Inspect Evor engine hardware constraints and runtime failures from preflight data and logs.
npx skills add https://github.com/it-dainb/oh-my-evor --skill evor-gotchas
Please help me install this Agent Skill. Skill: evor-gotchas Source: https://github.com/it-dainb/oh-my-evor/tree/main/skills/evor-gotchas Command: npx skills add https://github.com/it-dainb/oh-my-evor --skill evor-gotchas
The evor-gotchas Skill helps operators and agents understand the constraints and failures encountered by the Evor engine, providing insights into hardware capabilities and runtime issues.
Use the evor-gotchas skill to inspect hardware constraints and accumulated failures for the Evor engine by running /evor-gotchas.
High-intent search queries and answers about installing and using this skill.
To inspect hardware constraints for machine learning model evaluations, query the Evor engine's preflight data to view the CapabilityProfile, including GPU architecture, VRAM, and supported data types.
Reviewing runtime failures in the Evor engine involves checking accumulated runtime logs to identify out-of-memory errors, approach deadends, and hardware limitations encountered during execution.
Machine learning missions fail with hardware limitations when the execution environment lacks required capabilities, which you can verify by inspecting the gotchas and CapabilityProfile before starting the mission.
Yes, you can check GPU VRAM and architecture compatibility before starting an Evor mission by querying the preflight data to ensure your hardware constraints match the model evaluation requirements.
Access out-of-memory errors and approach deadends from runtime logs by executing the gotchas query mechanism, which aggregates these detailed failure records for inspection.
tygwanGuide teams from rough ideas to concrete designs through structured questioning.
jackspaceBuild, evaluate, and deploy classical machine learning models with scikit-learn.
it-dainbVisualize Evor mission evolution via SSE streams from tree.json and telemetry.jsonl.
foeriaDiagnose frontend errors from stack traces and runtime logs.
