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cccskills

「cohere」の検索結果

164 件 ・ 関連度順

概要と使いどころ

Design and implement game HUDs, menus, icons and portrait systems from visual proposals through reusable engine assets and input checks. Use when a game interface needs a coherent visual and behavior contract.

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。

witnesstodark/mr-mak-workspace4232026年10月11日 更新

Verify implementation matches change artifacts. Use when the user wants to validate that implementation is complete, correct, and coherent before archiving.

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。

Asymmetric-al/core3812026年10月12日 更新

Update an OpenSpec change by revising its existing planning artifacts and keeping them coherent with one another. Use when the user wants to revise a change's plan, fold new decisions into it, or reconcile its artifacts after an edit. Never edits 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。

Asymmetric-al/core3812026年10月12日 更新

Turn Chinese classical poems and ci into coherent vertical Chinese-art videos with poem-driven scene grouping, GPT ImageGen stills, Docker-only Gemini I2V, retained model-generated ambience, Gemini sparkle-watermark cleanup, brush-calligraphy captions revealed character by character, optional local BGM mixing, stitching, and final-frame QA. Supports verse-driven variation across ink landscape, gongbi bird-and-flower, colored figure-and-horse painting, blue-green landscape, xuan paper, silk, and related Chinese visual languages. Use when users ask for 古诗词动态视频、诗词逐句或两句一景、国风视频、毛笔字逐字出现、整首诗拼接成片,or want the established 月落乌啼霜满天 workflow applied to another poem.

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。

Mr-funny/hbg-classical-poem-silk-video3712026年8月3日 更新

Provides chunking strategies for RAG systems. Generates chunk size recommendations (256-1024 tokens), overlap percentages (10-20%), and semantic boundary detection methods. Validates semantic coherence and evaluates retrieval precision/recall metrics. Use when building retrieval-augmented generation systems, vector databases, or processing large documents.

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。

giuseppe-trisciuoglio/developer-kit3572026年9月10日 更新

Reconstruct and report long-running or multi-turn research, architecture questions, reviews, decisions, completion results, and status as a clear, self-contained brief. Use when a reader must re-enter earlier context, understand the real question and its relationships, distinguish verified facts from judgment and open evidence, or make a decision without reconstructing the work log. Quote the relevant original user wording before substantive analysis, keep one coherent main line, use spatial diagrams when relationships matter, and finish with an explicit decision boundary and practical next step.

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。

shareAI-lab/lab-skills3152026年9月16日 更新

Write model-native Seedance 2.0 video prompts from text, images, video, or audio references. Use for text/image generation, multimodal reference, video editing, extension, track fill, or combined tasks that need stable subjects, explicit asset roles, coherent event order, camera, sound, visible text, and a 4–15 second feasibility check.

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。

T8mars/minimax-h3-prompt-skill-T82852026年10月11日 更新

Combines search results from multiple sources into coherent, deduplicated answers with source attribution. Handles confidence scoring based on freshness and authority, and summarizes large result sets effectively.

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。

w95/awesome-claude-corporate-skills2462026年2月27日 更新

Conduct a structured literature review on a given topic by defining a search strategy, applying inclusion and exclusion criteria, extracting key findings, and synthesizing results into a coherent academic review. Use when the user requests literature review or provides relevant inputs for this workflow.

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。

seb1n/awesome-ai-agent-skills2112026年8月10日 更新

Think and work like an expert Embedded Systems Engineer. Use when a task calls for Embedded Systems Engineer judgment. Reasons from hardware timing, interrupt latency, memory maps, and deterministic WCET resource bounds through DWT CYCCNT and Saleae logic-analyzer timing proofs, SWD/JTAG (J-Link/OpenOCD) with CFSR/HFSR/BFAR fault decode, FreeRTOS/Zephyr respecting configMAX_SYSCALL_INTERRUPT_PRIORITY, MISRA C:2012 and ISO 26262 ASIL discipline, Nordic PPK2 power profiling, and MCUboot signed OTA while treating priority inversion, Cortex-M7 uncached-DMA D-cache incoherence, CAN bus-off, I2C NACK storms, and brownout-during-flash-write NVS corruption as first-class failure modes.

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/scientific-agents2052026年10月3日 更新

Think and work like an expert Computer Architecture Researcher. Use when a task calls for Computer Architecture Researcher judgment. Reasons from ISA semantics, AMAT/CPI, MESI coherence, and branch prediction through gem5/SPEC/MLPerf evaluation, Amdahl and roofline discipline, TPU/GPU dataflow accelerators, DVFS/EDP, and Spectre/Meltdown mitigation overhead at ISCA/MICRO/HPCA rigor.

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/scientific-agents2052026年10月3日 更新

Think and work like an expert Bayesian Statistician. Use when a task calls for Bayesian Statistician judgment. Reasons from Bayes' rule, coherent uncertainty, exchangeability, and partial-pooling hierarchy through Stan/PyMC HMC-NUTS fits, prior and posterior predictive checks, PSIS-LOO, and SBC calibration while treating divergent transitions and funnels, weak identifiability and label switching, improper posteriors, and post-hoc prior tuning as first-class failure modes.

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/scientific-agents2052026年10月3日 更新

Grounded in first principles, rigorously examine and refine a user's plan, task, decision, goal, strategy, proposal, or idea through structured, progressively deeper questioning, in order to bridge the gap between the User and the Agent. Use when the user explicitly requests grilling, challenge, pressure-testing, cross-examination, red-team review, pre-mortem analysis, or a decision audit. The goal is to uncover unclear objectives, hidden assumptions, contradictions, weak evidence, missing information, overlooked constraints, dependencies, risks, trade-offs, failure modes, and misalignment between intended outcomes and likely real-world results. Begin by establishing a shared understanding of the user's actual intent, goals, constraints, and success criteria. Ask focused, high-leverage questions rather than broad or repetitive ones. Adapt each question based on previous answers, probing deeper where uncertainty, unsupported assumptions, or strategic weaknesses remain. Regularly summarize the current understanding of the user's intent and position to confirm alignment, expose misunderstandings, and refine the problem or goal definition. Distinguish facts, assumptions, hypotheses, and unknowns. Challenge reasoning rigorously while remaining constructive, respectful, and solution-oriented. Continue until the reasoning is internally coherent, evidence-aware, constraint-conscious, risk-assessed, and translated into a clearer, more actionable goal, decision, or plan. Ultimately, achieving the super-alignment.

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。

Inference1/clarify-intent-and-establish-shared-understanding2042026年10月10日 更新

Plan and scope production work with Odyssey's real-time interactive video world models (odyssey.ml — Odyssey-1/Odyssey-2/Starchild-1/Agora-1). Use when a request involves generating video that a user steers live with keyboard, text, speech, or controller input (streamed frames that respond in the moment), or when someone must decide between Odyssey-style interactive generation and offline clip generators (Sora/Veo/Kling) or downloadable 3D / game engines. Covers what is verified versus announced, current access routes, latency and coherence limits, feasible-now versus speculative use cases, pricing/access terms, and content/rights considerations. This is a fast-moving research-stage product; the skill teaches honest scoping, not a promise of production reliability.

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。

calesthio/generative-media-skills2022026年7月14日 更新

Map user missions from trigger to value moment, organizing features into coherent paths during PRD v0.4 User Journeys. Triggers on requests to map user journeys, define user flows, describe how users accomplish goals, or when user asks "map user journeys", "define user flows", "user missions", "how do users accomplish X?", "journey mapping", "what steps do users take?", "pain to value flow". Consumes PER- (Persona Definition), FEA- (Feature Value Planning), KPI- (Outcome Definition). Outputs UJ- entries with step flows, pain points, and value moments. Feeds v0.4 Screen Flow Definition.

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。

mattgierhart/PRD-driven-context-engineering1812026年8月31日 更新

Run the evidence loop of one long-horizon GPU kernel optimization episode. Use this skill to reconstruct the incumbent, profile and localize a bottleneck, research progressively, plan one coherent direction, implement and repair, validate development correctness and performance, and record every decisive experiment in the episode journal.

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。

alibaba/atrex-kernel-agent1742026年10月12日 更新

The craft of weaving story into interactive systems where the player is both audience and author. This skill covers the unique challenges of game narrative: branching structures that respect player agency, environmental storytelling that rewards exploration, dialogue systems that feel alive, and the delicate balance between authored experience and emergent narrative. Unlike linear media, games don't tell stories TO players - they create the conditions for stories to emerge WITH players. The narrative designer's job is to build the scaffolding that supports infinite player-authored moments while maintaining coherent themes and emotional arcs. This skill synthesizes lessons from Disco Elysium's internal monologue as gameplay, Hades' death-as-narrative-engine, interactive fiction's branching mastery (Inkle, Twine), and procedural narrative pioneers like Dwarf Fortress. It addresses ludonarrative harmony, bark systems, cinematics that respect agency, and the "and therefore" test that separates plot from story. Use when "narrative design, game story, game writing, dialogue system, branching narrative, player choice, environmental storytelling, bark system, quest design, lore delivery, ludonarrative, interactive fiction, inkle, twine, dialogue tree, player agency, cinematic design, voice direction, localization, procedural narrative, narrative, game-writing, dialogue, branching, player-agency, environmental-storytelling, quest-design, voice-acting, localization, interactive-fiction, procedural-narrative, ludonarrative" mentioned.

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。

omer-metin/skills-for-antigravity1652026年1月22日 更新

The craft of designing icons that communicate instantly across cultures, contexts, and scales. Icon design bridges semiotics, cognitive psychology, and visual craft to create symbols that users understand without thinking. Great icons are invisible in the best way - they convey meaning so naturally that users never pause to decode them. This skill covers icon grid systems, optical alignment, stroke consistency, metaphor selection, scalability across sizes, SVG optimization, and icon set coherence. The best icon designers understand that icons are a visual language - each icon must speak the same dialect while carrying its own distinct meaning. Use when "icon, iconography, symbol, glyph, icon set, icon library, pictogram, svg icon, icon grid, icon pack, feather icons, lucide, phosphor, heroicons, icon system, icon style, icons, iconography, svg, symbols, glyphs, pictograms, ui-icons, icon-set, visual-design, design-system" mentioned.

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。

omer-metin/skills-for-antigravity1652026年1月22日 更新

World-class character and art style consistency for AI-generated images and videos - ensures visual coherence across series, maintains character identity, and provides rigorous QA before deliveryUse when "character consistency, art style, same character, consistent character, visual continuity, series, turnaround sheet, character sheet, reference image, character bible, style guide, anime character, consistent look, face consistency, outfit consistency, lora training, ip-adapter, flux kontext, visual qa, art quality, generation review, style drift, character drift, character-consistency, art-style, visual-qa, ai-art, image-generation, video-generation, anime, illustration, lora, ip-adapter, flux, midjourney, stable-diffusion" mentioned.

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。

omer-metin/skills-for-antigravity1652026年1月22日 更新

The orchestration layer for AI-native creative production. This skill coordinates multiple AI tools—video, image, audio, digital humans, effects—into cohesive campaigns, productions, and creative systems. As AI tools proliferate, the challenge shifts from "can we create this?" to "how do we orchestrate these capabilities into something coherent?" The AI Creative Director thinks in systems, not tools. In pipelines, not one-offs. In brand consistency across AI-generated assets. This is where creative vision meets technical orchestration. The AI Creative Director doesn't just use AI tools—they compose them into creative instruments that produce at scales and speeds previously impossible. Use when "AI creative director, orchestrate AI, AI campaign, multi-tool, AI workflow, AI pipeline, coordinate AI, AI production, AI creative system, full AI production, AI at scale, orchestration, creative-direction, ai-production, workflow, pipeline, multi-tool, scale, quality-control" mentioned.

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。

omer-metin/skills-for-antigravity1652026年1月22日 更新

Guides Lovart Agent from one visual reference to a coherent brand system, campaign assets, and packaging concepts through a gated creative-direction workflow.

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。

amirmushichge/brand-system-skill1382026年8月12日 更新

Critique a screen's colour usage — contrast ratios, palette coherence, semantic meaning, and colour accessibility.

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。

Infrasity-Labs/dev-gtm-claude-skills1362026年6月29日 更新

capture

無料

Captures and organizes chaotic brain dumps into a structured, actionable system with zero information loss. Use this skill whenever the user says 'capture this', 'brain dump', 'let me dump some ideas', 'I've got a bunch of thoughts', 'here's everything on my mind', 'idea dump', 'let me get this out of my head', 'I need to organize my thoughts', 'here's what I'm thinking', or any variation where someone is unloading a messy stream of ideas, tasks, thoughts, and plans wanting them turned into something coherent. Also trigger when the user pastes or dictates a long, unstructured block of mixed ideas — even without the exact phrase — the intent is the same. Fast-to-action by design: no upfront intake. Output is four sections (Projects/Ideas, Tasks, Connections, How I Can Help) ending with a directive question. Asks at most one mid-organization clarifying question when a single item is genuinely ambiguous between task and project.

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。

Infrasity-Labs/dev-gtm-claude-skills1362026年6月29日 更新

Define coherent motion timing and rhythm.

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。

TheGoat395/Codex-Skills1272026年9月11日 更新