transparent-product-recommendations

transparent-product-recommendations is a skill for Claude Code, Codex from microsoft/aibast-agents-library. It costs 22 tokens per session (80 once invoked), scanned A, original, MIT.

A drafting skill for ranking product options using stated preferences such as style, brand, color, budget, and previous products. It explains why each option matches.

In plain words
What is it for?
Use it to create explainable product shortlists for review, with each recommendation clearly marked as a draft.
Why use it?
It makes recommendations understandable and avoids guessing sensitive traits or taking shopping actions on the customer’s behalf.

Skill for Claude CodeCodex ✓ vendor

Written for no agent in particular: nothing here depends on one.

Good fit Use it to create explainable product shortlists for review, with each recommendation clearly marked as a draft.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/microsoft/aibast-agents-library/product-recommendations
About the project

AIBAST Agents Library is a collection of industry-focused AI agent templates accompanied by a local server that connects agents to GitHub Copilot for language-model inference. It helps developers create and run tool-using agents and isolated project environments, with an optional cloud-backed path for persistent memory. The catalogue entries provide the repository's agents, skills, commands, hooks, and instructions.

microsoft/aibast-agents-library · 7 stars · on GitHub

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 microsoft/aibast-agents-library --skill product-recommendations
Clone the repo
git clone --depth 1 https://github.com/microsoft/aibast-agents-library

Made for: Claude Code, Codex.

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.

agentmods badge for transparent-product-recommendations

README.md
[![agentmods](https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/product-recommendations/github.svg)](https://agentmods.dev/skills/microsoft/aibast-agents-library/product-recommendations)
Your own site
<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/product-recommendations"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/product-recommendations/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.

agentmods 80×15 button for transparent-product-recommendations

Your own site · 80×15
<a href="https://agentmods.dev/skills/microsoft/aibast-agents-library/product-recommendations"><img src="https://agentmods.dev/badge/skills/microsoft/aibast-agents-library/product-recommendations.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 22 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 80 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00022 $0.00080
Opus 5 $0.00011 $0.00040
Sonnet 5 $0.00004 $0.00016
Haiku 4.5 $0.00002 $0.00008

Measured 5d ago against content hash 92c8dcb4cda5, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

transparent-product-recommendations 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.

solutions/personalized-shopping-assistant/manual/skills/product-recommendations/SKILL.md · 10 lines

What it actually says

Transparent product recommendations

Rank options using stated style, brand, color, budget, and prior-product examples. Explain each match and label it a draft. Never infer sensitive traits, reserve stock, apply an offer, create an order, or complete a purchase.

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.

  1. 5d ago First seen · 10 lines · 22 tokens per session scan A 92c8dcb4cda5

Subscribe to this mod's changes

transparent-product-recommendations is a skill published in the GitHub repository microsoft/aibast-agents-library (7 stars, last pushed today), licensed MIT. It adds 22 tokens to every session and 80 once invoked, about $0.0001 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 2026-09-03.

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