product-tool-stack

product-tool-stack is a skill for Claude Code, Codex from RefoundAI/lenny-skills. It costs 27 tokens per session (856 once invoked), scanned A, original, MIT.

A guide for choosing and organizing the software a product team uses to communicate, analyze results, plan work, and deliver products.

In plain words
What is it for?
It helps review software spending, define core tools, compare options, and identify tasks such as ticket writing or video editing that could be automated.
Why use it?
It helps reduce duplicated tools, disconnected workflows, and unclear choices between established software and newer AI-based tools.

Skill for Claude CodeCodex

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

Good fit It helps review software spending, define core tools, compare options, and identify tasks such as ticket writing or video editing that could be automated.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/refoundai/lenny-skills/product-tool-stack
About the project

Lenny Skills is a collection of product-management and engineering workflows for Claude Code and other AI agents, covering areas such as strategy, research, planning, shipping, growth, and hiring. Each skill gives an agent specialized guidance, frameworks, checklists, or templates for product work, and the catalogue contains many of these skills.

RefoundAI/lenny-skills · 1,311 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 RefoundAI/lenny-skills --skill product-tool-stack
Clone the repo
git clone --depth 1 https://github.com/RefoundAI/lenny-skills

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 product-tool-stack

README.md
[![agentmods](https://agentmods.dev/badge/skills/refoundai/lenny-skills/product-tool-stack/github.svg)](https://agentmods.dev/skills/refoundai/lenny-skills/product-tool-stack)
Your own site
<a href="https://agentmods.dev/skills/refoundai/lenny-skills/product-tool-stack"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/product-tool-stack/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 product-tool-stack

Your own site · 80×15
<a href="https://agentmods.dev/skills/refoundai/lenny-skills/product-tool-stack"><img src="https://agentmods.dev/badge/skills/refoundai/lenny-skills/product-tool-stack.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 27 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 856 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00027 $0.00856
Opus 5 $0.00014 $0.00428
Sonnet 5 $0.00005 $0.00171
Haiku 4.5 $0.00003 $0.00086

Measured 9d ago against content hash 708fc957e7a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

product-tool-stack 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 9d 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.

skills/product-tool-stack/SKILL.md · 61 lines

How it starts

The opening of the file, as written. The whole thing — 61 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product Stack Strategy

Build a high-performance product toolkit by balancing established standards with AI-native speed.

Help the user with product stack strategy using insights from 6 guests and posts across Lenny's Podcast and Newsletter.

How to Help

  1. Audit and Consolidate - Review current software spending and identifying opportunities to move toward all-in-one platforms that reduce workflow friction.
  2. Define the Foundation - Establish the core data and communication layers required for early-stage stability and cross-functional alignment.
  3. Apply Selection Frameworks - Distinguish between 'safe bet' industry standards for stability and 'early-adopter' tools for competitive productivity gains.
  4. Integrate AI-Native Workflows - Identify specific opportunities to automate administrative tasks, ticket drafting, and video editing with agentic tools.

Core Principles

Consolidate for seamless workflows

From "A year free of PostHog ($16,500 value): The all-in-one analytics, experimentation, feature flag, surveys, session replay, error tracking, data warehouse, LLM analytics platform": "Being able to follow an issue from a session recording, to its impact in analytics, to shipping a fix as a feature flag, to testing a variant, to collecting feedback with surveys—that’s the holy grail."

Moving toward all-in-one platforms reduces the technical and operational friction of managing multiple point solutions, enabling better integration between discovery and shipping.

Commit to engineering-backed data

From "Five steps to starting your product-led growth motion, part 2": "Tools such as Amplitude and Mixpanel are commonly used here, but, as the saying goes, “garbage in, garbage out.” Companies need to dedicate engineering resources to instrument tracking properly. Many B2B companies are significantly lacking in product analytics—watching product usage closely is less important when you sell via human touch—but without a strong foundation of product analytics, PLG will never work."

Read the full file on GitHub · 61 lines

Files

What ships with it

2 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.

  1. 9d ago First seen · 61 lines · 27 tokens per session scan A 708fc957e7a9

Subscribe to this mod's changes

product-tool-stack is a skill published in the GitHub repository RefoundAI/lenny-skills (1,311 stars, last pushed 1mo ago), licensed MIT. It adds 27 tokens to every session and 856 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 2026-08-30.