolving the domain, loading reference files, reading field names, and running queries all happen silently — no "let me…" commentary. The triage board widget is the first substantive output.
- Resolve the domain first. Use what the user gave (name or UUID). If nothing, ask via
AskUserQuestionpopulated from their domains — don't ask about anything else. If exactly one domain, skip the question. - Use the
querying-noibu-datareference already loaded in context — do not read it again. It maps role-based names to real tools/columns and documents query constraints. - Call
list_scheduled_tasksnow — check whether any task's prompt references this domain and store the result. This sets the action bar button label later ("Schedule report" vs "Edit scheduled report") without blocking rendering. - Confirm every field name by role before using it. Steps name fields by role, never hard-coded column names.
- Default window: from the context reference; if none, last 30 days.
- If the entire dataset is near-zero (total sessions 0 or a handful), say plainly the domain has no traffic in this window and offer to widen the range or pick another domain.
Quick answer
For focused questions ("which products get the most views?", "how is the Sale collection performing?"):
- Run only the 1–2 queries needed.
- Answer directly — a few sentences and a small table if useful.
- Offer full analysis; if yes, proceed below.
Don't load the triage-board or scheduling references for a quick answer.
Full analysis
A broad request, a bare invocation, or "yes" to the quick-answer offer.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 5d ago First seen · 99 lines · 64 tokens per session scan A 6540109fe1f2
product-analysis is a skill published in the GitHub repository Noibu/ai-plugin (5 stars, last pushed 9d ago), licensed MIT. It adds 64 tokens to every session and 1,457 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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