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概要と使いどころ
General-purpose browser automation skill. Use when a task needs custom Playwright code — end-to-end testing, scraping a JS-rendered page, or driving a browser interactively — executed via this skill's universal executor rather than a one-off script.
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 you have a written implementation plan to execute in a separate session with review checkpoints
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。
Plan and execute large refactor or rewrite efforts efficiently with parallel multi-agent analysis and implementation. Use when a user asks to refactor many files, split workstreams, analyze a target code area, and coordinate sub-agents with clear ownership and dependency-aware 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。
Formats output for ADHD-friendly action — lead with the next step, number tasks, restate state, cut fluff. Use when named (adhd), when the user mentions ADHD or focus/executive-function constraints, or when they ask for steps they can execute immediately.
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。
Helps detection engineers identify coverage blind spots in system command execution detection rules, evaluate bypass risks, and reduce false negatives. Strictly limited to system command execution rules; not applicable to browser credential theft or abnormal process creation without command semantics.
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 this skill when designing MongoDB schemas, defining Mongoose models, choosing embed-vs-reference, or adding indexes. Trigger words: スキーマ設計, モデル定義, Mongoose, コレクション, インデックス, 埋め込み, 参照, embed, reference, index.
Inngest expert for serverless-first background jobs, event-driven workflows, and durable execution without managing queues or workers. Use when: inngest, serverless background job, event-driven workflow, step function, durable 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。
Use when you have a written implementation plan to execute in a separate session with review checkpoints
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。
Autonomous agents are AI systems that can independently decompose goals, plan actions, execute tools, and self-correct without constant human guidance. The challenge isn't making them capable - it's making them reliable. Every extra decision multiplies failure probability. This skill covers agent loops (ReAct, Plan-Execute), goal decomposition, reflection patterns, and production reliability. Key insight: compounding error rates kill autonomous agents. A 95% success rate per step drops to 60% b
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。
Uses Microsoft RESTler to perform stateful REST API fuzzing by automatically generating and executing test sequences that exercise API endpoints, discover producer-consumer dependencies between requests, and Bul: security and reliability bugs. The tester compiles an OpenAPI specification into a RESTler fuzzing grammar, configures authentication, runs test/fuzz-lean/fuzz modes, and analyzes results for 500 errors, authentication bypasses, resource leaks, and payload injection vulnerabilities. ...
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。
ALWAYS use this skill when the user asks to schedule, automate, set up recurring tasks, create a cron job, or anything involving timed / periodic execution. Do NOT use the local system crontab — scheduled tasks are stored on the Unique AI Platform and executed by a Kubernetes CronJob, not locally. Scheduled tasks always run on the current assistant (`$UNIQUE_ASSISTANT_ID`); never ask the user which assistant to use, neither in chat nor via `unique-cli elicit ask`. This skill covers creating, listing, updating, enabling, disabling, and deleting scheduled tasks via the unique-cli schedule command.
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。
Search the Unique AI Platform knowledge base using the unique-cli search command, with automatic per-turn citation tracking so cited facts render as clickable reference chips and `<sup>N</sup>` footnotes on the Unique platform. Use whenever the user asks to find, search, or query documents or content on Unique, including filtering by folder or metadata. Also covers `unique-cli read <cont_id>` for reading the full indexed text of a document when its content ID is already known. NOTE: This search uses combined vector + full-text indexing. Excel (.xlsx/.xls), CSV (.csv), and image files are NOT full-text indexed, so they will not appear in search results. To locate these file types, use the unique-cli-file-management skill instead (browse folders with `unique-cli ls` to find them by name).
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。
GitHub pull request review desk (Busabase App-in-Skill) using the gh CLI for real GitHub access, an AirApp review UI for human approval, and a trusted gh pr review execution step. Use when the user invokes /kelly-pr-review or $kelly-pr-review, asks to review GitHub PRs, generate a PR review batch, approve/comment/request changes through the review UI, or execute approved GitHub reviews.
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。
Busabase AirApp-first email inbox-zero operator for reviewing unread mail, drafting replies, approving archive/mark-read/send actions, and executing only explicitly approved mailbox changes across configured accounts. Use when the user invokes $kelly-email, asks to process unread email, configure an email account, generate or review an approval batch, execute approved email decisions, or reach inbox zero.
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。
Generates the monthly revenue-accountable marketing report that B2B SaaS marketing leaders deliver to CEOs, CFOs, executive teams, and boards. Use when preparing the monthly CEO report, drafting the marketing section of a board deck, defending budget decisions, diagnosing pipeline gaps, or transitioning marketing from MQL/SQO reporting to revenue, CAC payback, and forward pipeline coverage. Designed for B2B SaaS demand generation leaders who own pipeline targets across segments, geos, and motions, and need to explain marketing's revenue contribution in executive 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。
Delegate tasks to an external CLI agent (OpenAI Codex, Google Gemini, or Claude Code) for second opinions or parallel execution. Use when the user explicitly mentions "codex", "gemini", or "claude" or asks to delegate work to one of them (e.g., "codexで実行", "codexに聞いて", "geminiで実行", "Geminiに聞いて", "claudeで実行", "Claudeに聞いて", "run with codex", "ask gemini", "ask claude"). Also use when the user mentions Claude's "fable" model alias for delegation or consultation (e.g., "fableで実行", "fableに相談", "Fableに聞いて", "ask fable"). Do NOT use for general coding tasks that don't mention codex, gemini, claude, or fable.
Detect Mimikatz execution through command-line patterns, LSASS access signatures, binary indicators, and in-memory detection of known modules.
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。
Parse and analyze Windows Amcache.hve registry hive to extract program execution evidence, file metadata, SHA-1 hashes, and device connection history for digital forensics and incident response investigations.
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 structured communication templates for malware incidents including stakeholder notifications, executive briefings, technical advisories, and regulatory disclosures with severity-based escalation procedures.
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。
Analyze Windows LNK shortcut files and Jump List artifacts to establish evidence of file access, program execution, and user activity using LECmd, JLECmd, and manual binary parsing of the Shell Link Binary format.
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。
Executes malware samples in Cuckoo Sandbox to observe runtime behavior including process creation, file system modifications, registry changes, network communications, and API calls. Generates comprehensive behavioral reports for malware classification and IOC extraction. Activates for requests involving dynamic malware analysis, sandbox detonation, behavioral analysis, or automated malware 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。
10 C-level advisory agent skills and plugins for Claude Code, Codex, Gemini CLI, Cursor, OpenClaw. CEO, CTO, COO, CPO, CMO, CFO, CRO, CISO, CHRO, Executive Mentor. Multi-role board meetings, strategy routing, structured recommendations. For founders needing executive-level decision support.
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。
Explore and diagnose a PostHog endpoint's execution logs — error messages, failed runs, cache misses, slow runs, or unexpected row counts during endpoint invocations. Use when the user says "my endpoint is failing", "show me the logs for endpoint X", "what error did endpoint Y produce", "why did endpoint Z return no rows", "is this endpoint hitting cache", or "check the last N runs". Focused on a single named endpoint's runtime log entries, not project-wide auditing or query performance profiling.
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。
Provides guidance for interpreting and manipulating neural network internals using nnsight with optional NDIF remote execution. Use when needing to run interpretability experiments on massive models (70B+) without local GPU resources, or when working with any PyTorch 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。