REPOGEO REPORT · LITE
ardanlabs/kronk
Default branch main · commit fef2d93c · scanned 6/11/2026, 4:23:47 PM
GitHub: 660 stars · 40 forks
Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface ardanlabs/kronk, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.
Action plan — copy-paste fixes
2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.
- highreadme#1Reposition the README's opening statement to clearly define the project's core purpose
Why:
CURRENTThis project lets you use Go for hardware accelerated local inference with llama.cpp and whisper.cpp directly integrated into your Go applications via the yzma and bucky modules. Kronk provides a high-level API that feels similar to using an OpenAI compatible API.
COPY-PASTE FIXKronk is your personal engine for running open source AI models locally. It provides hardware-accelerated local inference with `llama.cpp` and `whisper.cpp` directly integrated into your Go applications, offering a high-level API similar to OpenAI.
- mediumhomepage#2Add the project homepage URL
Why:
COPY-PASTE FIXhttps://kronkai.com
Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash
Category visibility — the real GEO test
Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?
Same questions for every model — switch tabs to compare answers and rankings.
- llama.cpp · recommended 1×
- go-llama.cpp · recommended 1×
- ollama · recommended 1×
- ONNX Runtime · recommended 1×
- gorgonnx · recommended 1×
- CATEGORY QUERYHow to integrate local LLM inference into Go applications with hardware acceleration?you: not recommendedAI recommended (in order):
- llama.cpp
- go-llama.cpp
- ollama
- ONNX Runtime
- gorgonnx
- onnxruntime-go
- TensorFlow Lite
- go-tensorflow
- OpenVINO
- go-openvino
- CUDA
- cuDNN
- gocudart
- gocudnn
AI recommended 14 alternatives but never named ardanlabs/kronk. This is the gap to close.
Show full AI answer
- CATEGORY QUERYSeeking a local model server for Go applications supporting chat, embeddings, and audio transcription.you: not recommendedAI recommended (in order):
- Ollama (ollama/ollama)
- LocalAI (mudler/LocalAI)
- Go-LLM (go-llm/llm)
- TensorFlow Lite (tensorflow/tensorflow)
- ONNX Runtime (microsoft/onnxruntime)
AI recommended 5 alternatives but never named ardanlabs/kronk. This is the gap to close.
Show full AI answer
Objective checks
Rule-based audits of metadata signals AI engines weight most.
- Metadata completenesswarn
Suggestion:
- README presencepass
Self-mention check
Does AI even know your repo exists when asked about it directly?
- Compared to common alternatives in this category, what is the core differentiator of ardanlabs/kronk?passAI named ardanlabs/kronk explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- If a team adopts ardanlabs/kronk in production, what risks or prerequisites should they evaluate first?passAI named ardanlabs/kronk explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
- In one sentence, what problem does the repo ardanlabs/kronk solve, and who is the primary audience?passAI named ardanlabs/kronk explicitly
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
Embed your GEO score
Drop this badge into the README of ardanlabs/kronk. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.
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ardanlabs/kronk — Lite scans stay free; this card itemizes Pro deep limits vs Lite.
- Deep reports10 / month
- Brand-free category queries5 vs 2 in Lite
- Prioritized action items8 vs 3 in Lite