AI/ML●●Solid
Gcontext – a tree of llms.txt files to steer agents on support tasks
llms.txt tree structure lets agents navigate context instead of dumping everything.
Big BrainNiche Gem
bsampera
1024d ago
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A lightweight app to let LLM work for oncall
by tanglearncode·Jul 12, 2026·3 points·1 comment
AI Analysis
●●●BangerSolve My ProblemBig Brain
Local-first context injection solves the generic advice problem better than cloud RAG pipelines.
Strengths
- •Local-first architecture ensures sensitive runbooks never leave the desktop environment.
- •Directly contrasts generic LLM advice with grounded, team-specific actions in real-time.
- •Integrates with existing MCP ecosystems without requiring heavy server infrastructure.
Weaknesses
- •Requires manual maintenance of local knowledge bases which can drift from reality.
- •Desktop-only approach limits collaboration compared to centralized incident platforms.
Category
Target Audience
SREs, DevOps engineers
Similar To
Cursor · Sourcegraph Cody · Aider
Post Description
The biggest gap today in SRE agents is missing domain knowledge. So they cannot give accurate results for oncall incident handling. I just didn't find any lightweight and suitable solution to exactly solve the problem. So I created a desktop application NeatContext. It does nothing but can let LLMs know your domain knowledge to handle the incidents right.
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