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Found 150 Skills
USE FOR RAG/LLM grounding. Returns pre-extracted web content (text, tables, code) optimized for LLMs. GET + POST. Adjust max_tokens/count based on complexity. Supports Goggles, local/POI. For AI answers use answers. Recommended for anyone building AI/agentic applications.
Create a new Git branch or code worktree for experiments, features, baselines, rebuttal fixes, or method revisions. Use when starting an isolated code direction, creating a branch, creating a project-aware code worktree under a project control root, or setting up a worktree with UV sync, IDE config copying, linked assets, and worktree memory.
Analyse code changes since the last docs update and refresh the project's documentation files. Use when code has changed and documentation needs to be updated, after implementing new features, or before a milestone commit.
Plan, draft, and revise ML/AI limitations, scope, failure cases, ethics, broader impact, and conclusion caveats so they control claim boundaries without undermining the paper. Use when the user wants limitation wording, scope statements, failure-case interpretation, ethics/broader-impact text, or overclaim reduction.
Codex-native Academic Research Skills suite for deep research, academic paper writing, manuscript review, full research-to-paper pipelines, and experiment planning or validation. Use when the user asks for deep research, literature review, systematic review, meta-analysis, research question refinement, academic paper drafting, paper revision, citation or integrity checks, reviewer simulation, peer review, editorial decision letters, research-to-paper workflows, experiment execution planning, statistical interpretation, or human study protocol support. Also use for Claude-style ARS command aliases such as /ars-plan, ars-plan, /ars-outline, /ars-abstract, /ars-lit-review, /ars-citation-check, /ars-disclosure, /ars-format-convert, /ars-revision-coach, /ars-revision, and /ars-full. This skill vendors ARS role prompts, references, templates, and shared handoff schemas under ars/.
Use when planning, running, comparing, or recording computational experiments, benchmarks, ablations, autonomous research loops, overnight runs, training runs, or exploratory variants.
Use when verifying citations, bibliography, manuscript claims, source support, factual accuracy, numerical results, citation drift, or evidence provenance in academic work.
Use when responding to academic reviewers, planning revisions, writing rebuttals, mapping reviewer concerns, deciding concede/defend/reframe actions, or preparing camera-ready changes.
Use when building research dashboards, annotation tools, data browsers, paper-supporting demos, SOTA explorers, experiment viewers, or frontend interfaces for academic projects.
Paper Analyst — Responsible for in-depth paper reading, extracting method details, and building comparison tables. Activated when assigned to analyze papers by research supervisors or literature investigators. Conduct structured analysis on the Top 20 core papers, generate paper analysis cards and cross-paper comparison tables.
USE FOR spell correction. Returns corrected query if misspelled. Most search endpoints have spellcheck built-in; use this only for pre-search query cleanup or "Did you mean?" UI.
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.