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 skills add rshankras/claude-code-apple-skills --skill product-agentgit clone --depth 1 https://github.com/rshankras/claude-code-apple-skillsWrote 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/rshankras/claude-code-apple-skills/product-agent)<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/product-agent"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/product-agent/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.
<a href="https://agentmods.dev/skills/rshankras/claude-code-apple-skills/product-agent"><img src="https://agentmods.dev/badge/skills/rshankras/claude-code-apple-skills/product-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 218 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 222 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 223 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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 | $0.00081 | $0.02145 |
| Opus 5 | $0.00041 | $0.01073 |
| Sonnet 5 | $0.00016 | $0.00429 |
| Haiku 4.5 | $0.00008 | $0.00215 |
Grade A, and why
product-agent 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 7d 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 — 241 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Agent Skill
Product Agent validates iOS/macOS app ideas by analyzing problems, markets, and competition. It provides honest, structured assessments to help you decide whether to build.
When This Skill Activates
Use this Skill when the user wants to:
- Discover or validate product ideas
- Analyze market opportunities
- Check if an app idea is worth building
- Understand competitive landscape
- Assess problem severity
- Get honest feedback on app concepts
How It Works
This skill performs structured product analysis using reasoning and web research. No external tools required — Claude analyzes the idea directly and researches the market via WebSearch/WebFetch.
Quick Start
When the user provides an app idea, perform the Problem Discovery Analysis below and present the results.
If the user hasn't provided enough detail, ask:
- What's the app idea? (required)
- What platform? (iOS, macOS, or both — default: iOS/macOS)
- Who's the target user? (optional but improves analysis)
Problem Discovery Analysis
For each idea, analyze and produce these fields:
1. Problem Statement
One-sentence description of the core problem the app solves.
2. Target Users
Who experiences this problem most acutely? Be specific about demographics, roles, and context.
3. Pain Points
List 4-8 specific, concrete pain points users experience today. Each should be observable and verifiable.
4. Severity Score (1-10)
Rate how painful this problem is:
- 1-3: Weak problem, low urgency — users barely notice
- 4-6: Moderate problem, decent opportunity — users work around it
- 7-8: Strong problem, good opportunity — users actively seek solutions
- 9-10: Critical problem, excellent opportunity — users are desperate (rare)
5. Frequency
How often do target users encounter this problem? Daily problems are stronger than weekly ones.
6. Current Solutions
Research existing alternatives using WebSearch. For each competitor:
- Name and brief description
- Key strengths
- Main limitations
- Pricing model
What ships with it
3 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.
- 7d ago First seen · 241 lines · 81 tokens per session scan A 7ff710225d9b
product-agent is a skill published in the GitHub repository rshankras/claude-code-apple-skills (713 stars, last pushed 1mo ago), licensed MIT. It adds 81 tokens to every session and 2,145 once invoked, about $0.0004 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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