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cccskills

「sequence」の検索結果

1,196 件 ・ 関連度順

概要と使いどころ

Design a wise systems intervention from an existing analysis. Maps proposed actions against Meadows' leverage points, checks for unintended consequences, and generates alternatives.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Design a learning sequence teaching prompt quality — comparing vague vs. refined prompts to show why specificity and context transform AI output. Use when students use AI without understanding why output quality varies.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Generate a scaffolded sequence of practice problems with graduated difficulty and strategic variability. Use when creating worksheets, homework sets, or independent practice materials.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Build a complete explicit instruction sequence from teacher modelling through guided practice to independent work. Use when teaching new skills, procedures, or concepts through direct instruction.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Create an interactive digital worked example sequence with fading for online or blended delivery. Use when building e-learning modules, LMS content, or app-based instruction.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Design a sequence where students compare AI's handling of the same question across disciplines, developing a mental model of where AI is reliable vs. distorting based on knowledge type.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Design a Concrete-Pictorial-Abstract learning sequence for a mathematical concept using manipulatives. Use when teaching maths through Singapore method or when students struggle with abstraction.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Generate a cascading hint sequence for a problem type, revealing progressively without giving answers. Use when designing tutoring dialogues or scaffolded worksheets.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

sms

無料

When the user wants to plan, build, or optimize SMS or MMS marketing — including welcome flows, abandoned cart texts, post-purchase, win-back, promotional sends, or transactional/auth SMS. Also use when the user mentions "SMS marketing," "text message campaigns," "SMS sequence," "SMS automation," "abandoned cart text," "post-purchase SMS," "Klaviyo SMS," "Postscript," "Attentive," "Twilio," "A2P 10DLC," "TCPA," "SMS compliance," "short code," "toll-free SMS," "MMS campaign," "should I do SMS," or "SMS vs email." For email sequences, see emails. For SMS copy framing, see copywriting. For opt-in popups that capture phone numbers, see popups.

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。

nota-america/forgecat-agent-profiles902026年9月24日 更新

Generate Mermaid diagrams (.mmd) and export to PNG/SVG/PDF using mmdc CLI or Kroki API. USE THIS SKILL when user mentions diagram, flowchart, sequence diagram, class diagram, ER diagram, state machine, architecture, visualize, git graph, 画图, 架构图, 流程图, 时序图, 类图, ER图, 甘特图, 状态机. PROACTIVELY USE when explaining ANY system with 3+ components, API flows, authentication sequences, class hierarchies, database schemas, or state machines. Supports 17+ diagram types with fully automatic layout.

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。

Agents365-ai/365-skills842026年10月13日 更新

Optimize customer onboarding — map the activation sequence, identify drop-off points, design the aha moment, and produce the onboarding email sequence. Use when asked to "fix onboarding", "improve activation", "time-to-value is too slow", or "customers aren't getting started".

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。

tonone-ai/tonone762026年10月5日 更新

Write sales playbooks — outbound sequences, discovery call guides, objection handling scripts, and demo frameworks. Use when asked to "write a sales playbook", "build an outbound sequence", "help me handle objections", or "design a discovery call".

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。

tonone-ai/tonone762026年10月5日 更新

Build a product roadmap with sequenced bets and explicit tradeoffs. Use when asked to "build a roadmap", "prioritize the backlog strategically", "what do we build next quarter", "sequence our bets", "what should we focus on", or "product strategy for the next N months".

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。

tonone-ai/tonone762026年10月5日 更新

Causal reasoning in historical analysis. Covers distinguishing immediate from underlying causes, tracing chains of causation across time scales, identifying unintended consequences, and applying counterfactual reasoning to assess causal significance. Use when analyzing why historical events occurred, evaluating the relative weight of causes, or assessing whether outcomes were inevitable or contingent.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

Stellar structure and life cycles from birth to endpoint. Covers the Hertzsprung-Russell diagram, hydrostatic equilibrium, main-sequence physics and the mass-luminosity relation, nuclear fusion stages (pp-chain, CNO cycle, triple-alpha), nucleosynthesis, post-main-sequence evolution through red giants and the horizontal branch, and stellar endpoints — planetary nebulae, white dwarfs and the Chandrasekhar limit, supernovae, neutron stars, and black holes. Use when placing a star on the HR diagram, estimating its lifetime, predicting its fate from its mass, or teaching how a star lives and dies.

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。

Tibsfox/gsd-skill-creator712026年7月20日 更新

adaptyv

無料

Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding assays, expression testing, thermostability measurements, enzyme activity assays, or protein sequence optimization. Also use for submitting experiments via API, tracking experiment status, downloading results, optimizing protein sequences for better expression using computational tools (NetSolP, SoluProt, SolubleMPNN, ESM), or managing protein design workflows with wet-lab validation.

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。

plurigrid/asi672026年7月10日 更新

When the user wants to optimize post-signup onboarding, user activation, first-run experience, or time-to-value. Also use when the user mentions "onboarding flow," "activation rate," "user activation," "first-run experience," "empty states," "onboarding checklist," "aha moment," or "new user experience." For signup/registration optimization, see signup-flow-cro. For ongoing email sequences, see email-sequence.

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。

ComeOnOliver/skillshub652026年6月24日 更新

email

無料

Generates email sequences for different contexts. Currently supports event follow-up sequences. Produces ready-to-send emails with subject lines, body copy, and timing guidance.

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。

j1ngg/tech-marketing-framework582026年4月29日 更新

Plan and batch-produce an entire email system for a product. Maps every lifecycle touchpoint (onboarding, activation, conversion, retention, transactional, win-back), generates all emails with quality gates, outputs Loops-ready copy. Use when "create all emails", "email system", "build email sequences", "lifecycle emails", "onboarding sequence", "set up transactional emails", "plan all the emails for [product]", or any request to systematically produce a complete set of emails for a platform.

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。

cgallic/kai-cmo-harness562026年10月3日 更新

Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for custom binary or text protocol recovery, handshake reconstruction, framing, sequence control, checksums, stateful replay, and accepted-session reproduction. Use when the user asks to decode an unknown protocol, recover custom framing, build a replay harness, satisfy sequence or checksum rules, replay a captured session, or prove the smallest message order that reaches an accepted branch. 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。

zhaoxuya520/AI-Fullstack-Delivery-Workflow542026年5月19日 更新

Generates Remotion composition structure focusing ONLY on Sequence ordering, scene transitions, and duration mapping. Input is scene list with durations. Output is COMPOSITION_STRUCTURE.md with Sequence layout and timing calculations. Use when organizing scenes or when asked to "structure composition", "layout scenes", "calculate timing".

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。

ncklrs/startup-os-skills522026年2月27日 更新

Generate hand-crafted web animation patterns as self-contained HTML: typewriter/rotator effects, progress bar simulations, file review state machines, staggered reveals, terminal status displays, streaming AI-response demos, popover/dialog/toast lifecycles, Lottie orchestration, scroll-driven sequences. Behavioral animations that simulate live software. Triggers on typewriter effect, progress animation, stagger reveal, terminal animation, streaming text, AI demo animation, toast animation, data simulation, product demo animation, loading sequence, conductor motion.

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。

tdimino/claude-code-minoan412026年9月28日 更新

Compose or analyze sacred music in Hildegard von Bingen's distinctive modal style. Covers modal selection, melodic contour (wide-range melodies), text-setting (syllabic and melismatic), neumatic notation, and liturgical context for antiphons, sequences, and responsories. Use when composing a new piece in Hildegardian style, analyzing an existing chant for structure and mode, researching medieval modal music, preparing to perform or teach Hildegard's music, or setting Latin sacred texts.

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。

pjt222/agent-almanac372026年10月13日 更新

Estimate how likely a protein therapeutic is to provoke an anti-drug antibody response, and locate the sequence regions responsible. Use this skill to tile a sequence into peptides, predict class II MHC presentation across a population-representative allele panel, aggregate predicted binders into a per-region and whole-molecule risk score, compare a candidate against its closest human germline, and decide which liabilities are worth deimmunising. Also trigger on immunogenicity, anti-drug antibody, ADA, T-cell epitope, MHC class II, HLA-DRB1, NetMHCIIpan, NetMHCpan, deimmunisation, tregitope, or population coverage.

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。

K-Dense-AI/drug-discovery-agent-skills372026年10月12日 更新