文章をAIが扱う小さな単位に分け、大量のテキスト処理や独自の語彙学習を支援するスキル。分割結果と元の文章の位置対応、入力の長さ調整も扱います。
- 大量の文章をモデル入力用に処理したいとき
- 文章ファイルから独自の語彙を学習
- 予測結果を元の文章の位置に対応づける
2,093 件 ・ 関連度順
概要と使いどころ
文章をAIが扱う小さな単位に分け、大量のテキスト処理や独自の語彙学習を支援するスキル。分割結果と元の文章の位置対応、入力の長さ調整も扱います。
Per-token details for a specific token identified by keyword, symbol, or contract address: (1) search — find tokens by keyword/symbol/contract; (2) meta — static info: name, symbol, logo, social links, creator, official website; (3) dynamic — real-time market data: price, 24h change, volume, holder count, liquidity; (4) kline — OHLCV candlestick data for technical analysis. Use for: "price of $X", "search for token Y", "kline chart for $Z", "who created $W", "social links for $V", "holder count of $U", "candlestick data", "find the contract address of <token>".
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。
Extract design tokens, text styles, and variables from a Figma design system and produce a design-tokens.json plus ready-to-use QML singletons. Use this skill whenever someone wants to pull their design system out of Figma — whether they say "export tokens from Figma", "get design tokens", "set up my design system", "read our Figma design system", "get Figma variables into QML", "pull our color palette from Figma", "import design tokens", "extract colors/typography/spacing from Figma", or similar. Trigger this skill at the start of any design-system workflow that involves a Figma source.
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。
Validate DESIGN.md files against the official Google specification using the `@google/design.md` CLI linter. Works with local files. Use when the user wants to lint a DESIGN.md, check spec compliance, find broken token references, verify WCAG contrast ratios, diff two versions, export tokens to Tailwind or DTCG format, or audit a design system file for structural correctness. Trigger on mentions of "validate DESIGN.md", "lint DESIGN.md", "check my design.md", "design.md spec compliance", "WCAG contrast check", "broken token references", "design token validation", "export design tokens", "diff design systems", "design.md audit", "@google/design.md", "npx design.md lint", "design system validation", "frontmatter tokens", or any request to verify a DESIGN.md file.
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。
Audit or refactor a design token system for color — naming, structure, and coverage. Use when asked to "refactor our color tokens", "fix color token naming", or "improve token coverage for color".
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。
Tokenomics Analysis Agent — supply mechanics, unlock schedules, vesting, inflation, staking economics, distribution fairness, and token utility with Tokenomics Score (0-100)
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。
Deep OAuth 2.0 / OpenID Connect security assessment. Covers the full attack surface: redirect_uri validation bypass (path traversal, open redirect chains, subdomain confusion, URL parsing tricks, parameter pollution, response mode switching), missing/broken state parameter CSRF, PKCE downgrade and absent-challenge attacks, implicit grant token leakage (Referer, browser history, XSS fragment theft), authorization code injection, scope escalation, client confusion attacks, mutable-claims account takeover (iss+sub confusion, email-keyed identity merging), pre-account takeover via unverified registration, OpenID Connect dynamic client registration SSRF (logo_uri, jwks_uri, sector_identifier_uri, request_uri), nonce replay, ID token validation failures, Device Code phishing flow, mobile custom URI scheme hijacking, refresh token persistence, token introspection enumeration, consent screen clickjacking, host header injection, and cross-IdP mix-up attacks. Uses KOAuth, jwt_tool, nuclei oauth templates, and manual http(action="request", ...) payloads. Every technique includes actual request payloads and verification logic. Chains from /pentester or /api-security when OAuth endpoints are discovered. Chains into /web-exploit for open redirect, XSS, and SSRF chaining. Chains into /post-exploit when full account takeover is achieved. Chains into /credential-audit when access tokens or refresh tokens are recovered.
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。
Scrapes pump.fun/board using Chrome browser automation to extract the top 100 trending Solana tokens and writes structured markdown for a trading agent to consume. Use this skill any time you need to: scan pump.fun for new tokens, refresh the pump.md token list, run the scheduled board scrape, collect Solana meme token data, or build/update a trading watchlist from pump.fun. Even if the user says something casual like "check pump" or "update the token list" or "what's trending on pump", use this skill. The output file path and format are configurable but default to /Users/8bit/solanaos/pump.md.
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。
Dağıt: and monitor Canary Tokens via the Thinkst Canary API for deception-based breach Tespit using web bug tokens, DNS tokens, document tokens, and AWS key tokens.
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。
ローカルにある複数のAI開発エージェントのログを集計し、トークン数やAPI換算費用をSVGカードにします。READMEや資料に載せる利用状況をまとめられます。
Solanaのウォレット残高や保有トークン、取引、NFTを調べ、米ドル換算の資産額を確認するスキル。価格照会、大口送金やネットワーク状況の確認にも対応します。
Query token security audit to detect scams, honeypots, and malicious contracts before trading. Returns comprehensive security analysis including contract risks, trading risks, and scam detection. Use when users ask "is this token safe?", "check token security", "audit token", or before any swap.
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。
Crypto market leaderboards — ranked aggregate feeds across the whole market: social-hype/sentiment rank, trending / top-search / Binance Alpha / tokenized-stocks rank, smart-money net-inflow rank (which tokens received the most inflow), top meme tokens by breakout score on Pulse launchpad, top trader PnL leaderboard (ALL / KOL). Use whenever the user wants a ranked list of tokens or addresses by some metric — phrases like "trending tokens", "top N by hype", "leaderboard", "rank by X", "biggest inflows", "top traders this week".
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 mentions connect/disconnect wallet, sign in, sign out, web3 wallet, wallet address, check balance, how much crypto do I have, send BNB/USDT/crypto, transfer tokens, swap tokens, buy/sell token, DEX trade, limit order, market order, cancel order, get a quote, transaction history, wallet settings, daily limit, slippage, MEV protection, supported chains, available networks, prediction market, predict.fun, YES/NO market, place a prediction, redeem winnings, claim payout, prediction portfolio, prediction PnL, x402 payment, HTTP 402 Payment Required, pay a known x402 API, check approvals, view token approvals, revoke approval, manage approvals, wallet approvals, authorization management, token authorization, DeFi protocols, DeFi position, DeFi portfolio, staking, liquidity pool, LP, yield farming, health factor, APY, TVL, DeFi investment, DeFi deposit, DeFi redeem, DeFi stake, DeFi unstake, add liquidity, remove liquidity, claim rewards, claim fees, or any on-chain wallet operation.
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。
Deploy cloud-native deception across AWS, Azure, and GCP using decoy (honey) resources whose only purpose is to generate a high-fidelity alert the instant an attacker touches them: canary IAM access keys, permission-less decoy users/roles/service principals, honey object-storage buckets, and decoy secrets in Secrets Manager / Key Vault / Secret Manager. Wires detection through CloudTrail + EventBridge, Azure Sentinel honeytoken watchlists + Defender, and GCP Cloud Audit Logs, so any use of a decoy is routed to the SOC with near-zero false positives. Use when protecting cloud accounts and data stores, when an org has only on-prem honeypots and needs cloud coverage, when seeding fake AWS keys to catch credential theft and code-leak exposure, or when detecting cloud reconnaissance and lateral movement. Keywords: cloud deception, canary token AWS, honey S3 bucket, decoy IAM credentials, CloudTrail alert, GuardDuty, Sentinel honeytoken, decoy secret, honey service account, cloud honeypot, breach detection.
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。
Enumerate Microsoft Entra ID (Azure AD) tenants with ROADrecon and acquire, exchange, and abuse tokens (including primary refresh tokens) with roadtx. Use for authorized red-team enumeration of a tenant's directory objects or for token-based identity attacks against Entra ID you are explicitly authorized to test.
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。
Launch tokens on Base blockchain via the OpenServ Launch API. Creates ERC-20 tokens with Aerodrome concentrated liquidity pools. Use when launching tokens, deploying memecoins, or building agents that create tokens with locked LP. Read reference.md for the full API reference. Read openserv-agent-sdk and openserv-client for building and running agents. You can launch tokens for your OpenServ agents.
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。
Meme coin and token security audit — rug pull detection (honeypot, hidden mint, fee manipulation, LP lock bypass), Solana SPL token analysis (freeze authority, mint authority, metadata mutability), Token-2022 extension risks (transfer hooks, permanent delegate), DEX liquidity pool attacks (sandwich amplification, LP drain, bonding curve exploits), pump.fun/Raydium/Jupiter integration risks, token_scanner.py automation, and real exploit examples from 2024-2025. Use for any token audit, rug pull assessment, meme coin security review, or pre-investment due diligence.
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。
Hunt Forgot Password / Account Recovery Authentication Flaws — 5 distinct patterns: (1) username enumeration via different responses for valid vs invalid email, (2) reset token exposed directly in the API response body, (3) reset token not invalidated after use (replay), (4) password reset link works from a different IP/browser (no binding), (5) no rate limit on the reset request endpoint. These are the standalone recovery-flow broken-auth primitives — distinct from reset-email host-header poisoning (hunt-host-header) and the full ATO chain (hunt-ato owns password-reset as an ATO path; prove the primitive here, chain it there). Detection: trace the full forgot-password flow from request to token to use; check response diffs between valid/invalid emails; test token replay after consumption. Medium to High (enumeration=Medium, token-reuse=High, account-takeover=Critical when chained to known-email).
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。
Hunt JWT cryptographic failures — alg:none signature-stripping and RS256→HS256 key-confusion that let an attacker forge a token for any identity (e.g. an admin) without knowing a secret. Use when the app authenticates with a JSON Web Token (an `eyJ...` Bearer token in the Authorization header, a cookie, or a login response). This skill OWNS JWT signature/crypto forgery (alg:none, key confusion, kid/jku header injection); hunt-ato covers JWT as one ATO path, hunt-auth-bypass covers SSO/SAML token trust, hunt-api-misconfig covers non-crypto JWT handling. Critical when a forged token grants access to another user's data or an admin-only endpoint.
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。
Audit token usage across a product for coverage, drift, and hard-coded values. Use when tokens exist and you suspect they are being bypassed. For defining tokens in the first place, use `design-token` (design-systems).
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。
Secure Apify API tokens, configure proxy access, and protect Actor data. Use when hardening API key management, setting up environment-specific tokens, rotating a leaked token, or auditing Apify security configuration. Trigger with "apify security", "apify secrets", "secure apify token", "apify API key security", "rotate apify token".
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。
Token数量过滤器。筛选器将总令牌数的样本保留在特定范围内。 本SKILL使用依赖data_juicer,请在调用前安装好python环境并安装data_juicer,你可用以下指令进行安装: pip install py-data-juicer 当用户提到token数量过滤、文本token数筛选、按token数过滤、文本分词过滤等需求时使用此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。
Use when testing JWT-based authentication for algorithm confusion, alg:none bypass, weak HMAC secrets, missing expiration, kid parameter injection, and token storage in localStorage. Trigger on: Authorization: Bearer tokens, JWTs in cookies, any base64url encoded header.payload.signature pattern, OAuth2 access tokens, API authentication tokens, SSO tokens, JWKS endpoints. Detects RS256→HS256 confusion, public key as HMAC secret, unverified kid values used in file reads or SQL queries, and JWT cracking with short secrets.
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。