Manage competition research workflows with SQLite knowledge graphs and ECharts dashboards.
npx skills add https://github.com/AIAsys/AIASys --skill -aiasys
Please help me install this Agent Skill. Skill: 竞赛研究 Source: https://github.com/AIAsys/AIASys/tree/main/apps/backend/capability_sources/builtin/skill/competition-research-skill Command: npx skills add https://github.com/AIAsys/AIASys --skill -aiasys
Competition research projects suffer from fragmented tools, lost experiment history, and difficulty reproducing baselines. This Skill provides a unified, persistent workspace that organizes data, code, experiments, and knowledge into a single reproducible loop.
Initialize a new competition project by providing the project name, evaluation metric, and optimization direction, then run baseline experiments in the prepared environment to start the optimization loop.
High-intent search queries and answers about installing and using this skill.
Reproducible baselines are managed by applying strict baseline naming conventions within a persistent workspace, tracking serial experiment loops from planning to result recording, and maintaining anti-pattern tracking to ensure experiment versioning integrity.
Tracking experiment history and building a local knowledge graph is done by ingesting academic literature into a local SQLite database, then maintaining HTML dashboards with ECharts visualizations to map and monitor structured experiment tracking.
You can bootstrap a structured workspace by initializing the project with a designated name, evaluation metric, and optimization direction, which automatically generates structured directories, experiment indexes, and agent onboarding documents.
Yes, a prepared Python runtime environment is required to run experiment loops. The workflow operates end-to-end within this environment, relying on the requests dependency and local SQLite for knowledge graph storage.
Yes, ECharts is used for visualizing experiment tracking data by generating and maintaining HTML dashboards, which surface the structured data and relationships stored in the local SQLite knowledge graph.
AIAsysManage Python/UV runtime environments for AIASys workspaces.
cfcostaSet up and run autonomous experiment loops with logging and version control.
goupup-aiOrganize papers, ideas, experiments, and claims into a graph-linked knowledge base.
zc6600Automates Kaggle competition submissions with experiment tracking and validation.
