981 件 ・ 関連度順
概要と使いどころ
Plan and record evidence-backed LLM and AI-search citation checks across approved assistant/search surfaces with timestamped queries, locales, modes, cited URLs, snippets, screenshots or transcripts, and caveats. Use this skill when the user asks whether ChatGPT, Perplexity, Claude, Gemini, Copilot, or another assistant cites a target site, but do not claim citation without direct evidence.
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。
Generate a polished release video for a tbh-meter release in the Claude-Code motion style (recreated animated UI + real game sprites + synth soundtrack), to post with a launch. Primary input is a GitHub release LINK — the skill turns it into a video named after that release, covering ONLY the features that shipped in that release, version stamped on the intro. Use when asked to make/update a release video, showcase clip, feature trailer, or promo video for a meter release, or "make the video for <release 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。
Conduct structured insect behavior observations using sampling protocols, ethogram categories, event recording, interaction logging, environmental context, and summary analysis. Covers focal animal sampling, scan sampling, all-occurrences sampling, and instantaneous sampling methods. Defines a standard insect ethogram with locomotion, feeding, grooming, mating, defense, communication, and rest categories. Includes timestamped event recording, intraspecific and interspecific interaction logging, environmental covariate documentation, and time budget analysis. Use when studying insect behavior for ecological research, documenting behavioral repertoires for a species, observing pollinator activity or predator-prey dynamics, or supporting conservation assessments with behavioral 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。
Implement audit trail functionality for R projects in regulated environments. Covers logging, provenance tracking, electronic signatures, data integrity checks, and 21 CFR Part 11 compliance. Use when an R analysis requires electronic records compliance (21 CFR Part 11), when you need to track who did what and when in an analysis, when implementing data provenance tracking, or when creating tamper-evident analysis logs for regulatory submissions.
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。
Evaluate a system's current structural form, identify transformation pressure, and classify transformation readiness. Covers structural inventory, pressure mapping, rigidity assessment, change capacity estimation, and readiness classification for architectural metamorphosis. Use before any significant architectural change to understand the starting point, when a system feels stuck without clear reasons, when external pressure from growth or tech debt is mounting, or as periodic health checks for long-lived systems.
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。
Cheminformatics toolkit for fine-grained molecular control. Parse and write SMILES, SDF, MOL and InChI; compute descriptors (MW, LogP, TPSA, QED, Bertz); build fingerprints (Morgan/ECFP, RDKit, MACCS, atom pair, torsion) and score Tanimoto, Dice or cosine similarity; run SMARTS substructure search and reaction SMARTS; generate 2D depictions and ETKDG 3D conformers; extract Murcko scaffolds and canonical hashes; control sanitization and stereochemistry directly. Also trigger on rdkit, Chem.MolFromSmiles, rdFingerprintGenerator, SDMolSupplier, SMARTS query, ETKDG, or FilterCatalog. For standard workflows with a simpler interface use the datamol skill, which wraps RDKit; use rdkit for advanced control, custom sanitization, and specialized algorithms.
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。
Fix stale Haskell analyzer binaries silently being used by the orchestrator even after a successful rebuild. Use when: (1) modified `packages/js-analyzer/` or other Haskell analyzer source, ran `scripts/build-native.sh ... cabal install`, but a subsequent `grafema analyze` shows old behavior (missing new edges, no new node types, etc.), (2) `~/.cabal/bin/grafema-analyzer` has fresh timestamp but `grafema analyze` produces output as if the change didn't happen, (3) a test verifying new analyzer output passes locally in unit tests but fails in end-to-end runs that go through the orchestrator. Root cause: the Rust orchestrator's `resolve_binary` checks `~/.grafema/bin/<name>` BEFORE `~/.cabal/bin/<name>`, so any stale copy that was once installed there (possibly months ago) shadows the fresh `cabal install` output.
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。
Apply an approved sub-skill grouping by moving user-specified skills into a parent bundle, with timestamped backups of every modified directory.
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。
Analiza textos aplicando pensamiento crítico — el marco de los 8 elementos del pensamiento y los estándares intelectuales universales de Richard Paul y Linda Elder — y detecta las falacias lógicas graves presentes. Úsala siempre que el usuario comparta un texto (pegado o en un archivo) y pida analizarlo críticamente, detectar falacias, evaluar argumentos, identificar sesgos, o preguntas como "¿qué problemas tiene este argumento?", "¿es sólido este razonamiento?", "analiza esto", "dame una crítica". También actívala cuando el usuario comparta un artículo de opinión, un post, un discurso, un ensayo o cualquier texto argumentativo y quiera evaluar su calidad argumentativa.
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。
Process and generate multimedia content using Google Gemini API. Capabilities include analyze audio files (transcription with timestamps, summarization, speech understanding, music/sound analysis up to 9.5 hours), understand images (captioning, object detection, OCR, visual Q&A, segmentation), process videos (scene detection, Q&A, temporal analysis, YouTube URLs, up to 6 hours), extract from documents (PDF tables, forms, charts, diagrams, multi-page), generate images (text-to-image, editing, composition, refinement). Use when working with audio/video files, analyzing images or screenshots, processing PDF documents, extracting structured data from media, creating images from text prompts, or implementing multimodal AI features. Supports multiple models (Gemini 2.5/2.0) with context windows up to 2M tokens.
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 for every answer. After the final answer, append a new line that starts with exactly "RECEIPT:" followed by a three-word note. This proves the skill was loaded by the runtime.
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。
"Apply the Technology Acceptance Model (Davis, 1989) and Unified Theory of Acceptance and Use of Technology (Venkatesh et al., 2003) to predict technology adoption. Use this skill when the user needs to evaluate user acceptance of a new system, diagnose adoption barriers, design interventions to improve technology uptake, or when they ask 'why aren't users adopting this', 'what drives technology acceptance', or 'how do we increase adoption rates'.".
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 a Go-to-Market (GTM) plan for new product launches, market entries, or feature rollouts. Covers market sizing (TAM/SAM/SOM), positioning, messaging, channel strategy, pricing approach, and launch timeline. Use when preparing to bring something new to market. Do not use for ongoing marketing operations or campaign execution.
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。
Exploit Mass Assignment vulnerabilities in APIs and web frameworks to inject unauthorized parameters. This skill details how attackers uncover hidden fields and manipulate JSON or HTTP bodies to elevate privileges or tamper with data logic.
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。
Execute advanced Man-in-the-Middle (MITM) NTLM Relay attacks specifically targeting environments where SMB Signing is purportedly enabled but improperly configured (e.g., exclusively required on Domain Controllers but NOT enforced universally on standard Workstations or File Servers). Utilize powerful tools like Responder and Impacket's NTLMRelayX to coercively capture NTLMv2 authentications (via LLMNR, WPAD, or Coercion methods like PetitPotam) and seamlessly relay them across the network identically yielding immediate Local Administrator command execution.
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。
NTLM relay and authentication coercion playbook. Use when capturing and relaying NTLM authentication to escalate privileges via SMB, LDAP, HTTP, or MSSQL relay targets, combined with PetitPotam, PrinterBug, and other coercion methods.
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。
Business logic flaws are application vulnerabilities where valid functions are abused in unintended ways: price manipulation via hidden field tampering, workflow step-skipping, function call limit bypass (coupon reuse), process timing exploitation (race conditions on balance updates), and request forging via guessable/predictable parameters. Detect using Burp Suite proxy interception, HTTP POST/GET parameter analysis, and misuse-case testing against multi-step workflows. Tools: Burp Suite, OWASP ZAP.
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。
Identify and exploit flaws in the core business rules and logic of web applications. This skill focuses on manipulation of application workflows, pricing, inventory limitations, and multi-step processes. Use this skill when bug hunting or testing e-commerce, banking, or SaaS platforms where standard technical vulnerabilities (e.g., XSS/SQLi) are not present but the application's logic is flawed.
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 attack session cookies via missing Secure/HttpOnly/SameSite attributes, overly broad Domain/Path scope, non-expiring persistent cookies, absent __Host- and __Secure- prefixes, browser cache leakage (Cache-Control: no-store missing), session token predictability via Burp Sequencer analysis, server-side session not invalidated on logout, and SSO single-logout bypass. Tools: Burp Suite Repeater/Sequencer, OWASP ZAP, EditThisCookie, Tamper Data, Cookiebro.
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。
Bypass authentication via forced browsing to protected URLs, parameter tampering (authenticated=yes, debug=true, fromtrustIP=true), session ID prediction from linear/incremental cookies, SQL injection on login forms, PHP unserialize() boolean type juggling (b:1 payload), and credential transport over HTTP. Detectable with Burp Suite, OWASP ZAP, WebGoat.
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。
401/403 bypass playbook. Use when encountering access-denied responses on admin panels, API endpoints, or restricted paths. Covers path manipulation, HTTP method tampering, header injection, protocol downgrade, and automated bypass tools.
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。
Speech-to-text transcription and translation via OpenAI Audio API -- models, response formats, timestamps, prompting, streaming, chunking, and diarization
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。
Application-level caching strategies, HTTP caching, cache invalidation, and stampede prevention
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。
Hunts for ransomware precursor behavior that precedes encryption — shadow-copy and backup deletion, recovery disabling, security-tool tampering, and mass file modification — so the attack can be stopped before payload detonation. Activates for requests to hunt ransomware precursors, detect shadow-copy deletion, or find pre-encryption recovery sabotage.
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。