What is product-analysis?

An analysis workflow for Noibu data, which records online-store sessions and page activity. It examines how products and product groups perform.

Use it to investigate product sales, product-group performance, shopper drop-off, and differences between high- and low-performing products.

It helps identify where shoppers lose interest, which products attract views without sales, and why products may be converting poorly.

product-analysis — Skill for Claude Code by Noibu/ai-plugin

Install

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.

Any agent

npx skills add Noibu/ai-plugin --skill product-analysis

Clone the repo

git clone --depth 1 https://github.com/Noibu/ai-plugin

Made for: Claude Code.

Or install noibu, the plugin that ships this one along with the rest of its 9 skills.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/noibu/ai-plugin/product-analysis/github.svg)](https://agentmods.dev/skills/noibu/ai-plugin/product-analysis)

Your own site

<a href="https://agentmods.dev/skills/noibu/ai-plugin/product-analysis"><img src="https://agentmods.dev/badge/skills/noibu/ai-plugin/product-analysis/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.

Your own site · 80×15

<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="Reviewed on agentmods" width="80" height="20"></a>

Per session 64 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 1,500 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

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	$0.00064	$0.01500
Opus 5.5	$0.00026	$0.00600
Sonnet 5.5	$0.00013	$0.00300
Haiku 4.5	$0.00006	$0.00150

Measured 1mo ago against content hash 7af3b25df5ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 1mo 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.

src/skills/product-analysis/SKILL.md · 101 lines

How it starts

The opening of the file, as written. The whole thing — 101 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.

Call metadata: on every noibu_* call this skill drives, pass skill: "product-analysis" and a short skillStep (see the querying-noibu-data skill).

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 AskUserQuestion populated from their domains — don't ask about anything else. If exactly one domain, skip the question.
Use the querying-noibu-data reference 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_tasks now — 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.

Read the full file on GitHub · 101 lines

Files

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.

Changes

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.

1mo ago Changed · +2 lines 7af3b25df5ee
2mo ago First seen · 99 lines · 64 tokens per session scan A 6540109fe1f2

Subscribe to this mod's changes

product-analysis is a skill published in the GitHub repository Noibu/ai-plugin (5 stars, last pushed 13d ago), licensed MIT. It adds 64 tokens to every session and 1,500 once invoked, about $0.0003 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.

Analytics and metrics E-commerce

product-analysis next to 6 skills from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
product-analysisNoibu/ai-plugin	Skill	5	13d ago	MIT	A	64	Claude Code
amazon-reviews-api-skillbrowser-act/skills	Skill	6.3k	7d ago	MIT	A	124	Claude Code, Codex
amazon-competitor-analyzerbrowser-act/skills	Skill	6.3k	7d ago	MIT	A	48	Claude Code, Codex
asc-subscription-localizationrorkai/app-store-connect-cli-skills	Skill	1.1k	4d ago	MIT	A	60	Claude Code
external-purchasesrshankras/claude-code-apple-skills	Skill	881	2d ago	MIT	A	98	Claude Code
food-orderBitterbot-AI/bitterbot-desktop	Skill	2.5k	3d ago	MIT	A	53	Claude Code, Codex
logistics-opsericrisco/rsc-harness	Skill	579	yesterday	MIT	A	127	Claude Code, Codex