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Found 44 Skills
Use when creating animations for business contexts that require seriousness, competence, and trustworthy presentation.
Use when applying for Xiaohongshu account verification (blue check), understanding verification types and benefits, preparing verification application materials, or increasing account credibility and trust
Evaluate source credibility using primary/secondary classification, internal/external criticism, triangulation, and misinformation detection. Use this skill when the user needs to assess whether information is trustworthy, evaluate research sources, fact-check claims, or detect misinformation — even if they say 'can I trust this source', 'is this real', 'how reliable is this data', or 'fact-check this for me'.
Guides advanced short-term actuarial mathematics aligned with SOA ASTAM and P&C/health-adjacent modeling—severity and frequency distributions, aggregate and compound loss models, Bühlmann and Bühlmann-Straub credibility, ratemaking and experience rating, short-term reserving at the math level, MLE and goodness-of-fit, and risk measures (VaR, TVaR). Tool-agnostic and concept-first. Use when the user mentions advanced short-term actuarial mathematics, ASTAM, severity model, frequency model, aggregate loss, compound distribution, Bühlmann credibility, experience rating, ratemaking, pure premium, negative binomial frequency, tail factor, TVaR, or short-term actuarial models—not life contingencies (life-health-insurance), Excel workpapers only (actuarial-analyst), appointed actuary sign-off (actuary, appointed-chief-actuary), assumption governance (assumption-setting), P&C legal/operations depth (property-casualty-insurance), or general ML (data-scientist, quantitative-researcher).
Running structured, multi-source research that produces a trustworthy, cited synthesized answer. Use when a question needs more than a single lookup — comparing options, validating a claim, surveying a market or technology, or briefing a decision where being wrong is costly. Covers scoping (and narrowing) the question, fanning out across sources, judging source quality, adversarially verifying each key claim, separating fact from inference, and reporting with explicit confidence. Keywords deep research, multi-source, fact-check, verify, synthesize, cited report, source credibility, due diligence.
Decide whether to act on a caller's (喊单人) calls. Scores one call-out wallet on two axes — SELECTION (do the coins he calls actually run) and POST-CALL CONDUCT (does he sell into the attention his own call created) — then returns a follow / don't-follow verdict. The conduct axis is proved from the caller's own per-trade ledger, not from any self-reported field: for each sampled coin it compares the first buy, the call timestamp, and every sell after it, so "he dumped on his followers" is a measured sequence rather than an inference. USE THIS SKILL WHEN the user asks whether a caller is worth following: 这个喊单的能不能跟, 这个喊单号靠不靠谱, 喊单信誉分, 喊单评分, 他喊完会不会砸盘, 他是不是喊完就卖, 跟他的单能不能吃到, caller 评分, is this caller trustworthy, can I follow this caller's calls, does he dump after calling, call-out credibility score, score this caller. Accepts either a GMGN profile handle (twitter_username, e.g. the last path segment of a gmgn.ai/profile/<handle> link) or a wallet address; a handle is resolved to one (chain, wallet) pair in Step 0 and the resolution is always echoed. The same questions in any other language route here — match on meaning, not wording. DO NOT USE THIS SKILL for raw call-out data — "这个钱包 喊过什么单", "最新喊单", "谁在喊这个币", "KOL 在喊什么", the feed, the field dump, the 30d summary card — that is gmgn-callout, which owns every read of the callout endpoints and returns them untouched; this skill calls it and adds a verdict. Nor for a caller judged as a trader rather than as a caller ("这个钱包能不能跟单", "跟单评分", copy-trade backtest) — that is gmgn-wallet-analysis / gmgn-wallet-score, which read his trades and know nothing about his calls. Nor for a token the caller mentioned ("他喊的那个币安全吗", 尽调, rug check) — that is gmgn-contract-dd. Nor for a token creator's next launch ("这个 dev 的新盘能不能买") — that is gmgn-dev-score. A bare wallet address with no call-out intent stays with gmgn-wallet-analysis; a bare token address stays with gmgn-contract-dd. This skill needs the word 喊单 / caller / call-out in the ask to own it. TIE-BREAKS, because three words are shared with neighbouring skills: 喊单 paired with 能不能跟 / 信誉 / 砸盘 / 评分 routes HERE, while 喊单 paired with 喊过什么 / 最新 / 谁在喊 / 列表 routes to gmgn-callout — the first group asks for a judgement, the second for rows. 能不能跟 without 喊单 is about a wallet as a trader and stays with gmgn-wallet-analysis / gmgn-wallet-review. 信誉 without 喊单 is a launcher question and stays with gmgn-dev-score. PRESET PHRASES this skill is written to answer, each carrying the call-out intent word: 「帮我看看 [喊单人ID或地址] 这个喊单的能 不能跟」「[喊单人ID] 喊的币能跟吗」「查一下 [钱包地址] 的喊单信誉」「这个喊单号喊完会不会 砸盘:[地址]」. WHAT IT CANNOT ANSWER, so the ask goes elsewhere: whether any one called coin is safe to buy (gmgn-contract-dd); what he is calling right now (gmgn-callout global); whether he is a good trader to copy (gmgn-wallet-score); who else called the same coin or whether he called it first (no per-token caller list exists in the CLI, so it is not computable at all); how much he staked on a call (readable only in the unfilterable global feed); anything older than 30 days (callout record covers 30d only).
Reviews pitch decks and investor presentations. Reads slide content, evaluates narrative flow, problem/solution clarity, market sizing, competitive positioning, financial projections, team credibility, and ask clarity. Generates a scored pitch-review.md with slide-by-slide feedback, overall score, top improvements, investor objection predictions, and comparisons to successful decks. Use when reviewing fundraising materials, investor decks, or pitch presentations.
When translating product details into messaging, climb a 4-rung ladder from Feature → Product Truth → Functional Benefit → Emotional Benefit. Forces every emotional claim to have a credibility chain back to a verifiable feature, beating messaging that's either too technical (specs without meaning) or too floaty (emotion without proof).
Write academic research documents following academic guidelines with peer-reviewed sources from Google Scholar and other academic databases. Always verify source credibility and generate IEEE standard references. Use for research papers, literature reviews, technical reports, theses, dissertations, conference papers, and academic proposals requiring proper citations and scholarly rigor.
Grassroots-first campaign design for anyone being outspent — startups vs. incumbents, NGOs vs. corporate comms, movements vs. state-backed machines, solo brands vs. big-budget competitors. Ideates awareness, launch, fundraising, mobilization, community-build, counter-narrative, referral, founder-story, and coalition campaigns. Triggers on "campaign plan", "marketing strategy", "ad budget", "should I advertise", "paid vs organic", "launch plan", "grassroots", "low budget marketing", "NGO campaign", "outspent", "competitor has bigger budget", "how do I compete without money". Also trigger on any spend asymmetry, collapsing organic reach, rising CPAs, or a trust/credibility problem — even without the word "campaign". Nudge activation when the user debates buying ads, boosting posts, or hiring influencers; they are likely about to burn money on a channel that will not persuade.
Use when auditing domain authority, trust, or citation credibility; runs a peer-relative 40-item CITE profile with evidence coverage and verified manipulation/penalty veto checks. Not for page-level content quality — use content-quality-auditor; not for backlink profiling alone — use offsite-signal-analyzer. 域名权威/网站可信度
Analyzes events through journalistic lens using 5 Ws and H, investigative methods, source evaluation, fact-checking, newsworthiness criteria, and ethical journalism principles. Provides insights on story angles, information gaps, credibility, public interest, and media framing. Use when: Breaking news, information verification, source analysis, story development, media criticism. Evaluates: Factual accuracy, source credibility, completeness, newsworthiness, bias, public interest.