agon
Runs autonomous AI research from a bare topic through literature review, idea refinement and experiments, with agents working in loops so you write no experimental code by hand.

Runs autonomous AI research from a bare topic through literature review, idea refinement and experiments, with agents working in loops so you write no experimental code by hand.
Research-mindset catalog distilled from ARIS skills, for subagent Read on demand.
This skill should be used when the user asks to "search for papers", "get paper info", "download LaTeX source", "generate BibTeX…
Use when checking novelty of a research idea or proposal. Extract core claims, do multi-source arxiv / Scholar / S2 search, grade…
Use when you need project-specific compute/server notes to pick a server or confirm a running task, if the project has filled its…
Research-persona catalog distilled from Sibyl prompts, for subagent Read on demand. 与 ARIS 互补 — ARIS 按阶段组织, Sibyl 按人格视角组织.
Read one arXiv paper in depth, write its wiki note, and emit a deep-lit result JSON.
Check whether the system environment satisfies prerequisites for running the research system.
Audit the latest experiment round's key conclusions, execution consistency, and scientific validity.
Implement, deploy, monitor, sync, and debug experiments from the STATE.md Runs table.
Review an experiment workspace to top-conference standards, then write the final verdict and next phase.
Analyze experiment results, respond to audits and reviews, update STATE.md, and plan the next experiment round.
Screen experiment plans before implementation, blocking unnecessary scale and meaningless gates.
Research a topic landscape, generate and select research ideas, and save them under ideas/.
Improve an existing idea using reviewer feedback and write the next idea version.
Review an idea for novelty and quality, write the review, and update its ideas.xml score.
Write a proposal from an idea, or revise the latest proposal based on a review.
Review a proposal across multiple dimensions, write the review, and update its proposals.xml score.
Run the scoped deep literature loop until relevant papers are saturated.
Orchestrate the experiment scientist/screener/coder/auditor/reviewer loop for a workspace.
Create or continue ideas from a topic and run create/review/refine/deep-lit to dual-gate saturation.
Run proposal refine/review/deep-lit loops in parallel until proposals are ready.
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