Lately, I’ve been working on something I’ll be releasing soon—a contribution toFabric, a killer Golang project by Daniel Meissler. If you’re the kind of person who thinks the terminal is superior, this will put a smile on your face.
No more wasting system resources on bloated chat UIs. Instead, Fabric gives you alibrary of powerful prompt patternsaccessible through the–patternflag.
So, what’s a pattern?
A pattern is basically a highly detailed prompt for an LLM, designed to generate precise, structured output. No fluff, no randomness—just targeted results.
For example:
- extract_wisdompulls only the most important insights from a text, ditching the filler.
- create_essaytakes an input and crafts a solid essay with structured arguments.
- analyze_logsprocesses raw log files and highlights anomalies without making you dig through endless lines of text.
Since Fabric runs in the terminal,piping data in and out is effortless. Let’s say I want a local LLM to analyze web server logs:
Dtrh.net.weblog
While fabric is not without issue - and may have limitations in specific scenarios, it clearly demonstrates a much more efficient experience, with output to be much closer to deterministic than otherwise - but not in a way that is considered negative. LLMs turn out to respond to rules and commands quite well if you do it right
A key concept here is “context length,” which refers to the maximum number of tokens a language model can retain before earlier information is overwritten—a limitation that explains why these models may struggle to recall long-term details reliably or generate extensive code without errors.
When you combine an LLM that short of harmful questions is not designed to respond with something like “I dont know, I forgot”, and you mix context length in with large asks - this is when you see LLMs generating garbage that comes across as legit.
However, when it comes to tasks such as extracting information, identifying keywords, applying logical reasoning, and detecting patterns, AI excels. For instance, consider analyzing a webserver log that is nearly 2.5 MB of raw text (approximately 12,000 lines). In such cases, AI-driven analysis can significantly outperform manual methods, potentially rendering traditional log analysis roles obsolete.
It’s important to note that the quality of the output largely depends on the quality of the prompt. Language models are designed to generate a response regardless of prompt clarity, which can sometimes lead to misleading or circular answers if not properly directed.
To address this challenge, tools like Fabric help users craft effective prompts, and the accompanying API is designed to extract the precise information needed. While pre-written prompts can simplify the process, tailoring questions to your specific context remains essential for obtaining accurate and useful results.
Fabric helps you prompt, and the API I am writing will help you pull the information you need to use those prompts as effectively as possible. It just makes asking those questions a bit easier, and pre written. But contextually, I think one is always best off directly asking in context to your specific need.cat dtrh.net-ssl.log | fabric –pattern analyze_logs
One of the coolest integrations Daniel built is with theYouTube API. This means you canscrape a full transcript from any video in secondsusing your own GPU. No clicking around, no manual effort—just raw data, ready to process.
Want a transcript of an hour-long video? Easy:echo “https://youtube.com/watch?v=EXAMPLE“ | fabric -y –pattern extract_transcript
Now let’s refine it further—distilling the video’s key takeaways:echo “https://youtube.com/watch?v=EXAMPLE“ | fabric -y –pattern extract_transcript | fabric –pattern extract_wisdom
Boom.Raw video ➝ text ➝ wisdom, in just one command.
Just a heads-up: the YouTube pluginrequires an API keyto function, so you’ll need to set that up.
Scraping Websites with Curl + Fabric
Maybe YouTube transcripts aren’t your thing. No problem—Fabric also works withdirect web scraping. Let’s say you want to analyze a site’s content:curl -L “https://tempertemper.ca“ -k -v -i | fabric –pattern coding_master | fabric –pattern create_threat_scenarios
Here, we’re:
- Fetchingthe site’s HTML source withcurl.
- Processing itwith Fabric’scoding_masterpattern (which explains or interprets the code).
- Generating possible security threat scenariosbased on the content.
Why This Matters
Fabric isn’t just another AI wrapper—it’s amodular, hacker-friendly toolthat lets you create your own workflows. Chain patterns together, pipe any input, andbuild automation that actually worksinstead of wrestling with clunky interfaces.
These are just a few examples of how you can take advantage of fabric - linux, windows, mac, and even android with a bit of work (check my github, ive got an installation script for all of the above that handles basically all of it for you)OSFile NameLinkLinux, MacOS, Androidautofabric.shDownload at GithubWindows 10 / 11autofabric_windows.ps1Download at GithubTempleOSautofabric_tOS.c[Dead]
Please NoteTempleOS was not written in pure c and has been removed. Especially because I didnt write my own compiler. THere are no plans to fix this.
Wisdom
- Seek the Hidden Patterns.
Everything is a network—code, people, knowledge, entropy. The strongest minds do not force order onto chaos; they ride the wave, map the motion, and predict the collapse before it begins. Your edge is not raw knowledge, but the ability to see the game behind the game.
- Security Is a State of Mind, Not a Checklist.
No system is unbreakable. No vault is impregnable. The wise engineer does not build a wall and assume safety—they build a labyrinth, a mirror, a riddle, forcing attackers to play by their rules. Every lock should have a false key. Every gate should lead to a test. Know thy adversary, or be their prey.
- The Tools Are Nothing Without the Hand That Wields Them.
A fool with a great tool is still a fool. A master with a rock will sculpt the future. Learn to shape your tools, rewrite them, forge new ones. Break limits before they break you.
- Fail Quickly, Adapt Relentlessly.
Perfection is a graveyard of dead ideas. Move fast, break things, but understand the failure before you rebuild. The faster you iterate, the faster you evolve. Hesitation is a slow death.
- Knowledge Is a Fire.
To hoard it is to let it wither. To share it is to ignite revolutions. Teach what you know, but teach with precision—only the worthy should grasp the full blueprint. Some doors should stay locked.
- Choose Your Battles, Master Your Silence.
Not every war is worth fighting. Not every truth is worth revealing. Power comes not from shouting knowledge, but knowing when to let ignorance dig its own grave. Some enemies burn themselves out if you let them. Others require precision strikes. Learn the difference.
- Fear the Complacency More Than the Threat.
The system will fail. Your code will be attacked. Your work will be misunderstood. That is inevitable. What matters is that when it comes, you have already planned three moves ahead.
- The World Will Not Hand You Permission.
If you wait for the right moment, it will never come. If you ask for permission, you will be caged. Take the risk. Write the code. Start the fire. The ones who build the future are the ones who refuse to wait for it.
- Leave Behind Ghosts Worth Following.
Your work is temporary. Your systems will be replaced. Your code will rot. But ideas transcend decay. Make what you build so sharp, so undeniable, so ahead of its time that it leaves echoes long after you’re gone.
- The Last Truth: Everything Is Exploitable.
And that includes you. Stay sharp, stay paranoid, stay moving. You are either evolving, or you are decaying. There is no static state in the machine or in the mind.