「primary」の検索結果

arkcli 模型查询与基础模型服务激活能力：列出、搜索、获取火山公共基础模型详情，以及用户明确要求的开通/激活模型服务（`arkcli models activate`）；Volc 还支持 TTFT/TPOT 性能排名、延迟趋势和输入长度对比。激活已有基础模型服务不等于部署/创建 Endpoint，不得转成 `+deploy`。优先使用产品命令 `arkcli models ...`，而不是直接调用 Raw API。反触发：用户的最终目标是创建 / 部署 Endpoint 时，本 skill 承担有界的只读候选查询，owning skill 由创建路径确定：普通产品创建走 arkcli-deploy；用户显式要求 raw CRUD / CI / 无守卫的 `infer endpoint create` 走 arkcli-infer-endpoint。候选首先执行 `models search ... --size 10 --format json`；成功完整结果直接复用，空结果与捕获缺损按 reference 有界恢复，并把实时返回的 `name` 与非空 `primary_version` 组合成可直接传给 `--model` 的完整 ID，不能拉全量清单、把裸家族名当可部署 ID，或逐候选追加 `models get`。注意：查询/管理账号下自传或精调的自定义模型（`cm-xxx`）走 arkcli-custommodel。

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Detect keyword cannibalization across blog posts by extracting primary keywords from titles and headings, clustering semantically similar targets, and flagging posts competing for the same search intent. Supports local-only mode (grep-based) and DataForSEO API mode (Page Intersection endpoint at ~$0.01/call). Outputs severity-scored report with merge or differentiate recommendations. Use when user says "cannibalization", "keyword overlap", "competing pages", "duplicate keywords", "cannibalize".

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。

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' 'ad performance optimization,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' or 'I need more ad variations.' Use this whenever someone needs to produce ad copy at scale or iterate on existing ads. For campaign strategy and targeting, see ads. For landing page 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。

review-analyzer-skill是由buluslan（公众号：新西楼.AI）研发的电商评论深度分析Skill（VOC 客户之声分析），他会帮你把一堆产品评论变成一份能落地的决策依据——22 维 AI 打标提炼用户画像、痛点和真实需求，输出 15 章深度洞察报告和可视化看板，从差评里挖出产品优化机会点、从好评里找到爆款基因。 更多跨境电商 AI 实战内容，请关注公众号「新西楼.AI」。 Deep-dive e-commerce review & VOC analysis: 22-dimension AI tagging, 15-chapter insight report with anomaly signal cards, 6 themed visualization dashboards, CSV-primary multi-source input (SellerSprite optional), Feishu sync. 当用户需要以下功能时触发：分析电商产品评论（Amazon等平台）/ 从评论中提取用户画像、痛点和VOC（客户之声）/ 生成产品洞察报告和机会点分析 / 创建可视化分析看板 / 通过卖家精灵获取评论数据（可选增强；CSV为主源）/ 将分析结果同步到飞书文档。 触发关键词：电商评论分析、评论分析、竞品分析、用户洞察、VOC分析、产品优化、市场调研、评论数据挖掘、卖家精灵、sellersprite。 NOT for 关键词调研/选品雷达类任务（那些有专门工具）。

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。

Reverse-engineer the hook from a viral X (Twitter) tweet or thread URL. Identifies which of the 10 canonical 2026 X formulas it uses (one-liner contrarian, data-point, build-in-public, quote-tweet, mini-list, relatable cold-open, listicle-thread, story thread, curiosity-gap, how-I teardown), explains why it worked, and returns a blank template mapped to your topic with its primary goal. Use to learn from a tweet you admire. Not for writing your own (use x-post-writer or x-thread-builder).

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 a weekly X (Twitter) content plan from a theme, audience, and content pillars. Produces per-day recommendations (single tweet vs thread, X hook formula, angle, posting time, primary goal), a single-to-thread mix, daily reply and quote-tweet targets, and a goal-mix balance check across replies, reposts, likes, and bookmarks. Use when the user wants to plan a week of X content instead of ad-hoc posting. Not for drafting one tweet (use x-post-writer) or one thread (use x-thread-builder).

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Context-aware line edit that strips generic AI writing patterns without flattening the author's voice, plus a findings-only audit mode that names issues instead of rewriting. Applies contextual rules rather than blanket bans on adverbs, passive voice, and punctuation, and locks facts, numbers, quotes, code, links, and the supplied house style before it touches a sentence. Use before copy, a README, an email, a social post, or a doc ships; after a long assisted-writing session; when the text sounds fine but feels generated; or when the user asks for a findings-only slop audit. NOT FOR: writing new copy from scratch; deciding whether a person or a model wrote text; changing or certifying facts, which must be checked against primary evidence before publication.

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。

Suede-affiliated marketing deliberation that applies documented public frameworks through clearly labeled simulated advisors, surfaces disagreements, and synthesizes a decision. Use when the user wants multiple expert lenses on one bounded marketing question. NOT FOR: factual claims about a living person's private views, primary research (use suede-customer-research), or executing the selected tactic (route to the relevant public Suede skill).

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。

Suede Slop Stop: Suede Labs context-aware anti-slop pass for finished prose. Find or remove generic filler, manufactured emphasis, false agency, formulaic structure, chat and draft residue, and formatting applied by rule, without flattening the author's voice. Use before copy, a README, an email, a social post, or a doc ships; after a long assisted-writing session; or for a findings-only slop audit. NOT FOR: writing new copy (use suede-copy); deciding whether a person or model wrote text; changing or certifying facts, which require primary evidence.

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。

Suede-owned paid-media creative system for hooks, headlines, primary text, static and motion concepts, platform specs, review pages, and test-ready variant batches. Use when producing or iterating ad creative from grounded product and audience inputs. NOT FOR: campaign budgets, bidding, or targeting (use suede-ads), statistical test design (use suede-ab-testing), or landing-page copy (use suede-copy).

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 know if something works — the answer requires running code, not analyzing it. Output is a verdict backed by evidence: passed, failed, or broken. Primary triggers: 'run the tests', 'does X still work after my change?', 'did the merge break anything?', 'verify the fix worked', 'check if the endpoint returns X', 'confirm nothing regressed', 'run tests/unit/test_foo.py', 'let me know the results', 'make sure my changes didn't break anything'. Hard stops — do NOT use for: reviewing test code for quality/coverage gaps, debugging why test infrastructure/databases/seed scripts are misbehaving, writing or fixing tests, diagnosing root causes of unexpected behavior. The deciding question: is the user asking for the result of executing something, or asking for help understanding/analyzing/improving something? If it's the latter, use diagnose or review-code 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。

Build, modify, audit, repair, optimize, debug, and deploy agents with Agentforce Agent Script. TRIGGER when: user creates, reviews, or changes .agent files or aiAuthoringBundle metadata; asks to fix AgentScript, audit an existing agent, run an AgentScript health check, common-pitfall review, or baseline-versus-candidate repair loop; changes a response, action, subagent, route, state flow, or Agent Spec; previews, debugs, deploys, publishes, or tests agents; uses sf agent generate/preview/publish/test; or manages Agentforce MCP servers, tools, assets, or authentication. DO NOT TRIGGER when: Apex, Flow, Prompt Template, Experience Cloud, or general Salesforce CLI work is unrelated to Agent Script; or the primary input is a production session or trace ID rather than an agent artifact.

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Use only after explicit Codex `$superloopy:superloopy-research` or Claude Code `/superloopy:superloopy-research` invocation, a research task started with a leading `loopy` or `루피` (such as `loopy research`), or an active Superloopy loop explicitly routing a research deliverable here. Evidence-backed Superloopy research orchestration with automatic advisory usage targets, parallel read-only lanes, per-retrieval verdicts, graded and dated sources, empirical verification, a priced claim ledger, cited synthesis, and optional reports. Do not activate from research, investigate, look-up, summarize, deep-dive, report, or similar vocabulary alone, in any language; ordinary questions, debugging, and implementation context-gathering stay with their primary workflows.

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。

Unified image-generation engine for the product-shots ecosystem. Dispatches to the right model family (OpenAI gpt-image-2 / Gemini gemini-3-pro-image-preview Nano Banana Pro) with one parameterised script for text-to-image and image-to-image. Primary backend: OmniMaaS / Cloubic gateway (https://api.omnimaas.com/v1); also supports any OpenAI-SDK-compatible gateway via fallback env vars. Auto-resizes oversized reference images to prevent edge-proxy timeouts. Use when the user says "generate an image", "make a picture", "create a visual", "render this", "edit this image", "做一张图", "生成图片", "改这张图" — or when invoked as the image-generation backend by another product-shots skill (main-image / detail-page / ad-creative / social-post / multi-angle). NOT a creative-direction skill: takes a prompt + optional reference images, returns a file path.

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。

Design a pedagogical documentation protocol for making children's learning processes visible and shareable. Use when documenting learning, communicating with families, or planning next steps.

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。

Design a SEEDS regenerative inquiry cycle connecting place-based learning to ecological awareness for young learners. Use when building early childhood or primary inquiry around ecosystems and community.

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 students' capacity to interrogate a historical source before reading — asking who authored it, when, why, and what this means for reliability. Use when students read documents without attending to authorship.

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。

Present pathway options and orchestrate place-based curriculum design from a local place, curriculum requirement, or community issue. Use when place should become a primary text for 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。

Design a document set for a document-based lesson — selecting and sequencing sources for analytical tension around a central question. Use when assembling sources for a new lesson or when an existing set produces flat responses.

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。

When the user wants to generate, iterate, or scale ad creative — headlines, descriptions, primary text, or full ad variations — for any paid advertising platform. Also use when the user mentions 'ad copy variations,' 'ad creative,' 'generate headlines,' 'RSA headlines,' 'bulk ad copy,' 'ad iterations,' 'creative testing,' 'ad performance optimization,' 'write me some ads,' 'Facebook ad copy,' 'Google ad headlines,' 'LinkedIn ad text,' or 'I need more ad variations.' Use this whenever someone needs to produce ad copy at scale or iterate on existing ads. For campaign strategy and targeting, see ads. For landing page 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。

Query Etsy stores with multi-dimensional filters (sales, favorites, reviews, store opening date, country, primary category, Raving/Star ratings). Trigger when user mentions Etsy store, Etsy shop search, Etsy seller, Etsy shop ranking, Etsy weekly sales stores, Etsy stores, or Etsy store query — even if the tool name is not mentioned, as long as the need is to find stores, filter store data, or analyze store performance on Etsy.

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。

Drive one AI agent from another through kolu's terminals: spawn a Claude Code / Codex / opencode session in a PTY, prompt it, watch the screen, read the reply, prompt again. PRIMARY PATH: the kolu MCP tools (`lifecycle_create`/`lifecycle_sendInput`, `wait_outputSettled`/ `wait_agentState`, `screen_text`, the `terminals` resource). FALLBACK: the `kolu` CLI — same verbs, same discipline. Triggers on "drive another agent", "agent drives agent", "make Claude drive Codex", or wiring a loop where one coding agent supervises another.

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。

Maintain the durable, per-ticket run log that warp deploy/update skills append to at every milestone — a Linear-document-by-title primary with single-writer discipline and a local-file fallback, a machine-parseable per-chain row plus prose entry shape, and a surface-the-URL-as-proof hard gate. Referenced by any warp deploy/update skill that must leave a retrospective trail across worker restarts.

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。

Performs contract-driven compliance review of insurance certificates and endorsements against CRE/site-access and vendor agreement requirements. Produces pass/fail/conditional determinations, deficit lists, and broker-ready remediation instructions. Use when reviewing COI packets, ACORD 25 forms, or endorsements for additional insured, primary and non-contributory, waiver of subrogation, completed operations, umbrella alignment, limits adequacy, or insurer rating compliance. Trigger terms: COI, ACORD, additional insured, certificate holder, cancellation notice.

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。