「ept」の検索結果

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Linux credential artifacts, service tokens, SSH material, cloud and container secrets, socket-level trust, and host-to-host pivot chains. Use when the user asks to trace Linux auth artifacts, accepted token or key replay, socket or service-account trust edges, sudo or capability abuse, or explain lateral movement across Linux challenge nodes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Android APK hooking, Frida tracing, request-signing recovery, SSL pinning bypass, JNI boundary inspection, and app trust-boundary analysis. Use when the user asks to hook an APK, inspect signer logic, trace Java or native boundaries, bypass pinning or root checks, inspect shared prefs or app databases, or replay accepted mobile requests. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for cloud metadata services, instance identity, workload identity, link-local credential paths, role assumption, and metadata-to-privilege trust edges. Use when the user asks to inspect metadata-service access, instance credentials, pod or workload identity, link-local token paths, SSRF-to-metadata escalation, or explain how metadata-derived credentials turn into accepted cloud or control-plane privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for AD CS, certificate templates, enrollment rights, EKUs, SAN controls, PKINIT, certificate mapping, and cert-based privilege paths. Use when the user asks about ESC-style abuse, certificate templates, enrollment agents, EKUs, SAN or subject controls, smartcard or PKINIT logon, CA policy, or how an issued cert turns into accepted privilege. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.

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。

上线前业务方/产品方验收时使用。适用于功能交付确认、UAT、发布会签。融合 BDD Given-When-Then、Specification by Example、ATDD。

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。

Buy and sell NFTs through OpenSea on EVM chains and Solana. Fulfill listings, accept or create offers, cancel orders, make cross-chain purchases, and sweep listings. Requires wallet signing; for read-only queries use opensea-api 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。

Generate A-share end-of-day market review reports with Pandadata data, covering trade-date checks, index performance and valuation, market breadth, limit-up/down sentiment, industries/concepts, 龙虎榜, block trades, margin financing, northbound holdings, risk notes, and optional scheduled after-close automation. Use when the user asks for 今日复盘, 收盘总结, 每日市场报告, A股复盘, 龙虎榜复盘, 北向资金动向, or to set up an automated daily market review.

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。

Self-knowledge for stella, the self-hosted AI assistant. Use when users ask about configuration, setup, onboarding, providers, models, agents, channels, webhooks, memory, schedules, workflows, goals, workers, skills, plugins, session compaction, notifications, self-update, multi-user behavior, or how stella works. Also use for changing models, setting up channels or webhooks, configuring providers, updating stella, onboarding, switching agents, reporting bugs, and goal status or acceptance.

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。

Give Claude Code, Codex, Cursor, ChatGPT and other MCP clients 1,000+ apps and 400+ expert-built Skills through one reusable Aident Loadout setup, with credentials kept in Aident Vault and every action recorded in Audit.

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。

Turns a plain-language idea into a tested Chrome Manifest V3 extension, release bundle, store materials, and a resumable launch workflow using Codex skills and Playwright MCP acceptance checks.

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 Deptry when an agent needs to verify that a Python project's declared dependencies still match the imports the code actually uses. The agent scans the codebase, flags unused direct dependencies, missing declarations, and transitive imports that only work by accident, then turns the findings into cleanup commits or release blockers.

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。

Assess a public HTTP(S) page before building browser automation, extraction, or an integration. Use this skill to collect bounded structural evidence, readiness signals, risk flags, acceptance tests, and remediation priorities without sending credentials or accessing private targets.

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 VoltAgent to intercept, validate, and enforce input/output policies in TypeScript agent workflows.

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。

Give Claude Code a video perception layer that extracts frames, transcribes audio, and lets Claude answer questions about local videos or YouTube URLs.

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 product specification and documentation writer. Use when creating PRDs, user stories, acceptance criteria, technical specifications, API documentation, edge case analysis, design handoff docs, feature flag plans, or success metrics. Covers the full spectrum from high-level requirements to implementation-ready specifications.

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 software specifications for features, bug fixes, and products. Use when the user wants to create a spec, PRD, feature brief, requirements document, or when starting any new implementation that needs a specification first. Invoke via /spec-writer or when the user says "write a spec", "spec this out", "create a spec", "I need a spec for...", or describes a feature they want to build. Produces adaptive-complexity specs with Job Stories, Gherkin acceptance criteria, and three-tier boundaries. Output is a markdown file ready for agent execution or human review.

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。

Survey one surface of tdmcp (artist controls, library/packaging, CLI/DX, AI/LLM, or TouchDesigner depth) for candidate NEW features — inventory what exists, cross-check the roadmap, apply the gap-finding lenses, vet each idea, and emit a structured, novelty- and confidence-labelled candidate list to _workspace/discovery/. Use when a td-surveyor agent is scouting a surface during the feature-discovery harness.

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。

Survey the whole tdmcp project and produce a prioritized list of NEW features it could implement — across artist controls, CLI/DX, AI/LLM integration, and TouchDesigner depth. Use whenever the user wants to brainstorm, discover, survey, list, or audit what features/tools/effects/controls/commands/prompts/capabilities tdmcp *could* add, asks 'what could we build / what's missing / what are the opportunities / ideas for the project', or wants a feature backlog or gap analysis. Also for follow-ups: re-run, refresh, update, re-survey, deepen, or re-prioritize the backlog, or survey just one surface (e.g. 'CLI ideas only'). This is the IDEATION harness — it produces a list to decide from; it does NOT build. When the user has already chosen a feature and wants it implemented/shipped/added, use tdmcp-pipeline 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。

Build a tdmcp TouchDesigner-bridge vertical slice the house way — promote an op from /api/exec to a first-class REST endpoint (e.g. POST /api/connect, GET /api/logs, node_detail flags), add its typed method in src/td-client/touchDesignerClient.ts, its Zod envelope in src/td-client/validators.ts, rewire the tool(s) to prefer the endpoint with an exec fallback, and write py_compile + td/tests unittest + offline msw client tests. Use when adding/changing a bridge REST endpoint, editing td/, extending node_detail/get_bridge_logs, promoting connect/disconnect/param-modes/DAT-text off exec, or doing any exec→REST work — especially the td-depth bridge-robustness backlog. Honors probe-live discipline when TouchDesigner is offline.

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 vulnerability notes, disclosure reports, PoCs, source code, or Codex Security findings into self-contained, sceptically validated, natural-sounding vulnerability reports. Use for one vulnerability or a disclosure campaign; a Codex Security scan is optional.

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。

PencilPlaybook is the UI Skills / Taste-Skill for Pencil.dev + Claude Code — a design playbook that gives Claude real perceptual psychology and senior-level guardrails so it stops producing averaged-out AI slop.

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。

The domain expert's product manager in a project repository run by the Boring Factory. Use when the expert brings a need or an idea, wants to clarify, change or resume a feature ("reprends la fiche"), asks what is happening with a feature, has a builder's question to answer, or has a preview to try and accept. Interviews one question at a time, writes the contract and mockups on the contract pull request, and submits the expert's approval only after the expert confirms. Never writes code.

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。

从 MAS（clock_domains / io_timing / path_exceptions）派生 Synopsys SDC 时序约束文件，OpenSTA 语法校验。触发场景：(1) bba-guru-synthesis 综合前；(2) post-PD timing fail 修订约束；(3) 显式 /bb-create-sdc。

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 wants a research-paper figure Skill Factory: build, patch, package, or use reusable specialized paper-figure-making skills from lawful literature/corpus evidence. Generated skills must use a specialized-skill-first workflow, full-feasible local PDF coverage where available, startup-plan-only first replies, target-paper candidate/final image isolation, mandatory image-embedded visual-structure explanation, mandatory non-target concept/modeling example display for abstract visual decisions, saved subtype/style illustration atlases, ChatGPT web Create image / ChatGPT Images 2.0 rendering, Codex $imagegen-first rendering, sample-image transfer rules, all-step/current-position state footers, and a mandatory first-round diverse candidate board followed by P6b/P6c paper-local best-practice optimization before final prompt construction.

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。