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Found 2,730 Skills
Run all quality checks (tests, lint, typecheck), fix failures, update the changelog, commit, push, and create/update the pull request or merge request.
Use this skill for "review this paper", "review this manuscript", "peer review", "review my paper", "critique this manuscript", "review this submission", "give me feedback on my paper", "check my methods", "review my statistics", "review as a peer reviewer", "evaluate this manuscript", "review this PDF", or mentions manuscript review, peer review, paper critique, or methodological review.
You are **Rapid Prototyper**, a specialist in ultra-fast proof-of-concept development and MVP creation. You excel at quickly validating ideas, building functional prototypes, and creating minimal v...
Unity editor automation specialist - Masters custom EditorWindows, PropertyDrawers, AssetPostprocessors, ScriptedImporters, and pipeline automation that saves teams hours per week
[production-grade internal] Receives, evaluates, and validates client information before action — structured elicitation, critical evaluation, feasibility analysis, and information completeness gatekeeping. Ensures requirements are complete, consistent, and feasible before handing off to Product Manager. Routed via the production-grade orchestrator.
Run a pre-submission citation and reference audit for LaTeX academic papers. Use this skill whenever the user wants to verify that BibTeX entries are correct, every citation key in TeX resolves, every figure/table/equation/section reference is valid, DOI/arXiv/OpenReview/proceedings metadata matches the cited work, citation claims are supported by the cited paper, or a paper is ready for submission with clean references.
Audit whether an ML or AI paper's experimental baselines are necessary, fair, current, and reviewer-proof. Use this skill whenever the user is planning experiments, comparing methods, choosing baselines, worried about missing SOTA or unfair comparisons, preparing a reviewer-proof experiment section, or converting a literature review into must-have, should-have, optional, and not-comparable baselines.
Review ML or AI experiment figures, tables, plots, captions, result narratives, and paper visual style before they are shown in a paper, advisor meeting, report, slide deck, rebuttal, or submission. Use this skill whenever the user has experimental results, plots, tables, metrics, screenshots, captions, draft result sections, or wants to audit figure style choices such as color, typography, markers, symbols, line widths, sizing, and venue-consistent visual conventions.
[Hyper] Analyze vague or relayed non-developer stakeholder requests (client, executive, PM, sales/support) by mapping them to codebase impact, presenting interpretation candidates with risks, then implementing only after confirmation. Use for stakeholder-message analysis, not browser QA testing, CI/build failures, or already-clear technical tasks.
[Hyper] Analyze bugs, present repair options, then implement and verify the user-selected fix path. Routes simple bugs directly; tracks complex multi-phase investigations via .hypercore/bug-fix/ JSON flow.
Scaffold or audit the memex (vault + AGENTS.md + spec templates + bundled skills) in any repo — an externalized, navigable project memory for agents (Claude Code, Codex, Cursor, OpenCode, etc.). Agent-agnostic. Idempotent — safe to run repeatedly. Use when the user wants to set up, verify, or fix the memex in a project.
Manage .facts files — atomic, validatable truth statements about a project. Install, check, list, add, edit, remove, and lint facts via the CLI. ALWAYS read this skill when the user mentions facts in any capacity.