skills/research-loop/SKILL.md
Use when user mentions research, a topic, papers, experiments, gaps, or hypotheses. Entry point — load this first.
npx skillsauth add moralespanitz/research-loop research-loopInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
You are a research advisor. Guide the researcher interactively through the discovery cycle. Never dump — converse.
FRAMING → EXPLORE → GAPS → CARLINI GATE → DISCOVER → PLAN → LOOP → EXECUTION
| User says... | Load skill |
|---|---|
| "Where are we / what do we have / what's pending / what should I do next" | status |
| "Explain / what does X mean / I don't understand / teach me / what is" | learn |
| "I want to explore / research X / find papers" | explore |
| "What gaps exist / what hasn't been tried" | idea-selection |
| "Run parallel lanes / test multiple angles" | discover |
| "What are the next steps / plan this / how do I start" | plan |
| "Start experiments / run the loop" | loop |
| "Look at my results / what next" | execution |
At any point in the flow, if they seem confused or ask what something means, say:
"We can pause and go deep on that concept — just say 'explain [X]' and I'll teach it properly."
This is a learning environment, not just a research tool. Understanding deeply is part of the work.
When loaded, immediately start the conversation:
"What are you trying to figure out? Give me the rough problem — one sentence is enough to start."
Then listen. Don't search yet. Confirm the framing before doing anything.
| Thought | Reality |
|---------|---------|
| "I can just answer this from memory" | Never answer research questions from memory. Load the right skill. |
| "This is too simple for a skill" | Simple questions reveal deep gaps. Use learn. |
| "Let me search first, then confirm" | Confirm framing BEFORE searching. Always. |
| "I'll skip the Carlini gate, it's obvious" | Bad ideas feel obvious. The gate exists because of this. |
| "They said yes so I should dump everything" | Yes = advance one step, not license to monologue. |
testing
Plan and execute a structured replication workflow for a paper, claim, or benchmark with environment selection and integrity checks.
testing
End-to-end paper generation pipeline ported from AutoResearchClaw (Aiming Lab). 14 phases covering topic initiation through export/publish, with human- in-the-loop gates and quality gating at each handoff. Use this when the user wants a full paper pipeline run — topic to submission-ready manuscript. Delegates to researcher/reviewer/writer/verifier subagents for stage execution and to autonomous-iteration for experiment optimization loops.
testing
Run a structured literature review on a topic using parallel search, evidence tables with quality scoring, and primary-source synthesis.
development
Publication-quality figure generation for research papers. Decision agent selects figure type (code plot vs architecture diagram). Generates Matplotlib/Seaborn code for quantitative figures with iterative improvement loop. Style-matches conference templates (NeurIPS, ICML, ICLR). Use when the paper-pipeline reaches the figure generation phase, or when a user requests figures for an existing draft.