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概要と使いどころ
CLI output formatting standards for worktrunk. Load before editing any code that calls warning_message, hint_message, error_message, info_message, eprintln, or println, or that produces strings the user will see (CLI help, progress UI, snapshot text). Documents ANSI color nesting rules, message patterns, and output system architecture.
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。
Route retrieval of Chinese medical guidelines, consensus statements, regulatory documents, drug information, safety notices, standards, and public-health materials through authoritative originals and verified fallback copies. Use when a canonical medical source is blocked, slow, unavailable, moved, paywalled, or difficult to parse, or when designing and auditing domestic medical-source fallback rules. Do not treat secondary summaries or reposts as independent clinical 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。
OCR text recognition expert. ALWAYS invoke this skill when you need to extract text from images or PDFs — including invoices, receipts, ID cards, bank cards, business licenses, tables, handwritten documents, or any visual text 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。
Generate professional documents after tool failures using shell_agent for complex formats or write_file for simple text/markdown
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 coordinated internal/external documents from reference materials with consistent formatting and cross-references
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 documents via shell commands and locate nested outputs using find.
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 professional documents using write_file when primary data sources fail, leveraging embedded domain knowledge instead of external retrieval
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 documents with write_file when retrieval tools fail, with explicit guardrails against task context drift
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。
Multi-method PDF extraction with sequential fallback and OCR for scanned documents
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 structured PDF documents with tables, sections, and scoring using Python libraries in execute_code_sandbox
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。
Complete PDF lifecycle: download, extract, and generate structured documents with reportlab
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。
Audio production with diagnostic analysis, timecode parsing from documents, and verified export workflow
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。
Social engineering attack techniques beyond email phishing for authorized red team and physical penetration testing engagements. Covers pretexting methodology (persona creation, authority and urgency psychological triggers, rapport building), vishing (voice phishing via caller ID spoofing, IVR system exploitation, VoIP infrastructure setup with Twilio/Asterisk), smishing (SMS-based phishing, carrier gateway abuse, short code impersonation), physical social engineering (tailgating and piggybacking, RFID badge cloning with Proxmark3, lock picking and bypass, dumpster diving for sensitive documents), USB drop attacks (Rubber Ducky keystroke injection, Bash Bunny multi-vector payloads, O.MG cable covert implants, BadUSB firmware attacks), watering hole attack planning and execution, and OSINT-driven targeting (LinkedIn harvesting, organizational chart reconstruction, employee pattern analysis). Integrates with the Social Engineering Toolkit for attack automation, Proxmark3 for RFID/NFC cloning, USB Rubber Ducky and Bash Bunny for physical payload delivery, and BeEF for browser exploitation. Maps to MITRE ATT&CK T1598 (Phishing for Information), T1566 (Phishing), T1091 (Replication Through Removable Media), and T1189 (Drive-by Compromise). All techniques require explicit written authorization and defined rules of engagement.
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 as the top-level router for Omniverse Realtime Viewer USD app requests and focused viewer reference documents.
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。
Develop evidence-backed structural and architectural security hardening proposals from vulnerability disclosures, supplied findings, incident or assessment documents, source code, or a completed Codex Security scan. Use when a user asks for systemic improvements, alternatives beyond per-finding patches, before-and-after security architecture views, engineering tradeoff analysis, or an implementation-ready plan for a selected hardening option. Also use automatically after a Codex Security scan with reportable findings when the top-level scan workflow requests final-report hardening guidance.
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。
Evidence-first pull request judge that reviews a PR and posts one consolidated GitHub review with inline comments via the gh CLI. Runs the repo's own deterministic checks first, researches current official docs before any claim about external libraries or APIs, then reviews correctness, security, structural quality (code judo, spaghetti growth, file-size limits), and AI slop including useless code comments. Every finding must carry evidence, every comment passes a deterministic noise gate before posting, and the verdict (APPROVE, COMMENT, REQUEST_CHANGES) is weighed by findings. Use when asked to review a PR, judge this PR, review this branch or diff before merge, run the-judge, "revise esse PR", "faca o code review", or "julgue esse PR". Do NOT use for reviewing prose or documents, fixing CI failures, resolving merge conflicts, writing the fix itself, or responding to review comments (use gh-address-comments).
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 structured Request for Comments (RFC) documents for proposing and deciding on significant changes. Use when the user says "write an RFC", "create a proposal", "I need to propose a change", "draft an RFC", "document a decision", or needs stakeholder alignment before making a major technical or process decision. Do NOT use for TDDs/implementation docs (use technical-design-doc-creator instead), README files, or general documentation.
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。
Feature planning and implementation with 4 adaptive phases (Specify, Design, Tasks, Execute). Auto-sizes depth by complexity. Writes testable requirements in EARS notation, atomic tasks, atomic Conventional Commits, and requirement traceability. Ships deterministic Python validation scripts so structural gates are enforced by code, not memory. Features an independent Verifier (author != verifier, evidence-or-zero), a discrimination sensor, a decision log (STATE.md), a test-coverage matrix, and a self-improving lessons layer. Stack-agnostic and tool-agnostic. Use when (1) planning features, (2) implementing with verification and atomic commits, (3) validating an implementation against a spec. Triggers on "specify feature", "discuss feature", "design", "tasks", "implement", "validate", "verify work", "UAT", "record decision", "pause work", "resume work". Do NOT use for pure architecture decomposition analysis or standalone technical design documents.
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 comprehensive Technical Design Documents (TDD) with mandatory and optional sections through interactive discovery. Use when user asks to "write a design doc", "create a TDD", "technical spec", "architecture document", "RFC", "design proposal", or needs to document a technical decision before implementation. Do NOT use for README files, API docs, or general documentation (use docs-writer instead).
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。
Expert guide for designing and building high-quality skills from scratch through structured conversation. Use when someone wants to create a new skill, build a skill, design a skill, or asks for help making Agents do something consistently. Also use when someone says "turn this into a skill", "I want to automate this workflow", "how do I teach my Agent to do X", or mentions creating SKILL.md files. Covers standalone skills and MCP-enhanced workflows. Do NOT use for creating subagents (use subagent-creator) or technical design documents (use create-technical-design-doc).
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。
Spec-driven feature work that freezes obligations instead of the plan: one human-reviewed plan with EARS criteria, path, entities, interface and one-way doors, then proof-backed checks, then build, then an independent Verifier. Use when the user says "tlc-spec-lean", "plan feature", "specify feature", "write the checks", "build this plan", or "verify work". Do NOT use for standalone design documents unattached to a feature, architecture decomposition analysis, or work that already has a task list or checklist to execute.
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 the user explicitly chooses iPollo Onto or starts an Onto workbench task. Build and maintain business systems directly in its connected tables, relationships and documents, saving useful results progressively. A generic CRM, search or writing request alone does not activate this workflow.
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 project evidence into maintainable Notion briefs, decision records, runbooks, and status documents without overwriting unrelated 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。
Detect indirect prompt injection (goal hijack). Instructions hidden in "external" content (documents, RAG, web) that the agent processes. Use when the agent has document/RAG/web/file 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。