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cccskills

「scratch」の検索結果

550 件 ・ 関連度順

概要と使いどころ

Improve an open-source GitHub skill and open a friendly suggestion PR upstream: fork, run skill-creator's retrofit, attach asm eval before/after metrics. Don't use for local-only skills, authoring from scratch, bulk repos, or registry publish.

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。

luongnv89/asm9552026年10月13日 更新

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

freestylefly/wesight9482026年10月2日 更新

Build a complete design system from scratch. Competitive research via web search and browse. SAFE/RISK breakdown of choices. Self-contained HTML preview page. Outputs DESIGN.md as project design source of truth.

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。

paperclipai/companies9202026年3月24日 更新

Create agent company packages conforming to the Agent Companies specification (agentcompanies/v1). Use when a user wants to create a new agent company from scratch, build a company around an existing git repo or skills collection, or scaffold a team/department of agents. Triggers on: "create a company", "make me a company", "build a company from this repo", "set up an agent company", "create a team of agents", "hire some agents", or when given a repo URL and asked to turn it into a company. Do NOT use for importing an existing company package (use the CLI import command instead) or for modifying a company that is already running in Paperclip.

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。

paperclipai/companies9202026年3月24日 更新

Generate validated AWS architecture diagrams as draw.io XML using official AWS4 icon libraries. Use this skill whenever the user wants to create, generate, or design AWS architecture diagrams, cloud infrastructure diagrams, or system design visuals. Also triggers for requests to visualize existing infrastructure from CloudFormation, CDK, or Terraform code. Supports two modes: analyze an existing codebase to auto-generate diagrams, or brainstorm interactively from scratch. Exports .drawio files with optional PNG/SVG/PDF export via draw.io desktop 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。

awslabs/agent-plugins9182026年10月10日 更新

bootstrap

無料

Use when the user has nothing — no traces, no labels, no eval set — and needs to build a v0 evaluation from scratch. Also use when the user says "I need to start evaluating my app but don't know where to begin," "I want to set up eval for a new product," or has just identified failure modes and needs to turn them into principles. Outputs a v0 grader in 30 minutes using OpenJudge SimpleRubricsGenerator, plus a roadmap to reach calibrated evaluation.

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。

agentscope-ai/OpenJudge8742026年9月11日 更新

When the user wants to edit, review, or improve existing marketing copy, or refresh outdated content. Also use when the user mentions 'edit this copy,' 'review my copy,' 'copy feedback,' 'proofread,' 'polish this,' 'make this better,' 'copy sweep,' 'tighten this up,' 'this reads awkwardly,' 'clean up this text,' 'too wordy,' 'sharpen the messaging,' 'refresh this content,' 'update this page,' 'this content is outdated,' or 'content audit.' Use this when the user already has copy and wants it improved or refreshed rather than rewritten from scratch. For writing new copy, see copywriting.

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。

Nexus-JPF/note-companion8702026年10月13日 更新

Build VS Code extensions from scratch or convert existing JS/React/Vue apps. Supports commands, webviews (React/Vue), custom editors, tree views, and AI agent integration via file-bridge IPC. Use when user wants to create a VS Code extension, convert a web app to an extension, add webviews or custom UIs to VS Code, implement tree views, build custom file editors, integrate with AI agents, or package/publish extensions (.vsix).

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。

lawve-ai/awesome-legal-skills8642026年10月3日 更新

Panel structure design, firm selection criteria, right-sourcing analysis, and coverage gap assessment for in-house legal teams. Build panel frameworks from scratch or formalise existing informal arrangements. Define weighted selection criteria for firm evaluation. Run right-sourcing analysis (ABC tiering) to identify work sent to expensive providers that doesn't require that level of resource. Assess existing panels for practice area, geographic, and capability gaps. Trigger on: 'design our panel', 'how many firms do we need', 'panel structure', 'firm selection criteria', 'which firms should we use', 'right-sourcing', 'are we sending work to the right firms', 'panel gaps', 'too many firms', 'consolidate our panel', 'we need a firm for', 'preferred provider', 'panel tiers', 'do we need BigLaw for this', 'convergence', 'D&I panel targets', 'how do we choose firms'.

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。

lawve-ai/awesome-legal-skills8642026年10月3日 更新

skillify

無料

When you want to create, adapt, or update an Agent Skill (Claude Code, Codex, Cursor, and other hosts) in one of your repos (listed in ~/.config/makerskills/skillify/repos.yaml; defaults to makerskills). Modes — CREATE (from chat, video, dump, or scratch) turns a workflow into a new skill. ADAPT ports an external skill with keep/adapt/add classification, license check, and attribution. UPDATE improves existing skills from learnings with cross-skill propagation, memory-vs-skill triage, and semver. Checks new skills for host portability. Triggers on "/skillify," "create a skill," "make this a skill," "skill from this chat," "adapt this skill," "port this skill," "fork this skill," "update X skill," "apply this to the relevant skills," "propagate this learning," "improve [skill]," "fix [skill]." Part of the -ify trifecta (skillify / toolify / loopify).

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。

coreyhaines31/makerskills8562026年10月9日 更新

Stage exploration before instruction on complex problems. The learner produces two attempted approaches before consolidation — which builds on those attempts, not from scratch. Use for genuinely hard problems where struggle produces deeper learning.

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。

GarethManning/education-agent-skills8532026年8月29日 更新

Require the learner to explain a concept in their own words before the AI evaluates or extends it. Ensures the AI works from the learner's understanding rather than providing an explanation from scratch.

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。

GarethManning/education-agent-skills8532026年8月29日 更新

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

countbot-ai/CountBot7822026年10月11日 更新

aeon

無料

Set up and run an Aeon agent instance - get started from scratch, pick which skills to turn on or install more from packs, reschedule or change what runs, edit what an existing skill does, fix a skill that isn't firing, set the STRATEGY.md north star and soul/ voice, turn a coding-agent chat into a scheduled Aeon skill, and mine past coding-agent conversations for recurring work worth automating as a skill. Use when the user mentions Aeon, aeon.yml, an Aeon skill / instance / routine / pack, asks to schedule, enable, edit, or debug an agent that runs on a cron, or asks what of their repeated/manual work Aeon could take over.

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。

aeonfun/aeon7732026年10月12日 更新

Generate, simulate, audit, and deploy a Uniswap v4 hook + test pool from a brief, on any Uniswap v4 chain (every testnet and mainnet) - pre-audited templates or a from-scratch freeform hook (flags auto-derived; static audit + dangerous-pattern scan + a behavioral forge test + fork sim gate the deploy). Dry-run by default; explicit arm: to broadcast; testnet default, mainnet behind a double opt-in; records the deploy to main. Every deployed hook inherits a mandatory 10 bps AeonFee protocol fee.

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。

aeonfun/aeon7732026年10月12日 更新

Amazon listing builder and optimizer for sellers. Two modes: (A) Create — build keyword-optimized listings from scratch using keyword lists + product characteristics + AI copywriting, (B) Optimize — audit existing listings, find keyword gaps, score across 8 dimensions, and rewrite with missing keywords. Integrates with amazon-keyword-research for keyword input. Works on 12 Amazon marketplaces. No API key required. Use when: (1) creating a new Amazon listing from keywords, (2) auditing an existing listing for SEO and conversion, (3) checking keyword coverage in title/bullets/description, (4) generating listing copy with target keywords and tone, (5) comparing listings against competitors, (6) preparing a listing for launch or relaunch.

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。

nexscope-ai/Amazon-Skills7592026年8月26日 更新

Amazon PPC campaign builder and optimizer for sellers. Two modes: (A) Build — design a complete campaign structure from scratch with keyword groupings, bid calculations, and negative keyword lists, (B) Optimize — audit existing campaigns using search term reports, identify keyword funnel opportunities, calculate bid adjustments, and generate a week-by-week action plan. Integrates with amazon-keyword-research for keyword input. No API key required. Use when: (1) setting up Amazon PPC campaigns for a new product, (2) auditing existing campaign performance and ACoS, (3) optimizing keyword bids and negative keywords, (4) building Auto/Manual/Exact campaign structures, (5) analyzing search term reports for opportunities, (6) calculating break-even ACoS and target ACoS, (7) scaling profitable campaigns to Sponsored Brands or Display.

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。

nexscope-ai/Amazon-Skills7592026年8月26日 更新

Writes, improves, or rewrites Seedance 2.0 prompts that TRANSFORM footage the user already has (video-to-video), rather than building a scene from scratch. Use whenever a real clip is the starting point and they want to: add a VFX element (set a head or hair on fire, transform a hand, make a limb invisible), swap the environment around a preserved subject (desert, clouds, lava, a neon city), drop a giant photoreal creature behind or onto a subject/landmark, relight or regrade so subject and added elements read as one shot, sync a crash-zoom or push-in to a spoken line or timecode, or generate a matching transformed start frame to animate from. Also use when they paste such a prompt and ask to change its lighting, timing, creature, or runtime, or say 'make a Seedance prompt for this video' with a clip attached. This is the video-to-video specialization; for a brand-new scene from image references with no source clip to preserve, higgsfield-seedance applies 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。

OSideMedia/higgsfield-ai-prompt-skill7362026年9月27日 更新

Plan a complete affiliate funnel from research to revenue. Triggers on: "plan my affiliate funnel", "create a funnel strategy", "affiliate business plan", "how to start affiliate marketing", "full funnel roadmap", "plan from scratch", "week by week affiliate plan", "chain skills together", "build my funnel", "affiliate marketing roadmap", "step by step affiliate plan", "onboarding plan".

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。

Affitor/affiliate-skills7102026年9月15日 更新

Scaffolds a structured investigation in scratch/ for empirical research and documentation. Use when the user says "start an investigation" or wants to: trace code paths or data flow ("trace from X to Y", "what touches X", "follow the wiring"), document system architecture comprehensively ("document how the system works", "archeology"), investigate bugs ("figure out why X happens"), explore technical feasibility ("can we do X?"), or explore design options ("explore the API", "gather context", "design alternatives"). Creates dated folder with README. NOT for simple code questions or single-file searches.

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。

talmolab/sleap6182026年10月13日 更新

xlsx

無料

Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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。

ECNU-ICALK/AutoSkill6002026年5月10日 更新

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, update or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

ECNU-ICALK/AutoSkill6002026年5月10日 更新

Creates a lesson plan, student-facing materials, and observation template. Load this skill BEFORE asking the teacher any clarifying question about grade, subject, topic, standard, or timing. Use when a K-12 teacher needs a math, ELA, science, or social studies lesson built from scratch — even if grade, subject, or topic isn't yet stated. Do NOT load for grading, a rubric, assessment feedback, a quiz, or a standards lookup — answer those directly. Triggers on explicit requests (lesson plan, mini-lesson, unit plan, daily plan) and implicit teacher intent: "I'm teaching long division to 5th graders," "need to teach photosynthesis tomorrow." Core signal: teacher needs new instructional content created. A new lesson that asks for differentiated, tiered, or leveled materials is still ONE planning request — this skill produces those materials inside the lesson package; do not also invoke k12-lesson-differentiation. Not for differentiating an existing lesson (use k12-lesson-differentiation) or passage rewrites.

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。

anthropics/k12-teacher-skills5622026年9月2日 更新

Adapts an existing K-12 lesson (math, ELA, science, or social studies) for students at different proficiency levels (below / at / above grade level). Load this skill BEFORE asking the teacher any clarifying question about the lesson, tiers, or student levels. Triggers on explicit asks to differentiate, tier, or scaffold a lesson, and on implicit signals like "my students are at different levels". Produces 1 teacher-facing differentiation plan + 3 student-ready tier documents as editable Word documents in a single output turn, rendered from one material-source JSON via bundled scripts (shared content is written once so tiers cannot drift). Uses the Learning Commons Knowledge Graph when connected; works without it. This skill adapts a lesson the teacher brings or names. Not for creating a new lesson from scratch — a new-lesson request that asks for differentiated or leveled materials is k12-lesson-plan-creation's job, one package. Not for grading, rubrics, assessment feedback, or quizzes.

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。

anthropics/k12-teacher-skills5622026年9月2日 更新