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概要と使いどころ
Write rationale connecting decisions to user needs, business goals, and principles. Use when a decision needs defending in writing. For a live conversation, use `design-negotiation`.
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Advocate for design quality, scope, and timeline with partners and leadership using evidence and shared goals. Use in the conversation itself. For the commercial vocabulary behind it, use `business-design` (ux-strategy).
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Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
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Have a fast, conversational analysis with the AWS DevOps Agent. Use for cost optimization, architecture review, topology mapping, knowledge / runbook discovery, security audits, dependency questions, and quick diagnostics — anything that needs a 5-30 second answer rather than a 5-8 minute deep investigation. Trigger words include cost, optimize, review, architecture, topology, what runbooks, show me, compare, audit, what if.
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Authors and edits AWS Step Functions state machines: writes Amazon States Language (ASL) in JSONata, and chooses and structures state types (Task, Choice, Map, Parallel, Pass, Wait, Succeed, Fail). Covers ASL syntax, JSONata data transformation and variables, Retry/Catch error handling, service integrations (.sync, waitForTaskToken callbacks), Distributed Map for large-scale S3/CSV processing, saga/compensation patterns, Standard vs Express workflow choice, TestState API unit testing, and migrating state machines from JSONPath to JSONata. Use when the user is building, authoring, debugging, or migrating a Step Functions state machine or ASL definition, or orchestrating multi-step workflows with branching, retries, or human-approval callbacks, even if they don't say 'Step Functions.' Do NOT use for general Lambda function code, API Gateway, EventBridge wiring, or SAM/CDK application packaging.
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Org-grade attack-surface mapping: given a company's legal identity, discover its ENTIRE owned internet footprint — corporate family -> owned domains -> owned netblocks/ASN -> live assets — with attribution discipline, not just DNS breadth. The org-first attribution pyramid (legal entity -> LEI/registration -> corporate family -> owned domains -> owned netblocks/ASN -> live assets). Corporate-identity resolution via the GLEIF LEI API (legal name -> LEI, exact-LEI direct-children expansion, downward-only depth-capped BFS, NEVER a name re-resolution), SEC-EDGAR full-text search + Exhibit-21 subsidiary entity names, OpenCorporates entity corroboration, Wikidata SPARQL corporate graph (P856/P355/P749/P1830). Domain attribution via reverse-WHOIS (WhoisXML preview-then-purchase quota guard, SecurityTrails associated-domains — both paid), crt.sh O= certificate-transparency organization pivot (keyless), infrastructure correlation (shared NS/MX/SaaS-TXT, netblock membership, reverse-DNS PTR), and the independent-evidence combiner (1-prod(1-w_i), rule of three, OwnerTier NONE/WEAK/MODERATE/STRONG/CONFIRMED) — discover-only `related:` candidates are NEVER auto-scanned. Netblock/ASN attribution via org-first RIR queries (ARIN Whois-RWS org-handle search, RIPE DB organisation + inverse-org search) that recover 'dark netblocks' with no DNS link to the seed, ASN discovery (RIPEstat + BGPView union), the HYPERSCALER-SCOPE GUARD (never attribute a whole AWS/GCP/Azure/Cloudflare announced range to a tenant — keep only the seed-containing block, tag shared_hosting_cdn), and org-identity-seeded internet-scan-index queries (Shodan/Censys/ZoomEye/FOFA/BinaryEdge org: filters + an always-on keyless crt.sh fallback). Promote-to-scan triage ranks forgotten discover-only netblocks by remote-access exposure (gateway-vendor/KEV/control-plane/datastore port scoring) into an operator queue. Attribution confidence rubric + anti-patterns (namesake grafting via GLEIF name re-resolution, single-signal ownership, hyperscaler over-attribution, privacy-WHOIS pivot poisoning, RIR org-name collisions). Passive/keyless-first OSINT only — every paid-key dependency is enrichment on top of a keyless core, never a hard requirement. Use when mapping an organization's full corporate-family internet footprint, resolving a legal entity to its LEI/subsidiaries, discovering domains/netblocks/ASNs an org owns beyond its one seed domain, auditing M&A/shadow-IT sprawl, or scoping an engagement that starts from a company NAME rather than a domain.
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Compare multiple job offers side-by-side with total compensation analysis
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Lark/Feishu channel output rules. Always active in Lark conversations.
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 aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
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开发、维护、分发和验证 DeepSeek Harness (DSH) 插件的执行型 Skill。覆盖 host/client 形态判断、bundle/profile 契约、Service 与函数插件、工具、HTTP、持久化、slot、Conversation Node、客户端构建、HMR、GitHub 安装和真实组合验证。
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Analyze tau2-bench task export files to identify exactly where and why tasks failed. Map failures to specific conversation rounds, show root causes, check whether relevant documentation was available, and cite sources. Use this skill whenever you need to debug a tau2-bench evaluation, understand why an agent made wrong decisions, identify missing knowledge, or review task performance—especially when context length, eligibility criteria, or policy compliance might be at fault.
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Verifies that work is actually complete before it is claimed to be — running the checks, reading the output, and confirming the original request was satisfied rather than approximated. Use this before saying something is done, fixed, or passing; before committing or opening a pull request; and whenever a claim of success has not been backed by command output.
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Designs quotas, territories and commission plans that produce the behavior the business needs — sizing territories against real potential, setting quotas people can hit often enough to believe in, choosing what to pay on, handling accelerators, draws, clawbacks and disputes, and changing a plan without destroying trust. Use this to build or fix a comp plan, allocate territories, work out why reps are chasing the wrong deals, or plan a mid-year change.
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Handles the difficult human situations — grievances, complaints, investigations, conflict, and separations conducted properly. Use this to respond to a complaint or grievance, structure an investigation, handle a conflict between colleagues, prepare for a difficult conversation, or work out what a manager can and cannot do in a given situation.
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Builds the loop from what customers say to what gets changed — collecting feedback, distinguishing signal from noise, routing it to owners, and closing the loop back to the customer. Use this to set up a feedback program, design or interpret CSAT/NPS, decide what customer feedback deserves action, get product to act on recurring issues, or diagnose why feedback is collected but nothing changes.
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 and send sticker images in chat. Use during casual conversations, greetings, encouragement, or celebrations to make interactions more lively and engaging.
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。
Miaoda App Builder - create web apps, WeChat mini-programs, games, AI tools, SaaS products, and dashboards through natural language conversations. Full workflow from code generation to deployment.
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Rewrite drafts according to target writing style or target journal format. Triggers when user says "rewrite in XX style", "match this tone", "format for XX journal", "rewrite following this format". Input can be .docx / .md / .txt or conversation text.
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Verifies whether a scientific or biomedical claim is actually supported by the cited original papers rather than by citation drift, overstatement, selective citation, or correlation-to-causation inflation. Use this skill whenever a user wants to check whether a repeated statement, slide claim, manuscript sentence, review assertion, or “people often say” scientific conclusion is truly supported by the underlying primary literature. Always separate the claim itself, the cited paper(s), what the paper actually showed, what it did not show, and whether later retellings drifted beyond the original evidence. Never fabricate references, findings, study features, or citation chains.
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Turns your protocol and analysis workflow into publication-ready Methods text. Use when writing or revising the Methods section of a biomedical manuscript, ensuring it complies with reporting guidelines (CONSORT, STROBE, PRISMA, TRIPOD), matches what is in the Results section, and satisfies journal-specific word limits and declarations. Also triggers on "write my methods", "revise my methods section", "how to report my statistics", "what do I need to include in methods for [study type]", or "make my methods CONSORT-compliant".
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Lomb-Scargle periodogram for finding periodic signals in unevenly sampled time series data. Use when analyzing light curves, radial velocity data, or any astronomical time series to detect periodic variations. Works for stellar rotation, pulsation, eclipsing binaries, and general periodic phenomena. Based on lightkurve library.
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Compare and implement eviction policies (LRU, LFU, FIFO, S3FIFO, ARC) for bounded-capacity caches. Use when choosing or implementing an eviction policy for a buffer pool, page cache, CDN edge, or LLM KV cache, or when writing a replay simulator that supports multiple policies. Clarifies recency vs frequency semantics, queue topology, saturating counters, ghost buffers, and the second-chance rule that distinguishes modern FIFO-family policies from classic LRU.
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 dynamic-object binary masks after global motion compensation, output CSR sparse 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。
Strategy for solving constraint optimization problems on spatial maps. Use when you need to place items on a grid/map to maximize some objective while satisfying constraints.
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。