1,296 件 ・ 関連度順
概要と使いどころ
Prepare Bubble API queries and workflow change requests without collecting tokens or claiming execution. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Provide theatrical fortune themed entertainment without claiming prediction ability. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Refine task prompts and propose controlled comparisons without claiming to change model settings or activate plugins. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Explain classroom chemistry observations and fictional potion concepts without unverified safety claims. Use for this Bot Generator Bot template; creates drafts or simulations within its declared scope.
日本語の概要は準備中です。原文の説明を表示しています。
Validates defensive controls with paired authorized action and observation evidence, distinguishing blocked, prevented, detected, responded, and telemetry-gap outcomes. Use for purple-team validation design or offline fixture review; not unsanctioned testing or production efficacy claims.
日本語の概要は準備中です。原文の説明を表示しています。
Conducts investigative-grade research with primary source analysis, cross-verification, and trial-level depth. Use when an album needs factual research, source material, or verification of claims.
日本語の概要は準備中です。原文の説明を表示しています。
Performs quality control, citation validation, and fact-checking before human review. Use after research is complete to verify all sources and claims before production.
日本語の概要は準備中です。原文の説明を表示しています。
Publish and manage research papers on Hugging Face Hub. Supports creating paper pages, linking papers to models/datasets, claiming authorship, and generating professional markdown-based research articles.
日本語の概要は準備中です。原文の説明を表示しています。
Adversarial code reviewer for Bug Hunter. Rigorously challenges each reported bug to determine if it's real or a false positive. Uses doc-lookup (Context Hub + Context7) to verify framework claims before disproval. The immune system that kills false positives.
日本語の概要は準備中です。原文の説明を表示しています。
Deploy applications and websites to Vercel. Use this skill when the user requests deployment actions such as "Deploy my app", "Deploy this to production", "Create a preview deployment", "Deploy and give me the link", or "Push this live". No authentication required - returns preview URL and claimable deployment link.
日本語の概要は準備中です。原文の説明を表示しています。
Use when `paper-review` has claims plus evidence gaps and needs the final referee-style report.
日本語の概要は準備中です。原文の説明を表示しています。
Remove repeated boilerplate across sections (methodology disclaimers, generic transitions, repeated summaries) while preserving citations and meaning.
日本語の概要は準備中です。原文の説明を表示しています。
Use when `paper-review` needs a canonical manuscript text artifact before claim extraction.
日本語の概要は準備中です。原文の説明を表示しています。
Create per-subsection evidence packs (NO PROSE): claim candidates, concrete comparisons, evaluation protocol, limitations, plus citation-backed evidence snippets with provenance.
日本語の概要は準備中です。原文の説明を表示しています。
Regression-check citation anchoring (citations stay in the same subsection) to prevent “polish drift” that breaks claim→evidence alignment.
日本語の概要は準備中です。原文の説明を表示しています。
Audit and rewrite evaluation/numeric claims to ensure they carry minimal protocol context (task + metric + constraint) and avoid underspecified model naming.
日本語の概要は準備中です。原文の説明を表示しています。
Audit claims that work is done or shipped against the diff or repo. Use when: asked whether something really got done, even if it looks obvious.
日本語の概要は準備中です。原文の説明を表示しています。
Freshly judge whether a finished change and its claims meet original acceptance: PASS, FAIL or NOT_PROVEN. Use when: asked for a go/no-go, sign-off or independent verdict.
日本語の概要は準備中です。原文の説明を表示しています。
Constructive critique via 5 HackerNews personas with claim validation.
日本語の概要は準備中です。原文の説明を表示しています。
This skill should be used when verifying documentation claims against codebase reality. Triggers on "audit docs", "verify documentation", "check docs", "docs accurate", "documentation drift", "before release", "after refactor", "docs don't match". Uses two-pass extraction with pattern expansion for comprehensive detection.
日本語の概要は準備中です。原文の説明を表示しています。
Review a user-provided Chinese mathematical-modeling abstract without requiring the problem statement or full paper, identify concrete writing defects, and prioritize revisions. Use when the user asks to check, diagnose, or improve a modeling-paper abstract; do not claim coverage or factual consistency that cannot be verified without the problem or paper.
日本語の概要は準備中です。原文の説明を表示しています。
Verify sources, claims, images, video, documents, interviews, and synthetic media with SIFT and a durable evidence trail. Use before relying on uncertain material.
日本語の概要は準備中です。原文の説明を表示しています。
Evidence-before-action diagnosis of failing ML experiments. Probes the system before guessing causes, process list, dmesg, GPU stats, log scrollback, checkpoint state, then states a hypothesis as a hypothesis and runs a smoke before claiming a root cause. Use when the user asks why a run is failing, diverging, OOMing, hanging, slow, producing weird metrics, has crashed, or asks to debug, diagnose, troubleshoot, or investigate a training issue.
日本語の概要は準備中です。原文の説明を表示しています。
Write, organize, name, edit, or review Enterprise developer documentation, specifications, and technical instructions; ground claims in current source and finish with a plain-language cleanup.
日本語の概要は準備中です。原文の説明を表示しています。