product-teardown

product-teardown is a skill for Claude Code from tushaarmehtaa/tushar-skills. It costs 39 tokens per session (683 once invoked), scanned A, original, MIT.

A method for examining a product or competitor using visible evidence from its pages, screens, copy, pricing, onboarding, and user journey. It turns those observations into lessons that can be applied elsewhere without copying protected design or content.

In plain words
What is it for?
Use it to critique a page, study a marketing site, review onboarding, compare pricing, analyze the full customer journey, or extract reusable product and design principles.
Why use it?
It replaces vague opinions with documented findings tied to specific screens, states, or URLs. It also separates what was observed from sourced facts and interpretation.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the slashskills plugin — 34 skills shipped together

Good fit Use it to critique a page, study a marketing site, review onboarding, compare pricing, analyze the full customer journey, or extract reusable product and design principles.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/tushaarmehtaa/tushar-skills/product-teardown
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 tushaarmehtaa/tushar-skills --skill product-teardown
Clone the repo
git clone --depth 1 https://github.com/tushaarmehtaa/tushar-skills

Made for: Claude Code.

Or install slashskills, the plugin that ships this one along with the rest of its 34 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.

agentmods badge for product-teardown

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

Your own site · 80×15
<a href="https://agentmods.dev/skills/tushaarmehtaa/tushar-skills/product-teardown"><img src="https://agentmods.dev/badge/skills/tushaarmehtaa/tushar-skills/product-teardown.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 39 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 683 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 $0.00039 $0.00683
Opus 5 $0.00019 $0.00342
Sonnet 5 $0.00008 $0.00137
Haiku 4.5 $0.00004 $0.00068

Measured 13d ago against content hash 7699e845066e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

product-teardown 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 13d 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.

product-teardown/SKILL.md · 73 lines

How it starts

The opening of the file, as written. The whole thing — 73 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Product teardown

Analyze a product in context and convert observations into transferable principles. Do not copy protected expression, brand assets, or distinctive implementation.

Choose a mode

  • Page critique: one public page or screenshot.
  • Marketing-site teardown: positioning, proof, pricing path, and conversion.
  • Onboarding/activation teardown: first-use journey and time to value.
  • Pricing/packaging teardown: plans, value metric, comparison, and purchase friction.
  • Full-funnel teardown: acquisition through activation and visible retention loops.
  • Comparison: evaluate multiple products on the same scoped lenses.

Infer the target product, application context, and learning objective from the request. Ask one blocking question only when the product or intended application is genuinely missing.

Evidence protocol

  1. Record product, URLs or artifact names, capture date, viewport/device, authentication state, locale, and pages/states covered.
  2. Distinguish visible evidence, user-provided behavior, sourced fact, and inference.
  3. Cite URLs and describe the exact screen, state, or copy supporting each important finding. State access gaps rather than extrapolating.
  4. Do not infer conversion, retention, revenue, strategy, or user sentiment from UI alone.

Lenses

Select only relevant lenses and explain material omissions:

  • five-second comprehension and category;
  • audience, alternative, differentiation, and message hierarchy;
  • copy, information scent, calls to action, and objection handling;
  • proof, trust, risk, privacy, and credibility;
  • pricing, packaging, value metric, and purchase friction;
  • navigation, primary task, empty/loading/error/recovery states;
  • onboarding, activation, time to value, and progressive disclosure;
  • accessibility, responsive behavior, performance cues, and inclusive design;
  • visual hierarchy, typography, motion, and craft;
  • visible sharing, collaboration, habit, or retention loops.

Workflow

Read the full file on GitHub · 73 lines

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. 13d ago First seen · 73 lines · 39 tokens per session scan A 7699e845066e

Subscribe to this mod's changes

product-teardown is a skill published in the GitHub repository tushaarmehtaa/tushar-skills (11 stars, last pushed 3d ago), licensed MIT. It adds 39 tokens to every session and 683 once invoked, about $0.0002 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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