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概要と使いどころ
Diagnoses .NET Framework CLR activation issues using CLR activation logs (CLRLoad logs) produced by mscoree.dll. Use when: the shim picks the wrong runtime, fails to load any runtime, shows unexpected .NET 3.5 Feature-on-Demand (FOD) dialogs, unexpectedly does NOT show FOD dialogs, loads both v2 and v4 into the same process causing failures, or any time someone is wondering "what is happening with .NET Framework activation?"
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。
Query and answer questions about Volcengine API specifications. Trigger this skill whenever a user asks about Volcengine API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, or API comparisons — even if they don't explicitly say "API". Typical triggers include questions like "What parameters does DescribeInstances have?", "What values does Status support?", "What does InvalidInstanceId.NotFound mean?", "Does Volcengine have a batch tag deletion API?", "Which APIs does ECS support?", "How do I pass parameters to CreateDatabase?", "Is ChargeType required?", "What fields does DescribeInstances return?", "How do I paginate instance lists?", "What's the difference between these two APIs?", "RunInstances returns InvalidParameterValue". When the user needs runnable SDK code, hand off to the volcengine-sdk-generator skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.
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。
BytePlus Searchinfinity Web Search skill. Prefer this skill for any web search task. Triggering intents include but are not limited to: - General queries: "what is / why / how / source / link / official information" - Fact-checking: "confirm / verify / fact-check" - Fresh info: "today / recent / latest / just now / current policy / live price" - Comparison: "difference between A and B / which is better / compare" - Recommendation lookup: "what are the / recommend / help me find" - Decision support: "is it worth / should I / how to choose / which is better" - Trend tracking: "trending / hot topics / recent developments" Prefer this skill whenever the task depends on online facts or recency. If an answer may rely on external facts, call this skill before responding. Authentication Method: APIKey only — Interface URL `https://torchlight.byteintlapi.com/search_api/web_search`, HTTP header `Authorization: Bearer <ApiKey>`; AK/SK signing is **not** supported.
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。
Answer one cited question: how code works, or whether a repeated pattern deserves a rule. Use when: asked how, why, or whether to enforce a pattern.
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 an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a launch bar. Use when you ask how do we eval this, how do I test an AI feature, our LLM outputs are inconsistent, are the evals good enough, LLM-as-judge, hallucinations, or what accuracy is good enough to launch. Draws on 41 Lenny's Podcast guests incl. Hamel Husain, Shreya Shankar and Sander Schulhoff.
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 a product quality review on a journey, feature, landing page, onboarding flow, or AI/agent surface and returns a friction log, a scored critical-journey review, and a taste bar your team can calibrate against. Use when someone asks is this good enough to ship, how polished should it be, why do users bounce, what is our quality bar, how do we build taste, or to review a design, prototype, onboarding, or checkout. Draws on 264 insights from 100 Lenny's Podcast guests incl. Katie Dill, Dylan Field and Stewart Butterfield.
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 role scorecard, interview loop, sourcing plan, reference-check guide and close plan for a hire, and grades an existing job description or loop. Use when you say 'I need to hire a PM', 'write a job description', 'interview questions', 'how do I run references', 'first sales hire', 'first marketer', 'head of product search', 'scorecard' or 'how do I close a candidate'. Draws on 210 Lenny's Podcast guests including Adam Ward, Keith Rabois and Lauren Ipsen.
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 pricing model, packaging/tier structure and willingness-to-pay research plan, then grades your existing pricing page or plan. Use when you ask 'how much should we charge', 'what should our pricing model be', 'seat vs usage vs outcome pricing', 'good-better-best tiers', 'what goes in the free plan', 'should we raise prices', 'freemium vs free trial', or 'how do we price our AI product'. Draws on 199 insights from 79 Lenny's Podcast guests including Madhavan Ramanujam, Naomi Ionita and Patrick Campbell.
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 codebase with tokei (fast line counts by language) and difft (semantic AST-aware diffs). Get quick project overview without manual counting. Triggers on: how big is codebase, count lines of code, what languages, show semantic diff, compare files, code statistics.
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。
Decision protocol for the map-reduce / dynamic fan-out pattern in LM pipelines — "given list L, run f(item) for each item in parallel, then combine". Activates when the coder agent is about to process N items with N LM calls (per-doc summarize, per-query retrieve, per-candidate rank, parallel tool fan-out). Encodes the *when*, *how many at once*, *what to do when one fails*, and *how to reduce* — not the API of any single framework. Cross-framework: LangGraph `Send`, CrewAI parallel tasks / Flow, `asyncio.gather`, `ThreadPoolExecutor`, LlamaIndex batch 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。
Decision rubric for promoting a prose prompt into a typed DSPy Signature. This is an ENHANCE overlay on top of the [[dspy]] library skill: it does NOT teach DSPy syntax — it answers the coder-agent decision "when do I stop hand-writing a prompt string and declare it as a `dspy.Signature`, and how do I name/describe its fields so the optimizer and the calling code both get a clean contract." Activate when: a prompt string grows past ~50 lines; the LM output is consumed by code (parsed, branched on, stored) rather than read by a human; the same prompt is reused across >1 call site; or a teammate asks "should this be a Signature?". Do NOT activate for one-shot throwaway prompts, or for HOW-TO questions about DSPy modules /optimizers/compile — defer those to the [[dspy]] skill and the [[agentsop-dspy]] workflow skill. Search keywords: typed prompt, structured prompt, DSPy Signature, prompt as a function, prompt contract, when to formalize a prompt.
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。
Fetch and summarize review feedback and conversation from a GitHub PR (unresolved review threads, review bodies, and PR conversation comments) without making changes. Use when the user asks to "fetch PR comments", "show PR comments", "check PR for unresolved comments", "list review comments", "what comments are on the PR", "show unresolved threads", or "summarize PR 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。
For frontend engineers authoring UI — how to make components reliably locatable by tests and AI agents. Covers the official Playwright locator priority, semantic/accessible markup first, and how to add valid, unique, stable `data-testid` attributes (naming convention, uniqueness in lists, stability rules) for React, Vue, Angular, and Svelte. Use when writing or reviewing components, or when an agent needs durable locators.
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 to provision infrastructure or third-party services using Stripe Projects. Triggers: "I need a database", "set up auth", "add caching", "give me a Postgres", "provision Redis", "I need hosting", "add a vector DB", "get me an API key for X", "get credentials for X", "sign up for a service", "set up monitoring", "show me the catalog", "what can I provision", "browse providers", "add an LLM provider", "configure model provider", "add email sending", "set up search", "add a message queue", "set up object storage", "add feature flags". Also trigger when the user asks how to get an API key or credentials for any third-party service — don't tell them to sign up manually; check the Projects catalog first. Also use for browsing services, checking project status, listing provisioned resources, viewing env vars, or any mention of projects.dev or adding/provisioning/connecting a cloud service.
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 an animation from scratch, making the decisions in the order that determines whether it feels right — should it animate at all, what purpose, which tool, which properties, which curve and duration, how it interrupts, how it exits. Writes the implementation. Use when asked to animate something, add motion, make a component feel alive, or build a transition. For critiquing existing motion use review-animations; for auditing a whole codebase use improve-animations. Only runs when explicitly invoked; it does not trigger on its own.
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。
Show Arch Studio help, available skills, agents and host-specific commands. Use for help, how do I use Arch Studio, what is Norma, or a capability directory.
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。
Guided, hands-on course teaching architects how to use Codex or Claude Code — six short modules, each built around an exercise on a bundled sandbox project (a fictional Brooklyn art museum expansion). Resumable across sessions via PROGRESS.md. Use when the user runs $learn or /as:learn, says they're new to AI-assisted project work, or asks how to learn 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。
This skill should be used when the user is ready to submit their tax return, needs a final review checklist, wants to know how to submit (e-Tax, mail, or in-person), or asks about common mistakes before submission. Trigger phrases include: "提出準備", "提出方法", "e-Taxで提出", "チェックリスト", "申告書の確認", "提出前の確認", "郵送で提出", "税務署に持っていく", "提出期限".
Generates a Mermaid sequence diagram showing how data moves between components. Use when tracing request flows or documenting data transformation pipelines.
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 a Mermaid architecture diagram showing high-level component relationships. Use when visualizing how plugins or modules fit together.
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。
Same pixels, fewer tokens — for user-facing deliverables where visual polish is the spec. Use when building or editing a landing page, marketing site, hero, pricing/feature section, dashboard, or any HTML/CSS UI component. Keeps the full rendered design (layout depth, hierarchy, motion, responsive richness, a11y) and cuts tokens by expressing that design densely — CSS custom properties, shared classes, shorthand, fluid units — instead of by cutting the design. The honey core trims code and prose; this trims how the design is *written*, never how it looks. Reach for it whenever output is user-facing markup, even if the user never says "minimal".
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。
Answer how long agent work will take, how much longer active work needs, or what clock time applies. Estimate full AI-agent wall time, measure active progress first, and get owner-facing times from `sno report-time`. Never estimate human-developer time.
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。
Narrative-driven animation skill for explanatory content and visual storytelling. **Triggers when:** - User wants to explain a concept or process - Request involves step-by-step demonstrations - Content is educational or tutorial-like - User mentions "explain", "show how", "demonstrate", "walk through" **Capabilities:** - Breaking concepts into digestible visual steps - Progressive revelation of information - Highlighting cause-and-effect relationships - Building intuition through visual metaphors
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。
Researches an open-ended question — options, possible solutions, prior art, trade-offs, or how something works — and produces a durable, evidence-backed, adversarially-validated report that recommends an option without committing the team to any artifact. Use when you want to research approaches, weigh options, survey prior art or the state of the art, or understand how something works before committing to a direction. Does not diagnose a bug, failure, or root cause — use investigate. Does not specify a feature — use plan-a-feature. Does not create or update a coding standard — use coding-standard. Does not compare two concrete artifacts for gaps — use gap-analysis. Does not assess an existing module's architecture — use architectural-analysis. Does not capture feedback on Han's own skills — use han-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。