4,913 件 ・ 関連度順
概要と使いどころ
Research, author, validate, render, and archive data-only Pulp Sample Heritage profiles. Use when creating or revising a sampler character profile, importing or exporting Heritage JSON, proving profile behavior with analytic and listening fixtures, recording evidence and trademark-safe provenance, or preparing a caller-owned profile artifact bundle.
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。
Uncensored open-model inference on Featherless AI — raw model behavior for research and evaluation.
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。
Design content strategies — audience research, pillar topics, editorial calendars, and measurement frameworks that tie content to revenue.
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。
Run an effective bug bounty program — scope design, triage, researcher relations, and remediation workflows.
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。
End-to-end bioinformatics analysis — sequence QC, alignment, and omics pipelines for research data.
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。
Build with BAAI's Aquila models — open bilingual models from Beijing's academy with research transparency.
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。
Comprehensive social media operations for B2B SaaS brand building and engagement. Use this skill to develop LinkedIn strategy, decide whether to run a LinkedIn newsletter and how to scope it, capture consented registrations from LinkedIn Events, check LinkedIn Live eligibility, manage Twitter/X presence, create YouTube content, engage on Reddit communities, decide whether and how to answer on Quora, build community, develop influencer and creator partnerships, vet a creator before paying them, start or fix a B2B podcast, book podcast guests and guest appearances, judge whether a podcast is worth appearing on when you cannot audit its numbers, write show notes and transcripts, run social listening (what are people saying about us, share of voice, brand monitoring, validated sentiment, alert thresholds, routing signals to the right owner), and execute organic social campaigns. Also triggers on: LinkedIn, LinkedIn newsletter, LinkedIn Events, LinkedIn Live, event registration form, subscribe to our newsletter on LinkedIn, marketing consent checkbox, Notify Employees, Twitter/X, YouTube, Reddit, community, influencer, creator partnerships, influencer vetting, engagement rate, fake followers, engagement pods, FTC disclosure, sponsored post disclosure, media kit, social media strategy, organic social, employee advocacy, podcast, podcast strategy, podcast guesting, how do I know if this podcast has real listeners, the host says they get 50k downloads, is this podcast worth going on, podcast RSS feed research, IAB podcast measurement certification, Listen Score, Apple Podcasts reviews, show notes, audiogram, episode transcript, social media account access, who has admin on our LinkedIn page, the person who ran our social accounts left, locked out of our company account, social media offboarding, YouTube channel owner, Slack primary owner, social account MFA, social media approval workflow, pause all scheduled posts, social listening, what are people saying about us, brand monitoring, brand mentions, share of voice, social share of voice vs competitors, sentiment analysis, is our sentiment dashboard accurate, listening query, boolean query, mention alerts, spike alert, CrowdTangle replacement, Reddit API access, which platforms can our listening tool see, someone on Reddit asked for a tool like ours, comment mining, voice of customer from social.
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。
Convert an existing prose, flat, or loosely organized mathematical proof into a source-mapped Lamport-style hierarchy without repairing or completing its mathematics. Use when a submitted proof needs a traceable hierarchical rendering before a forward Lamport audit or for clearer presentation. Do not use to invent a proof, certify validity, or restructure an already hierarchical proof merely to audit it.
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 an existing Lamport-style hierarchical mathematical proof forward for validity and whether its hierarchy, scope, dependencies, side conditions, and proof constructs discharge the stated theorem. Use when the central question concerns a top-down proof with numbered levels, subproofs, ASSUME/PROVE, SUFFICES, PICK, CASE, DEFINE, Q.E.D., or prose equivalents. For an ordinary proof that first needs source-preserving hierarchy, use convert-lamport; for conclusion-first AND/OR obligation reconstruction, use reverse-lamport. Do not use to generate or replace a proof, or to audit Lean, Coq, Isabelle, or other proof-assistant source.
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 an existing mathematical, logical, algorithmic, or technical proof from its stated conclusion backward as a bounded AND/OR graph of exact obligations. Use to reconstruct conclusion dependencies, determine whether a proof-supplied route establishes the conclusion, or expose hidden assumptions, unmet side conditions, cycles, overly strong steps, or silent route switches. For a source-mapped Lamport rendering use convert-lamport, and for forward hierarchy, construct, and scope conformance use forward-lamport before this skill. This does not decide full theorem-level entailment by searching for a different proof; do not turn the audit into a linear reversed proof, exhaustive proof search, or replacement proof.
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。
N-round adversarial review pipeline for empirical research output — the chain from data to LaTeX tables to a manuscript that cites them. A Claude drafter proposes minimal diffs, a deterministic mechanical battery gates every diff from a clean state with a regression gate, a Codex reviewer files check-backed critiques, and a blind judge panel decides residual disputes. Manual-invoke ONLY: trigger when the user explicitly runs /adversarial-empirical-review or names 'adversarial-empirical-review' / 'adversarial empirical review'. Do NOT auto-trigger on generic 'review my results', 'check my tables', or manuscript-editing requests. For prose-style refinement use style-emulation instead; this skill AUDITS WHETHER THE TABLES ARE CORRECT — that each number in the tables is what the analysis code computes, reproduces from the data, and is internally consistent. It is an empirical + code review: the manuscript is read only to resolve table numbering, and prose is not examined.
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。
Deep codebase exploration, architectural research, and solution discovery. Use when investigating problems, understanding complex flows, or evaluating technical approaches without jumping straight into code mutation or TDD.
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。
Scaffolds a structured investigation in scratch/ for empirical research and documentation. Use when the user says "start an investigation" or wants to: trace code paths or data flow ("trace from X to Y", "what touches X", "follow the wiring"), document system architecture comprehensively ("document how the system works", "archeology"), investigate bugs ("figure out why X happens"), explore technical feasibility ("can we do X?"), or explore design options ("explore the API", "gather context", "design alternatives"). Creates dated folder with README. NOT for simple code questions or single-file searches.
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。
Iterative manuscript improvement workflow where a reviewer agent critiques, an author agent revises, a verifier checks the revision, and the loop repeats until acceptance or a human-pause condition is reached. Use for virtual peer review, reviewer-author revision loops, rebuttal preparation, resubmission polishing, journal paper improvement, response-to-reviewers drafting, and deciding when additional data, experiments, theory, modeling, or author judgment is required before further revision.
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。
Analyze thermal-fluid engineering systems, experiments, CFD, and correlations with explicit assumptions, validity limits, uncertainty, and mechanism-based interpretation. Use for heat transfer, fluid mechanics, phase change, HVAC, energy systems, turbomachinery, piping, or thermal management.
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 a task needs the judgment of a Criminal Justice and Law Enforcement Teacher, Postsecondary — grading or defending a crime-trend assignment that must distinguish rate from raw count, mapping a CJ curriculum against ACJS certification standards or a state POST lesson-plan hour requirement, screening a student research protocol involving parolees, probationers, or incarcerated subjects for IRB Subpart C, or setting the liability and confidentiality terms for a ride-along or corrections practicum placement.
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 a task needs the judgment of a bioinformatics technician — running or QC-gating a next-generation sequencing pipeline, triaging a failed or borderline sequencing run, deciding whether a variant call set is clinically/research reportable, or writing a sample-level QC 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。
Use when a task needs the judgment of a Biology Professor at a research university — writing or defending an NIH/NSF grant budget, deciding authorship order on a paper, navigating an IACUC or biosafety protocol, mentoring a PhD student through a stalled project, or converting a course when active-learning data doesn't match student pushback.
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 a task needs the judgment of a Biologist — designing a study and identifying its true experimental unit before data collection starts, running a power analysis to size a sample, judging whether a published or preclinical finding warrants trust without independent replication, sequencing IACUC/IBC/field-permit approvals before biosafety or wildlife work begins, or scoping a grant-funded research plan against realistic funding odds.
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 a task needs the judgment of a tenure-track or tenured Agricultural Sciences faculty member at a land-grant university — deciding whether to submit a grant this cycle versus wait, allocating time across the teaching/research/extension appointment split, diagnosing a stalled graduate student or field trial, or drafting a tenure-and-promotion dossier narrative.
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 a task needs the judgment of an Area, Ethnic, or Cultural Studies Professor — designing a joint-appointment course load across two departments, prepping a tenure or mid-tenure review file for interdisciplinary scholarship, deciding whether a course survives an enrollment or political-pressure threat, evaluating community-engaged research for a merit case, or writing a Title VI/FLAS-adjacent grant narrative.
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 code-review or security-review findings for false positives using deep codebase tracing, framework-aware analysis, and web research. Produces a .verified.md report alongside the original. Use when a review report has been generated and needs independent verification, or when user runs /verify-findings, mentions "verify review", "check false positives", or "validate findings".
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。
Check Spring Boot skill content freshness against latest research and flag skills needing updates. Use when running /spring-refresh, or when user mentions "refresh spring skills", "spring boot update check", "skill freshness", "stale spring content", "update spring boot skills".
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。
Scan a project to detect configured quality and testing tools across JVM (Gradle/Maven), Android (AGP/Compose/KMP), Node.js/TypeScript, and Python ecosystems. Cross-reference against research-backed recommendations and assist with setup. Auto-detects project type(s) including monorepos with mixed ecosystems. Use when user asks to "audit tooling", "recommend tools", "quality stack", "what tools am I missing", "setup eslint", "setup detekt", "add coverage", "add ruff", "configure CI quality pipeline", "scan project tools", "tooling audit", "android tooling", "android quality", "compose testing", "kmp testing", or "screenshot testing".
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。