skvm-generalDrive the skvm CLI on behalf of a user to profile models, AOT-compile skills, run skill-assisted tasks, run benchmarks, and manage compiled proposals. Trigge...
Install via ClawdBot CLI:
clawdbot install lec77/skvm-generalGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Calls external URL not in known-safe list
https://skillvm.ai/install.shAudited Apr 23, 2026 · audit v1.0
Generated May 22, 2026
Companies can use skvm bench to systematically test and compare the performance of their LLM skills across multiple models and conditions. For example, an enterprise deploying a customer support skill can benchmark it with original vs. AOT-compiled variants to determine the best configuration for accuracy and speed.
Organizations can profile various LLMs (e.g., GPT-4, Llama 3, Claude) on 26 primitive capabilities using skvm profile to select the most suitable model for their specific tasks. A healthcare startup might profile models to find the best fit for medical text analysis.
IoT companies can use skvm aot-compile to precompile skills for specific target models, reducing latency and compute costs at the edge. For instance, a smart home device manufacturer can compile a voice command skill to run efficiently on a low-power chip.
Developers can quickly test and debug individual skill implementations using skvm run with a single task JSON, enabling rapid iteration. A fintech startup can validate a fraud detection skill on a specific transaction trace before large-scale deployment.
Companies can create a pipeline using skvm pipeline to profile and AOT-compile a skill across multiple models in one go, streamlining the model selection and optimization process. An e-commerce platform could optimize a recommendation skill across different models to find the best performer.
Offer automated LLM skill benchmarking services to enterprises, using skvm bench to provide detailed performance reports across models and conditions. Revenue comes from subscription fees for regular benchmarking and optimization insights.
Provide AOT compilation and optimization services for companies deploying AI skills, ensuring they run efficiently on target hardware. Revenue is generated per compilation job or through annual contracts for ongoing optimization.
Use skvm profile to help clients identify the best LLM for their specific use cases, reducing trial-and-error costs. Revenue from consulting fees based on project scope.
💬 Integration Tip
Ensure skvm is installed via the official script and set OPENROUTER_API_KEY before running any LLM-calling commands. For benchmarking, always confirm with the user due to high cost, and use --concurrency for parallel runs.
Scored May 22, 2026
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