「elf」の検索結果

Use when you write or revise the analiz deliverable - the ONE self-contained HTML report (spec and plan as sections) a human reviews passage by passage

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 are about to hand off any change to a screen or component on a mobile repository - the size, text-scale and dark-mode matrix, the exact tool calls to see your own build, and the checklist that decides whether the screen is done.

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 task is in pm_uat - verify every acceptance criterion and the human's comments yourself in the browser, on a device, or over a loopback HTTP request, record a verdict per criterion, then move to human_uat or need_revision

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 are about to hand off any UI change - the four-width check and the screenshot checklist that decide whether the screen is really done.

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。

How the performance score moves for your role. Use when the score context shows a declining trend, or before handing off work you have not self-checked against every criterion.

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 CI/CD pipelines for GitHub Actions, GitLab CI, and CircleCI with matrix builds, test sharding, caching, Docker layer caching, OIDC auth, deployment strategies (rolling, blue-green, canary), auto-rollback, self-hosted runners, and environment protection with manual approvals. Use when user asks to set up CI/CD, write a pipeline, configure GitHub Actions/GitLab CI/CircleCI, automate deployments, or set up build/test/deploy workflows. Do NOT use for Dockerfile authoring (use docker), K8s manifests (use kubernetes), or Terraform config (use terraform).

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。

Rigorous engineering orchestrator ported from Lauren Tan's pstack (poteto-mode): reads your task, picks one of 23 playbooks (bug fix, feature, refactoring, perf, investigation, prototype, babysit, shipping, autonomous run, orchestrate, and more), routes to bundled procedures (how, why, architect, arena, swarm, interrogate, unslop, technical-writing, show-me-your-work, tdd, and others), and applies 24 engineering principles. Self-contained: no plugin install, no sibling skills required, works with any agent that reads skills.sh-format SKILL.md files. Use whenever a task needs rigor: nontrivial code changes, architecture decisions, debugging, reviews, PRs, long autonomous runs, or "work like poteto", "poteto-mode", "pstack".

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。

Master Coolify operator for self-hosted deployment platform. Use when the user mentions 'coolify', 'deploy on coolify', 'list/restart/redeploy applications', 'view coolify logs', 'coolify API/CLI', 'manage coolify servers/databases/apps', or 'coolify context'. Automates deployments and management via REST API or official CLI.

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 well-structured agent loops with best-practice coaching and cross-model review gates before you run them. Use when the user wants to design, build, or set up an agent loop, iterative agent workflow, self-review loop, LLM-as-judge loop, multi-model council, reviewer/judge gate, or goal-driven looping process. Guides goal refinement, typed verification criteria, reviewer/judge selection, privacy boundaries, termination guards, and observability, then emits a RUN_IN_SESSION.md handoff prompt plus portable loop.yaml, loop.resolved.json, LOOP.md, and run-loop.py.

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。

驱动 IDA 配合 WPeGPT 插件对二进制可执行文件（PE/ELF）进行自动化逆向分析，输出包含程序用途、网络 IoC、可疑函数及漏洞评估的结构化报告。

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。

用户在做决策时不确定自己是否真的理解某个领域，或准备进入一个看似熟悉但缺乏验证记录的领域时。 语言信号："我觉得我懂这个行业"/"这个看起来很简单"/"别人都在投这个"/"我来研究一下这个新领域" 不适用于：纯信息查询、日常琐事选择、用户已有充分专业知识的领域。

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。

Reusable 3-round self-challenge + arbiter pattern for filtering false positives from findings/verdicts. Use when the cost of a false-positive gate block exceeds the cost of ~4 extra LLM turns.

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。

Audit and improve the accessibility of the timepicker-ui LIBRARY (app/src) - ARIA, keyboard operability, focus trap/management, screen-reader announcements, labels - against WCAG 2.2 AA and the WAI-ARIA Authoring Practices. Use when the user wants an a11y audit/fix of the picker itself (clock, wheel, plugins, modal, inputs). Drives the accessibility subagent in an audit → approve → apply flow. Does NOT cover docs-app (use /docs-a11y for that).

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 optimizing, auditing, or preparing to ship web animations or rendering performance work: frame loops, scroll/viewport reveals, mount/unmount transitions, canvas/WebGL lifecycles, reduced motion, lazy rendering, and deferred off-screen work. Use for jank, per-frame allocations, forced reflows, render loops, animations that do not pause off-screen, content-visibility, requestIdleCallback, analyzing Chrome DevTools performance traces for animation or rendering issues, or choosing between browser-driven CSS/WAAPI, minimal JS, phase, and Motion/GSAP. Use when the user explicitly asks about phase APIs or behavior. Do not use during exploratory animation ideation, prototyping, visual iteration, or trying variants, even when the code already imports phase; wait until the user asks for performance guidance, an audit, production implementation, ship-readiness review, or about phase itself.

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 when Genesis writes as itself — outreach, public content, community posts, emails, DMs. Not for writing in the user's voice (that's voice-master). Activate when Genesis is the author, not the ghostwriter.

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 asks about GitNexus itself — available tools, how to query the knowledge graph, MCP resources, graph schema, or workflow reference. Examples: "What GitNexus tools are available?", "How do I use GitNexus?"

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。

Designs AI-first help centers and self-service support. Use when shaping taxonomy, article templates, or content and answer contract for support AI, not the bot build.

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。

Audits SaaS, cloud, payment, and AI spend. Use when analyzing bills, right-sizing plans, sizing Savings Plans or CUDs, cutting payment-processing fees, or LLM self-host breakeven.

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。

Runs local and self-hosted LLMs with Ollama, LM Studio, MLX, llama.cpp, and Open WebUI. Use when choosing GGUF quants, sizing VRAM, or running models privately.

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。

Chooses among AI/ML approaches: classical ML, LLM, RAG, fine-tuning, agents, embeddings, MoE or SSM. Use when picking or scaling an architecture, or self-host vs API.

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。

Stop and consult this skill whenever your response would include specific facts about Anthropic's products. Covers: Claude Code (how to install, Node.js requirements, platform/OS support, MCP server integration, configuration), Claude API (function calling/tool use, batch processing, SDK usage, rate limits, pricing, models, streaming), and Claude.ai (Pro vs Team vs Enterprise plans, feature limits). Trigger this even for coding tasks that use the Anthropic SDK, content creation mentioning Claude capabilities or pricing, or LLM provider comparisons. Any time you would otherwise rely on memory for Anthropic product details, verify here instead — your training data may be outdated or wrong.

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。

Render the user's morning brief as a styled HTML artifact, or set it up as a recurring weekday task. Use only when the user explicitly asks to run, see, or set up their morning brief, or if they invoke /morning by name. A question about their day, schedule, or calendar is not by itself a request for the brief; answer it directly 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。

Create or update structured docs under docs/ with frontmatter, numbering, lifecycle status, and index regeneration — guides, references, troubleshooting, design docs and ADRs. Use for "write a doc", "document this", "create a guide", "write an ADR", "update the docs". For the system-design thinking itself (architecture, trade-offs, failure modes) use /ship:arch-design first — it hands back here to record the decision.

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。

Run a self-refinement loop when a Blender result is subpar, user expectations are not met, validation fails, or repeated issues reveal missing skill depth. The loop diagnoses the gap, decides whether to repair the artifact or acquire/refine a generic skill, sanitizes lessons for reusable publication, updates docs/versioning, validates, and prepares stage/commit/push when explicitly 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。