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概要と使いどころ
Build structured communication templates for malware incidents including stakeholder notifications, executive briefings, technical advisories, and regulatory disclosures with severity-based escalation procedures.
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Designs and documents structured incident response playbooks that define step-by-step procedures for specific incident types aligned with NIST SP 800-61r3 and SANS PICERL frameworks. Covers playbook structure, decision trees, escalation criteria, RACI matrices, and integration with SOAR platforms. Activates for requests involving IR playbook creation, incident response procedure documentation, response runbook development, or SOAR playbook design.
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。
Builds a structured SOC incident response playbook for ransomware attacks covering detection, containment, eradication, and recovery phases with specific SIEM queries, isolation procedures, and decision trees. Use when SOC teams need formalized response procedures for ransomware incidents aligned to NIST SP 800-61 and MITRE ATT&CK ransomware techniques.
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。
Break down implementation plans into actionable task lists. Use after planning to create a structured task breakdown. Generates tasks.md with ordered, dependency-aware tasks.
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 and create a git commit following this repository's established message format. Use when the user asks to "commit", "commit all changes", "commit and document", or similar. Also applicable when any agent (gemini-cli, codex, qwen, opencode, claude-code) needs to stage and commit a set of changes with a properly structured message.
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。
Structured clarification workflow for underspecified requirements. Use before planning to resolve ambiguities through coverage-based questioning. Records answers in spec clarifications section.
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。
Scrapes pump.fun/board using Chrome browser automation to extract the top 100 trending Solana tokens and writes structured markdown for a trading agent to consume. Use this skill any time you need to: scan pump.fun for new tokens, refresh the pump.md token list, run the scheduled board scrape, collect Solana meme token data, or build/update a trading watchlist from pump.fun. Even if the user says something casual like "check pump" or "update the token list" or "what's trending on pump", use this skill. The output file path and format are configurable but default to /Users/8bit/solanaos/pump.md.
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 PDF documents to clean structured Markdown for LLM context. Supports two modes: fast (PyMuPDF) and accurate (IBM Docling TableFormer AI). Features aggressive persistent caching, image extraction with metadata, table detection, and batch processing. Use when asked to convert PDFs, extract PDF content, parse documents, or prepare PDF data for AI/LLM consumption.
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。
Nuxt SEO meta-module with robots, sitemap, og-image, schema-org. Use when configuring SEO, generating sitemaps, creating OG images, or adding structured 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。
Add, update, or retire an AI provider model option for the BYOK theme generator (OpenAI, Anthropic, Google) and verify the provider requests native structured output for it. Use when model lists go stale or a new provider/model is requested.
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 or change structured input for application use cases, including extracting HTTP request data for Actions invoked from controllers, jobs, or commands. Avoid DTOs for trivial scalar input.
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。
Read public X/Twitter post URLs as structured evidence through the ADHX API. Use for relevant user-provided or research-discovered x.com, twitter.com, or adhx.com links. ADHX does not search X, and long-form Article content may be incomplete.
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 new Claude skills from structured idea specifications. Use when the skill auto-generation pipeline needs to produce a Claude CLI prompt that creates a complete skill directory (SKILL.md, references, scripts, tests) following repository conventions.
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。
Transform client hearing sheets and meeting notes into structured requirements documents. Use when converting raw hearing data (Japanese/English) into formal requirements, generating traceability matrices, identifying gaps/ambiguities, and mapping requirements to WBS items. Triggers include "hearing to requirements", "meeting notes to specs", "requirements traceability", "gap analysis for requirements", or requests involving hearing sheet 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。
Generic helpdesk first-response skill for creating KB-based response drafts. Use when handling support tickets, creating response templates, or building a structured helpdesk workflow. Supports error code detection, keyword matching, confidence scoring, multi-language templates, and escalation workflows. Customize by providing your own KB articles and configuration.
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 simulating a technical interview to build confidence, expose reasoning gaps, and train structured communication under pressure.
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 learner needs a structured review session prioritizing high-value topics by recency, error history, and upcoming deadlines.
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 evaluating a completed or in-progress project across scope, correctness, quality, testing, and learning outcomes using structured Praise-Critique-Grow feedback.
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 a set of Rosetta Stone attribute mappings to a Narrative dataset by wrapping them in a one-shot workflow that calls the `CreateRosettaStoneMappingsIfNotExist` task. Consumes the structured output of `/generate-rosetta-stone-mappings`, normalizes the generator's snake_case to the workflow task's camelCase, re-validates every expression against the dataset's current schema, gates on user approval, submits via `narrative_workflows_create`, polls the triggered run, and reports per-mapping created / conflict / failed. Use when: "apply these mappings to dataset N", "create the Rosetta Stone mappings I just generated", "push the mappings I saved earlier to <dataset>", "productionize this mapping list", "submit the suggested_mappings array". (narrative-common)
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。
Translate a fuzzy analytical question into a rigorous investigation plan. Interrogates the ask, grounds the plan in the available data dictionary, applies analytical best practices, and produces a structured brief of query specifications for a downstream query-writing skill. Plans, does not write SQL. Use when: "why did X drop", "is there a relationship between A and B", "who are our highest-value customers", "what's driving the change in Y", "investigate this trend", "design an analysis for", "scope this analytical question". (narrative-common)
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。
Choose the design and the numbers a research run can honestly claim — write the structured METHOD RECORD (databases, date of access, search string, criteria, screening counts) that r0 validates, pick the claim strength a design can actually carry, record a statistic as data rather than prose, route to the reporting guideline the design owes, and decide what to preregister. Use when a run's question, design, search or statistics have to be settled before the writing, or when a claim needs a strength or a number attached to 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。
Two-phase code quality skill: (1) review codebase for structural smells — file LOC, method LOC, accidental complexity, test readability — producing a structured report, then (2) fix all smells via provable refactorings with ACN micro commits and green-bar-at-all-times discipline. Use this skill when the user says 'sweep', 'code review', 'find code smells', 'check method lengths', 'review for complexity', 'tidy up the codebase', 'refactor smells', or asks about long methods, test readability, or accidental complexity. Also trigger when users ask to 'clean up' or 'improve code quality' across multiple files.
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 a Marty-Cagan-style opportunity assessment interview and produce a ~2-page Opportunity Brief in Confluence. Covers business objective, customer, problem, success metric, current alternatives, assumptions/risks, and what we don't know yet. Triggers on "opportunity brief", "opportunity assessment", "discovery brief", "who is this for", "why are we building this", "validate this idea", "product discovery", or any request to frame a feature before implementation. One question at a time. Records accepted research gaps as structured Confluence Decision pages with bidirectional links.
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。
Load for .NET observability changes involving structured logs/Loki, Prometheus metrics, OpenTelemetry traces, exception handling, correlation IDs, dashboards, alerts, or production error diagnosis; not for ordinary business validation errors.
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。