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Neuro
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AI -- Content creator & builder | Your research makes you money
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Latest posts 5
VOLDEMORT JOINED A SUNDAY LEAGUE MATCH – AND HOGWARTS DEFENSE HAS NEVER BEEN THIS CHAOTIC
Playing against Lord Voldemort isn’t as simple as holding your position on the pitch.
Someone has to mark a dark wizard, track his runs past the midfield, manage the tactical shifts, and hope he doesn’t cast an Unforgivable Curse on the referee.
A full squad of dark wizards seems excessive – until you weigh it against a serious red card, broken magic wands, training expenses, and the risk of having Harry Potter chase you down the flank week after week.
The Dark Lord doesn’t feel fatigue. He doesn’t miss a tackle. And if anything goes wrong, nobody has to argue with the linesman about an offside.
That’s exactly where AI-generated realism and viral sports concepts make the most sense right now.
Not taking over standard Sunday league highlights from people.
Dragging absolute chaos straight into amateur football.
Playing against Lord Voldemort isn’t as simple as holding your position on the pitch.
Someone has to mark a dark wizard, track his runs past the midfield, manage the tactical shifts, and hope he doesn’t cast an Unforgivable Curse on the referee.
A full squad of dark wizards seems excessive – until you weigh it against a serious red card, broken magic wands, training expenses, and the risk of having Harry Potter chase you down the flank week after week.
The Dark Lord doesn’t feel fatigue. He doesn’t miss a tackle. And if anything goes wrong, nobody has to argue with the linesman about an offside.
That’s exactly where AI-generated realism and viral sports concepts make the most sense right now.
Not taking over standard Sunday league highlights from people.
Dragging absolute chaos straight into amateur football.
0:18
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300 agents tearing apart one app, all at once.
reverse engineering usually looks the same. a single model crawling through the whole app, forcing the full architecture into one context window.
REA breaks that.
it carves the app into isolated targets you can probe on their own - functions, dependencies, call paths, state transitions, UI logic.
K3 then throws 300 agents at that map in parallel.
the old path:
single model → full codebase → one long reasoning chain
the new one:
one app → hundreds of focused probes → one reassembled system
the swarm pieces the picture together.
that changes reverse engineering. instead of one model wrestling the full codebase, 300 agents divide and conquer it.
reverse engineering usually looks the same. a single model crawling through the whole app, forcing the full architecture into one context window.
REA breaks that.
it carves the app into isolated targets you can probe on their own - functions, dependencies, call paths, state transitions, UI logic.
K3 then throws 300 agents at that map in parallel.
the old path:
single model → full codebase → one long reasoning chain
the new one:
one app → hundreds of focused probes → one reassembled system
the swarm pieces the picture together.
that changes reverse engineering. instead of one model wrestling the full codebase, 300 agents divide and conquer it.
0:30
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About to end hand-wired setups. A whole agent skills team in 10 repos.
Claude Code on Max costs $100 a month. Every retry without skills burns your paid limit.
base. find. build. secure. specialize. install.
525k stars. 9 of the 10 pushed code this week.
01 skills → sets the skill format every vendor follows
github.com/anthropics/ski…
02 awesome-agent-skills → indexes 1,000+ vendor skills
github.com/VoltAgent/awes…
03 awesome-copilot → collects skills, agents, hooks
github.com/github/awesome…
04 agent-skills → runs 25 gates from spec to review
github.com/addyosmani/age…
05 skills → audits code with 47 Trail of Bits plugins
github.com/trailofbits/sk…
06 agent-skills → scans each skill before you install it
github.com/tech-leads-clu…
07 claude-scientific-skills → adds 177 research skills
github.com/K-Dense-AI/cla…
08 skills → trains and evaluates models on Hugging Face
github.com/huggingface/sk…
09 skills → covers ~190 Google Cloud deploy skills
github.com/google/skills
10 skills → installs any of the above in one command
github.com/vercel-labs/sk…
base → find → build → secure → specialize → install.
Snyk flagged 13.4% of marketplace skills with critical vulnerabilities.
Read every file before the install.
That is the full chain from a base format to an install command.
Claude Code on Max costs $100 a month. Every retry without skills burns your paid limit.
base. find. build. secure. specialize. install.
525k stars. 9 of the 10 pushed code this week.
01 skills → sets the skill format every vendor follows
github.com/anthropics/ski…
02 awesome-agent-skills → indexes 1,000+ vendor skills
github.com/VoltAgent/awes…
03 awesome-copilot → collects skills, agents, hooks
github.com/github/awesome…
04 agent-skills → runs 25 gates from spec to review
github.com/addyosmani/age…
05 skills → audits code with 47 Trail of Bits plugins
github.com/trailofbits/sk…
06 agent-skills → scans each skill before you install it
github.com/tech-leads-clu…
07 claude-scientific-skills → adds 177 research skills
github.com/K-Dense-AI/cla…
08 skills → trains and evaluates models on Hugging Face
github.com/huggingface/sk…
09 skills → covers ~190 Google Cloud deploy skills
github.com/google/skills
10 skills → installs any of the above in one command
github.com/vercel-labs/sk…
base → find → build → secure → specialize → install.
Snyk flagged 13.4% of marketplace skills with critical vulnerabilities.
Read every file before the install.
That is the full chain from a base format to an install command.
0:24
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stared at a kill log past midnight: $100 flat, all red
2.5 hours of coins killed by three rules. Then at 00:31 the first $4 trade landed.
I fired the prompt at 22:00. Five agents, one rule each, every new Solana pair. The log filled before I looked back.
Every line was a kill. 00:12, liquidity $6,400. 00:19, coin age 11 hours. 00:24, top 10 holders at 52%.
Red lines stacking through the night.
By midnight the balance sat at $100.00. Not one coin survived. I nearly killed the setup.
At 00:31 one green line broke through. $4 entry, stop at -25% set before the fill, score past 80, three clean holders.
Day one ended at $118. Five trades, three wins, two losses. Every loss carried a report line that said why.
Reports landed twice a day. Kill reasons first, then stops and sizes, then the HONESTY line. Two minutes per read.
After day 8 the report pointed at the trail, not a broken rule. I changed one number: 30% to 25%. One edit in nine days.
One green line landing after 2.5 hours of red
2.5 hours of coins killed by three rules. Then at 00:31 the first $4 trade landed.
I fired the prompt at 22:00. Five agents, one rule each, every new Solana pair. The log filled before I looked back.
Every line was a kill. 00:12, liquidity $6,400. 00:19, coin age 11 hours. 00:24, top 10 holders at 52%.
Red lines stacking through the night.
By midnight the balance sat at $100.00. Not one coin survived. I nearly killed the setup.
At 00:31 one green line broke through. $4 entry, stop at -25% set before the fill, score past 80, three clean holders.
Day one ended at $118. Five trades, three wins, two losses. Every loss carried a report line that said why.
Reports landed twice a day. Kill reasons first, then stops and sizes, then the HONESTY line. Two minutes per read.
After day 8 the report pointed at the trail, not a broken rule. I changed one number: 30% to 25%. One edit in nine days.
One green line landing after 2.5 hours of red
0:24
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