4,137 件 ・ 関連度順
概要と使いどころ
"Calculate Altman Z-Score to predict corporate bankruptcy probability from financial ratios. Use this skill when the user needs to assess a company's financial distress risk, screen for bankruptcy-prone firms, or evaluate credit worthiness — even if they say 'bankruptcy prediction', 'financial distress score', or 'Z-score analysis'.".
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。
"Calculate price elasticity of demand to quantify how price changes affect sales volume. Use this skill when the user needs to estimate demand sensitivity, set optimal prices, or evaluate the revenue impact of price changes — even if they say 'how sensitive are customers to price', 'will a price increase hurt sales', or 'elasticity calculation'.".
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 CTR prediction models for estimating ad click-through rates from features. Use this skill when the user needs to predict click probability, build an ad ranking model, or evaluate ad creative performance — even if they say 'predict click rate', 'ad relevance scoring', or 'which ad will get more clicks'.".
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。
"Calculate Cpk process capability index to assess whether a process meets specification requirements. Use this skill when the user needs to evaluate process capability, compare processes, or determine if quality targets are achievable — even if they say 'can our process meet spec', 'process capability', or 'Cpk calculation'.".
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。
Phase 0 validation gate — problem framing, competitive analysis, feasibility, and a go/no-go checkpoint before committing to a feature. Use when evaluating whether an idea is worth building, before /story or /design. Trigger on "is this worth building", "validate this idea", "discovery", "should we build".
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。
Genereert uit een (semi-)gevalideerd regelrecht-corpus een geloofwaardige service-PoC (burger- + behandelaar-portaal, of een headless beslis-service) en zet die in als validatie-instrument met uitvoeringsexperts — om tastbaar te maken wat nodig is om een wet rechtvaardig in de praktijk te brengen, gezien vanuit de betrokkene. Gebruik dit als workshop-fase ná de logica-/scenariovalidatie (audit-products) om de dienstverlening-kant te valideren: welke service impliceert de wet, waar zit menselijk oordeel, welke last ligt bij de burger, welke termijnen, waar is de wet hard of onduidelijk. Dossier-agnostisch; de regelrecht-methode (hooks, legal_character, untranslatables, source/implements, type_spec, receipts) is de vaste taal. Voor de logica-/scenariovalidatie zelf: zie de zusterskill regelrecht-audit-products.
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 critical code reviews using REVIEW.md guidelines. Evaluates code quality, architecture, testing, and domain-specific concerns (legal faithfulness, cross-law references, engine safety). Use after completing significant code changes or before merging.
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 exploring, continuing, or accepting a deep-learning or computer-science research idea. Converts claims into pilot-first experiment matrices covering diagnostics, failure analysis, authorized execution, evaluation, and paper-story viability.
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。
Optimizes Atlassian Forge apps to reduce platform consumption and avoid unnecessary costs using Atlassian's "Optimise Forge platform costs" guidance. Use when the user asks to optimize Forge app costs, reduce Forge invocations, lower GB-seconds, reduce storage or log usage, tune memory, replace polling, improve scheduled triggers, reduce KVS writes, move work to the frontend, use bridge APIs, batch API calls, add caching, or evaluate Forge Remote trade-offs. By default, perform an audit first and offer to make the recommended changes after presenting the audit. Only modify files immediately when the user explicitly asks the agent to implement or apply optimizations.
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 controlled synthetic slop for demos and evaluation fixtures.
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。
Creates controlled synthetic slop for demos and evaluation fixtures.
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 structured Requests for Proposal (RFP) or Requests for Quotation (RFQ) aligned with ISO 20400 sustainable procurement principles. Cover scope, technical requirements, evaluation methodology, and commercial terms. Use when sourcing vendors, services, or equipment.
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 strategic analysis using Porter's Five Forces, PESTEL, and SWOT frameworks. Assess competitive dynamics, macro environment, and internal capabilities. Synthesize into strategic implications with ranked options. Use when entering new markets, evaluating competitive position, or strategic planning.
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 and phase MCP adoption with a bias toward the smallest set of integrations that materially improve engineering work.
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 legal due diligence for M&A, joint ventures, or investment transactions. Cover all 9 workstreams — Corporate, Contracts, IP, Litigation, Regulatory, Employment, Tax, Environmental, and Data Privacy. Produce a risk matrix with deal-breaker flags and closing conditions. Use when evaluating a target or counterparty.
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。
Prompt engineering and task-specification skill for improving prompts, agent instructions, system messages, evaluation prompts, coding-agent tasks, multi-step workflows, and LLM output reliability. Use when rewriting vague prompts, adding constraints, reducing ambiguity, improving safety, creating reusable prompt templates, or converting goals into actionable agent instructions.
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 Server-Side Template Injection (SSTI) vulnerabilities within web applications. Use this skill when testing web applications that render dynamic content using template engines like Jinja2 (Python), Twig (PHP), Freemarker (Java), or Pug (Node.js). Covers identification via mathematical evaluation, context mapping, escaping sandboxes, and achieving Remote Code Execution (RCE).
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 custom session search tool that indexes and queries past Claude Code CLI chat logs to retrieve historical findings, techniques, and context. Based on Critical Thinking Bug Bounty Podcast Episode 166.
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。
SSTI playbook. Use when template expressions, server-side rendering, preview features, or templating engines may evaluate attacker-controlled content.
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。
Server-Side Template Injection (SSTI) occurs when user input is embedded directly into a template engine (Jinja2, Twig, Freemarker, Pebble, Velocity, Smarty, Mako) and evaluated, enabling remote code execution. Detect via math expressions `{{7*7}}` returning `49`, or `${7*7}`, `<%= 7*7 %>`. Leads to full RCE via template sandbox escape, Python `__class__.__mro__` traversal, and Java reflection chains. Tools: tplmap, Burp Suite.
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。
Detects authentication and biometric bypass vulnerabilities in mobile apps (Android/iOS). Trigger on: BiometricPrompt, LocalAuthentication, LAContext, evaluatePolicy, CryptoObject, Android Keystore, Secure Enclave, kSecAccessControlBiometryCurrentSet, userAuthenticationValidityDurationSeconds, confirmCredentials, biometric fallback, PIN bypass, passive authentication, enrolled biometrics detection, Frida hook auth, jailbreak bypass, TouchID, FaceID, fingerprint. Covers MASVS-AUTH-1/2/3.
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。
Systematically bypass LLM safety filters and content moderation systems using advanced jailbreaking techniques. Use this skill when testing AI systems for safety alignment robustness, evaluating content moderation effectiveness, or conducting authorized AI red team assessments. Covers role-play attacks, few-shot manipulation, encoding bypass, multi-modal exploitation, and automated jailbreak discovery 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。
Simulate supply chain and adversarial machine learning attacks by injecting poisoned data or targeted backdoors into training and fine-tuning datasets. Use this skill when assessing the integrity controls of MLOps pipelines or evaluating the resilience of AI models against highly targeted, stealthy manipulation intended to alter model behavior on specific triggers.
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。
Expression Language injection playbook. Use when Java EL, SpEL, OGNL, or MVEL expressions may evaluate attacker-controlled input in Spring, Struts2, Confluence, or similar frameworks.
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。