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 AnastasiyaW/codex-claude-code-config --skill product-meaning-extractorgit clone --depth 1 https://github.com/AnastasiyaW/codex-claude-code-configWrote 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/anastasiyaw/codex-claude-code-config/product-meaning-extractor)<a href="https://agentmods.dev/skills/anastasiyaw/codex-claude-code-config/product-meaning-extractor"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/product-meaning-extractor/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/anastasiyaw/codex-claude-code-config/product-meaning-extractor"><img src="https://agentmods.dev/badge/skills/anastasiyaw/codex-claude-code-config/product-meaning-extractor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00155 | $0.02437 |
| Opus 5 | $0.00077 | $0.01218 |
| Sonnet 5 | $0.00031 | $0.00487 |
| Haiku 4.5 | $0.00015 | $0.00244 |
Grade A, and why
product-meaning-extractor 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 3d 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 — 214 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Product Meaning Extractor
Extract the REAL value from a product before writing a single line of video/presentation code. Without this step, content is a flat list of features. With it, content tells a story.
Why This Exists
A feature list alone may not explain why the product matters to this audience. Product analysis connects capabilities to a relevant, supportable customer outcome; it does not guarantee engagement.
This skill forces you to find what actually matters: the enemy, the transformation, the mechanism, and the emotional hook. Everything else flows from these.
Process
Step 1: Gather Raw Material
From the product URL:
- Visit the site, extract ALL text (hero, features, pricing, about, FAQ)
- Screenshot key visuals (hero, before/after, product shots)
- Extract brand colors from CSS (
--primary,--accent, metatheme-color) - Note the tone: formal/casual, technical/simple, premium/accessible
From reviews/testimonials (if available):
- Find testimonials on the site itself
- Check App Store / Product Hunt / G2 / Trustpilot / Reddit mentions
- Extract relevant VERBATIM customer phrases with their source, author/context, and date. Do not turn a paraphrase or invented phrase into a customer quotation.
Evidence travels with the brief: For each factual number, capability, comparison,
customer name, or testimonial, retain the source URL/file and relevant scope/date.
Separate verified observations, attributed vendor claims, and hypotheses. Examples
below illustrate a structure, not facts about the current product. If evidence is
missing, use [needs data], omit the claim, or write a clearly labelled hypothesis;
continue the useful brief without inventing proof to fill a field.
Step 2: The "So What?" Test
For EVERY feature on the site, ask "So what?" until you reach the real value. Most features need 3-4 "so what?" iterations:
Feature: "Outputs .PSD with layers"
So what? → "You can edit individual elements"
So what? → "You don't redo the whole job if one thing is wrong"
So what? → "It saves hours of re-work and frustration"
REAL VALUE: "Never redo work from scratch again"
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.
- 3d ago Changed · +17 lines f931f4e0af66
- 10d ago First seen · 197 lines · 155 tokens per session scan A 0ee6c7e52148
product-meaning-extractor is a skill published in the GitHub repository AnastasiyaW/codex-claude-code-config (149 stars, last pushed yesterday), licensed MIT. It adds 155 tokens to every session and 2,437 once invoked, about $0.0008 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.
Other skills, from other repositories
ai-content-filter
Professional Ai Content Filter Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
ai-product-manager
Professional Ai Product Manager Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
embedding-architect
Professional Embedding Architect skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
hallucination-detector
Professional Hallucination Detector Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
model-card-writer
Professional Model Card Writer Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.
responsible-ai
Professional Responsible Ai Expert skill. Integrate LLM API workflows, safe system prompt guidelines, and agentic workflows.