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概要と使いどころ
Fetch website traffic estimates (monthly visits, traffic sources, top countries, keywords, engagement, ranks) for any domain from SimilarWeb. Use when the user asks about a domain's traffic, monthly visits, traffic sources, audience countries, or wants to compare/benchmark sites against competitors.
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Manages Ahrefs API usage in Python using `ahrefs-python` library. Use when working with SEO / marketing related tasks or with data including backlinks, keywords, domain ratings, organic traffic, site audits, rank tracking, and brand monitoring. Covers `ahrefs-python` usage including AhrefsClient / AsyncAhrefsClient, typed request/response models, error handling, and all API sections.
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Build an interactive competitive-traffic report for any company and its rivals — monthly visits (SimilarWeb), organic search traffic and Domain Rating (Ahrefs) — as one self-contained HTML page with ranked charts, a three-month trend, a multi-year overlay and a data table. Use when asked to benchmark a product against competitors, size up a market, answer "how much traffic does X get compared to Y", build a competitive landscape, or produce a traffic/authority comparison deck or page.
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Perform keyword research using the SemRush API. Use when the user says "find keywords", "keyword research", "what should I rank for", "keyword ideas", "search volume", "keyword difficulty", "topic clusters", "content gaps", or asks about SEO keywords for a topic or niche.
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Estimate pages needed for topical authority. Go/no-go decision before investing months in content. Triggers on: "how much content do I need", "topical authority estimate", "content moat", "how many articles", "content gap analysis", "can I compete in this niche", "content investment calculator", "is this niche worth the effort", "SEO feasibility", "how many pages to rank", "content volume needed", "competitive content analysis", "moat calculation", "authority gap", "should I invest in this niche".
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。
TripAdvisor Content API for hotel ratings, restaurant search, attraction reviews, rankings, and nearby locations. Use when evaluating hotels or researching destinations. 5K calls/month.
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。
Find low-follower viral Bilibili videos for account-growth topic selection. Use when the user asks for B站低粉爆款, Bilibili low-fan hits, 起号选题 from B站, niche Bilibili references, or videos ranked by UP主粉丝数, 播放, 点赞, 投币, 收藏, 分享, 评论, 弹幕, and 播放粉丝比.
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。
Find recent viral YouTube videos for account-growth topic selection. Use when the user asks for YouTube 爆款, YouTube hot videos, 起号选题 from YouTube, niche video references, recent high-view videos, or videos ranked by views, likes, comments, freshness, and topic relevance without low-follower filtering.
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。
Find low-follower viral posts on X/Twitter for account-growth topic selection. Use when the user asks for X low-fan hits, Twitter low follower viral posts, 起号选题 from X, niche tweet inspiration, or viral posts ranked by author followers, views, bookmarks, likes, reposts, and replies.
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。
One-shot efficiency audit of a file, diff, or whole repo across BOTH axes at once: over-engineered code (reinvented stdlib, needless abstractions, speculative config) AND bloated prose (verbose comments, padded docstrings, redundant doc sections). Neither a pure code-minimizer nor a pure prose compressor does both in one pass. That's the point. Ranked report, biggest saving first; changes nothing. Use when the user says "chisle audit", "/chisle-audit", "audit this for bloat", "what can I cut", "review this PR for over-engineering and verbosity".
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。
Daily cross-platform rankings of AI agent skills (skills.sh, ClawHub, Tencent SkillHub, GitHub, X/HN/Bluesky). Use when the user asks which agent skill to install, what is trending, whether a skill is popular or trusted, or wants to compare skills. Read-only public CSV data; it recommends and links, it does not install anything.
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 taste evaluation framework — DVF primary filter, Apple/Google/Jobs design principles as explicit scoring criteria, weighted decision matrix, and option ranking for the DIVERGE wave
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Weekly, browser only when a source refuses to be fetched. Counts unpublished calendar entries per property by folding the published ledger against the calendar, and where every property is above its runway threshold it records the counts and exits, which is the normal run. Where a property is low it researches the next block from rank evidence, the topic map, and live result sets, refuses any keyword already targeted, and appends fully specified entries after the last existing block. It is the only writer of the calendar and it never modifies, reorders, or renumbers an existing entry.
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。
Weekdays, file work only, no browser at all. Reads every run record since it last ran, folds the published, draft, indexing, and rank ledgers, folds the card inbox into the work board, marks the single card the draft run works today, and writes the short morning brief the member opens first. It holds publishing and spending unless you released the channel, and it never touches a credential.
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。
Weekly, browser heavy, read only on every screen. Fixes a scoring window that neither double counts nor loses an hour, reads the member's search performance console and analytics property, verifies each range actually applied before reading a figure, reconciles every number against what this Employee published, writes the week's scoreboard and the short rolling state file every other routine reads, and files what it found as cards rather than doing the work itself. It types nothing on any screen, changes no setting, publishes nothing, and never touches a credential.
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。
Weekdays, browser only when a source refuses to be fetched. Works the single card the standup marked next: reads the shared publishing standard and the card's specification, pulls the live result set for the primary keyword, reads the pages currently ranking, writes the body, the metadata, the internal links and the outbound authority links, generates and compresses a hero, and leaves a complete draft folder with one ready line. It never opens a publishing surface, never touches a live property, and never touches a credential.
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。
Weekly, on a Friday, read only everywhere. Scores the week from the daily metrics ledger alone, with the screen and the date range beside every number, then writes the ranked paste ready list of what to change in the account next week. Each line names one change, the exact screen, the current value, the proposed value, and the evidence row it came from. It proposes no change it cannot source, it names no action it took because it takes none, and it spends only where you released it.
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 an ad account needs a systematic CONFIGURATION audit — 84 checkpoints across account, campaign, ad set, ad, tracking, and optimization, scored into a Health Score out of 100, quick wins ranked by impact, regional benchmarks, and a dropshipping checklist, covering Meta, Google, and TikTok. Trigger on 'ads audit', 'audit my ad account', 'is my Meta setup correct', 'health score for the account', 'review my Google Ads', 'we inherited this account and it is a mess'. Not for — diagnosing why the numbers moved this week, see `03-performance-eval-global`; planning fresh budget, see `54-media-plan-global`; rebuilding the campaign hierarchy, see `52-account-structure-global`.
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 paid ad AUDIENCES must be researched and defined before launch — target profile, interest and behavior mapping per platform, audience sizing, cold, warm, and hot tiering, lookalike seeds, exclusions, and ranked targeting hypotheses to test. Trigger on 'audience research', 'who should I target', 'interest targeting', 'Meta audience for this product', 'TikTok targeting ideas', 'my targeting is too broad'. Also use when launch is imminent and the ad set targeting is still empty. Not for — persona and JTBD depth for content, see `09-customer-insight-global`; warm retargeting tiers, see `56-retargeting-plan-global`; where the budget goes, see `54-media-plan-global`; the campaign hierarchy, see `52-account-structure-global`.
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。
针对Pandas DataFrame，按行计算非空且非零元素的排名分位数，并返回该行每个元素对应的分位数值。用于数据标准化或特征工程。
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。
Analyze and optimize tweets for maximum reach using Twitter's open-source algorithm insights. Rewrite and edit user tweets to improve engagement and visibility based on how the recommendation system ranks content.
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 designing, building or reviewing UI/UX for a web or mobile app: picking styles, color palettes, typography, layout, animation or charts, or checking accessibility and touch targets. Priority-ranked rules ordered by impact.
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。
Define a repository review policy fixing what each review pass checks, how severities rank, which paths are skipped, the nit cap, and who approves. Use when review findings feel inconsistent or noisy, or when tuning an automated reviewer.
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 anything in a Phoenix app is slow, times out, or uses too much memory, even if the cause looks obvious. Load it before analyzing or fixing: it runs measured Ecto, LiveView and OTP checks and ranks fixes.
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。