Updates, generates, and validates tests using git-workspace context and TDD/BDD methodology. Use when code changes require new or updated test coverage.
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。
2,364 件 ・ 関連度順
概要と使いどころ
Updates, generates, and validates tests using git-workspace context and TDD/BDD methodology. Use when code changes require new or updated test coverage.
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。
Guides project ideation via Socratic questioning to produce a validated brief. Use before specification when requirements are unclear.
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。
Turn hunches into accepted results: worthiness score, evidence bar, research-to-rules. Use when vetting ideas. Not for QA; use night-market-validation-and-qa.
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 FlashRAG for retrieval-augmented generation research workflows: config/data validation, retrieval and index building, generation/refinement components, RAG pipelines/method reproduction, evaluation, and WebUI setup.
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 MosaicML Composer for PyTorch training loops, speedup methods, loggers, checkpoints, distributed launch, profiling, and model export.
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。
Routes substantive ML, AI, data, scientific-computing, and software-engineering requests to the smallest useful set of managed repository skills. Invoke proactively when a request names or implies a package, framework, model family, dataset, modality, workflow, backend, deployment target, evaluation method, or implementation approach that may benefit from repository guidance, even if no repository is named. Narrow progressively from area to family to repository root: inspect only the one or two most likely area pages; compare candidates by capability, task surface, model/data format, training versus inference versus evaluation intent, runtime constraints, and root-skill description; then open only the selected root and relevant sub-skills, references, or scripts. Select multiple repositories only when each adds a distinct capability. Do not load the whole collection, treat dependencies or incidental integrations as capabilities, choose by name alone, or force a match when no exact taxonomy family applies.
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。
Online (incremental) covariance, correlation, and precision estimation in Python — the streaming complement to sklearn.covariance. Use when code needs a covariance/correlation matrix updated per observation, recomputes np.cov/np.corrcoef in a rolling loop, must judge or compare covariance estimates, or proposes a new covariance methodology. Points to task-specific 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。
Use when turning a single topic into a full content plan with multiple angles, formats, and a publishing calendar. Triggers on "content plan", "content calendar", "snowball method", "turn one topic into many posts", "content multiplication", "30 days of content", "content from one idea".
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。
Socratic method teaching skill that guides users to discover answers themselves through questioning, never giving direct answers. TRIGGER when: user's message contains 'socratic', 'Socrates', or '소크라테스'. Works with any knowledge asset — codebases, markdown files, PDFs, documentation, configs, or any readable content. Respond in the user's language.
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。
SSRF hunting - OOB-mandatory methodology. Cloud metadata, blind SSRF via Collaborator/interactsh, redirect-based bypass, headless browser chains. Wiki-first, FIND schema 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。
IDOR / BOLA hunting - two-account methodology, identifier discovery and UUID leak chaining, the trusted-identifier test, GraphQL node and nested-object IDOR, cross-tenant escalation, write and delete operations. Bounded ID sampling, never range sweeps. Wiki-first, FIND schema output. Trigger on IDOR, BOLA, broken access control, object level authorization, cross-tenant, "read another user's data", "swap the id", or any API path or parameter carrying a numeric ID, UUID, or account identifier.
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。
Boot-to-root methodology for a full machine (THM/HTB/PG/CTF box, "get user.txt+root.txt", "root the box", "foothold to root"). Enforces basic-tool recon (nmap, nc, ffuf, nuclei, dig) before anything custom, wiki-first lookups, and ALWAYS pspy + linpeas/winpeas for privesc. Use when handed a box/IP to own end-to-end.
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 the user asks to "create a plot arc", "story structure", "add a plot point", "story timeline", "track foreshadowing", "pacing", "sagging middle", "act structure", "story arc", "plot outline", "snowflake method", or wants to plan and manage the narrative structure of a story. It owns book-level pacing; NOT for the craft of scene outcomes or chapter hooks, which this skill only plans in the outline (use scene-craft), or a pacing check as a revision pass (use revision-continuity).
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。
Research why neural architectures and training methods work through forward computation, geometry, gradients, optimization dynamics, historical experiments, and competing explanations. Use for deep mechanism questions about neural networks, AI models, layers, representations, or training; explain the meaning in plain language with evidence and explicit limits.
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。
Plans an architecture-driven change to code that already exists: module boundaries, type responsibilities, layering, coupling, and the public surface a revision moves. Produces a buildable change plan that names the types, modules, and methods involved and records the surface delta each change makes. Use when the user wants to plan, scope, or sequence a restructure, extraction, split, consolidation, responsibility shift, or API revision of existing code, including "these responsibilities are wrong, plan the fix". Does not assess an area and stop at findings — use architectural-analysis. Does not specify new behavior — use plan-a-feature. Does not diagnose a bug — use investigate. Does not write the code — use refactor to restructure it or tdd to build 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。
Guides the post-Schrems II Transfer Impact Assessment process following EDPB Recommendations 01/2020 six-step methodology. Covers assessment of third country legal frameworks, supplementary measures evaluation, and TIA scoring. Activate for international data transfers, SCCs, third-country adequacy, or Chapter V compliance. Keywords: TIA, Schrems II, transfer assessment, EDPB, supplementary measures, SCCs, international transfer.
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。
Guides the post-Schrems II Transfer Impact Assessment process following EDPB Recommendations 01/2020 six-step methodology. Covers destination country surveillance law assessment, European Essential Guarantees evaluation, and supplementary measures determination. Keywords: TIA, transfer impact assessment, Schrems II, EDPB recommendations, supplementary measures.
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。
Universal opt-out mechanism implementation across US state privacy laws. Covers Global Privacy Control (GPC) signal technical implementation, state-by-state recognition requirements, browser detection methods, authenticated vs unauthenticated handling, and compliance 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。
On-site and remote vendor audit procedures per GDPR Article 28(3)(h). Covers audit planning, evidence collection methodologies, finding classification, remediation tracking, and audit report generation for processor compliance verification.
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。
Vendor privacy risk tiering methodology for processor management. Covers scoring factors including data volume, sensitivity, transfer locations, certifications, breach history, and control maturity with weighted risk calculation and tier assignment.
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。
Preparation guide for ISO 31700 privacy by design for consumer goods certification. Covers the 30 requirements across design, production, and disposal phases. Includes gap assessment methodology, remediation planning, and mapping to GDPR Article 25 data protection by design obligations for consumer-facing products and services.
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。
Guides privacy law change monitoring and impact assessment for multi-jurisdiction organisations. Covers regulatory tracking sources, change classification, impact scoring methodology, and implementation prioritisation. Keywords: law monitoring, regulatory tracking, change management, impact assessment, implementation priority.
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。
Implements NIST SP 800-88 Rev. 1 media sanitization procedures including Clear, Purge, and Destroy methods for all media types. Covers certificate of destruction generation, verification procedures, vendor management for third-party destruction, and chain of custody documentation. Activate for data destruction, media sanitization, secure erasure, certificate of destruction queries.
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。
Guides privacy program maturity assessment using the AICPA/CIPT Privacy Maturity Model with five levels: Ad Hoc, Repeating, Defined, Managed, and Optimized. Covers assessment methodology across ten privacy domains, scoring criteria, gap analysis, maturity roadmap generation, and benchmarking against industry peers. Keywords: privacy maturity, AICPA, maturity model, assessment, roadmap, benchmarking.
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。