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 nortonx/ai-tooling-free --skill takeawaysgit clone --depth 1 https://github.com/nortonx/ai-tooling-freeWrote 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/nortonx/ai-tooling-free/takeaways)<a href="https://agentmods.dev/skills/nortonx/ai-tooling-free/takeaways"><img src="https://agentmods.dev/badge/skills/nortonx/ai-tooling-free/takeaways/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/nortonx/ai-tooling-free/takeaways"><img src="https://agentmods.dev/badge/skills/nortonx/ai-tooling-free/takeaways.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00052 | $0.00788 |
| Opus 5.5 | $0.00021 | $0.00315 |
| Sonnet 5.5 | $0.00010 | $0.00158 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
takeaways 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 1mo 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 — 82 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Arguments
<url | text>
- Required. A URL to a video, social post, or article, OR raw text/transcript content.
- Examples:
/takeaways https://www.youtube.com/watch?v=example,/takeaways <pasted transcript>
Copilot CLI note:
$ARGUMENTSdoes not substitute in skills; include the argument inline in your prompt.
Extract Takeaways: $ARGUMENTS
Extract the core conclusions, pros, cons, and answers from long-form content, video transcripts, or social posts. Always resolve clickbait titles up front by delivering a direct, unambiguous verdict.
Step 1: Input Resolution
Check the content provided in $ARGUMENTS:
- Raw text or pasted transcript: proceed directly to Step 2.
- URL (YouTube, Instagram, article, podcast):
- If runtime browsing or fetching tools are available, attempt to retrieve page content or transcript.
- If external tools are unavailable, if scraping is blocked by captchas/auth, or if no captions are extractable, stop and ask the user:
"Could not extract transcript automatically from
<url>. Please paste the transcript, subtitles, or article text to continue."
- Empty or missing argument: stop and prompt:
"Usage:
/takeaways <url | text>. Please provide a URL or paste the content to analyze."
Step 2: Identify Core Premise and Title Question
Identify the central question, debate, or promise in the title or opening framing (for example: "Is framework X worth learning?", "Tool A vs Tool B", "Does technique Y really work?").
Step 3: Group Findings and Key Points
Synthesize the content into clear categories:
- Primary claims and evidence presented
- Concrete pros and cons
- Product, tool, or methodology comparisons
- Benchmark numbers, pricing, or measurable results
Step 4: Output Template
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.
- 1mo ago Changed · +61 lines · +7 tokens per session fe73b6bf17f2
- 1mo ago First seen · 21 lines · 45 tokens per session scan A 41adbb009ce3
takeaways is a skill published in the GitHub repository nortonx/ai-tooling-free (1 stars, last pushed 18d ago), licensed MIT. It adds 52 tokens to every session and 788 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-31.
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