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Found 586 Skills
When the user wants to design, launch, or optimize a referral or affiliate program. Use when they mention 'referral program,' 'affiliate program,' 'word of mouth,' 'refer a friend,' 'incentive program,' 'customer referrals,' 'brand ambassador,' 'partner program,' 'referral link,' or 'growth through referrals.' Covers program mechanics, incentive design, and optimization — not just the idea of referrals but the actual system.
Interpret the meaning of paper figures and output a highly readable Markdown report that 'teaches humans how to read figures'; supports input of absolute paths to one or more figure files and manual interpretations, automatically attempts to retrieve the source code used to generate the figures from the vicinity of the figures, and uses a parallel-vibe-like approach to interpret each figure with process-level isolation via `codex exec`/`claude -p` (default concurrency limit is 3, adjustable in config.yaml). ⚠️ Not applicable: Users only want to adjust figure size/crop/change format; or request direct modification of images/source code (this skill has read-only access to images and source code throughout, modification is strictly prohibited).
Query-driven targeted ingest from a specific AI agent's raw history. Use this skill when the user invokes /wiki-claude, /wiki-codex, /wiki-hermes, /wiki-openclaw, /wiki-copilot — with or without a search topic. Different from wiki-history-ingest (which bulk-ingests everything new): this skill finds sessions about a SPECIFIC TOPIC in a specific agent's history and ingests just those, then returns a synthesized answer immediately usable in the current session. Primary use case: you're working in agent A and want to pull in how you solved X in agent B's history. Cross-referencing, not archiving. Also trigger on: "what did I work on in codex about X", "search my claude sessions for Y", "pull in hermes knowledge about Z", "find that conversation where I did X in codex".
Designing meeting schedulers and booking experiences that qualify leads, set up calls well, and convert at higher rates than a generic Calendly link. Availability logic, qualification gating, prep automation, follow-up sequencing. Honest about any-time-friction (no qualification, just a booking link), interrogation-gate (so much qualification it scares users off), and qualified-fast-path (just enough qualification to set up the call well) patterns. Triggers on scheduler design, meeting booking, demo scheduling, sales call scheduling, calendar tool, booking page, qualification flow. Also triggers when sales team complains about cold demos, when booking conversion is poor, or when scheduler is being scoped for the first time.
Graham cigar-butt (NCAV / net-net) single-stock diagnostic. Combines a 100-point static cheapness score (NCAV, PE, PB, dividend yield, debt coverage, earnings stability) with a dynamic adjustment layer (industry cycle, earnings trend, insider activity, NCAV trajectory) to separate real bargains from value traps. Pulls data from Longbridge CLI/MCP first, falls back to WebSearch only for gaps, runs cross-statement reconciliation (勾稽校验) before scoring, and footnotes every figure to its source. Triggers: "格雷厄姆", "捡烟蒂", "烟蒂股", "烟蒂投资", "NCAV", "净流动资产", "清算价值", "安全边际", "价值陷阱", "深度价值", "撿煙蒂", "煙蒂股", "煙蒂投資", "淨流動資產", "清算價值", "安全邊際", "價值陷阱", "深度價值", "Graham", "cigar butt", "net-net", "liquidation value", "value trap", "margin of safety", "deep value", "Benjamin Graham".
End-to-end conference talk pipeline: paper → slide outline → Beamer + PPTX → per-page polish → assurance checks (claim / citation / anonymity) → final export and report. Default-good for academic conference talks (NeurIPS / ICML / ICLR / VALSE / 投稿 talks). Trigger phrases: "做 talk", "做 PPT 全流程", "talk pipeline", "end-to-end slides", "做演讲", "conference talk full workflow". Use when the user wants the complete talk artifact, not just a slide deck.
Patterns for building applications that integrate the Krea API. Auth, polling discipline, error handling, validation, frontend integration (SvelteKit/React/Vue), and the 'prototype in chat, productize in app' workflow. Use when the user is writing code that calls the Krea API directly — building a generator UI, a content pipeline, a creative tool — not when they just want to generate one image. For interactive generation use the sibling krea-ai skill instead.
Amend a published CLI from one of two input sources: (1) dogfood mode mines the active Claude Code session transcript for friction (missing flags, hand- rolled API payloads, silent-null returns); (2) direct-input mode accepts user-supplied asks (rename a command, add commands or feeds, fix a named bug, optionally sniff the source site for new endpoints). Confirms scope with the user, plans + executes the fix autonomously, scrubs PII, and opens a PR against mvanhorn/printing-press-library. Two user-in-loop checkpoints: scope after capture, PR draft before open. Trigger phrases: "amend the CLI", "submit a patch", "fix what I just dogfooded", "open a PR for this CLI", "patch this CLI", "add features to my CLI", "rename this command", "add these feeds to <cli>", "sniff for new APIs in <cli>", "amend with these ideas", "use printing-press-amend", "run printing-press-amend".
Extract self-contained static HTML from a built web application or React components by inlining CSS and images. Use this skill whenever you need to capture a specific UI state, share a static version of a page, or prepare assets for Stitch upload, even if the user just asks to 'save the HTML' or 'mock the view'.
Guide for theming .NET MAUI apps — light/dark mode via AppThemeBinding, ResourceDictionary theme switching, DynamicResource bindings, system theme detection, and user theme preferences. Use when: "dark mode", "light mode", "theming", "AppThemeBinding", "theme switching", "ResourceDictionary theme", "dynamic resources", "system theme detection", "color scheme", "app theme", "DynamicResource". Do not use for: localization or language switching (see .NET MAUI localization documentation), accessibility visual adjustments (see .NET MAUI accessibility documentation), app icons or splash screens (see .NET MAUI app icons documentation), or Bootstrap-style class theming (see Plugin.Maui.BootstrapTheme NuGet package).
Prepare for and respond to SEC and FINRA regulatory examinations across the full exam lifecycle. Use when the user asks about exam notification letters, document request lists, deficiency letter responses, mock examination programs, annual compliance reviews under Rule 206(4)-7, or SEC/FINRA examination priorities. Also trigger when users mention 'we just got an exam letter', 'preparing for our first SEC exam', 'how to respond to a deficiency finding', 'staff interview preparation', 'what does OCIE look for', 'examination readiness checklist', 'sweep exam on off-channel comms', or ask what to expect during a regulatory audit.
Drafts, reviews, rewrites, and coaches outcome-based OKR sets across team, department, product, or company scopes. Supports five entry modes (Guided default, One-Shot via --oneshot, Sustained Coach, Audit Only, Rewrite). Diagnoses empowered-team context and adjusts framing; refuses to fabricate baselines or targets; refuses to use OKR scores for compensation; reframes feature-delivery KRs into outcome KRs. Use when planning quarterly OKRs, translating strategy into team outcomes, reviewing draft OKRs for quality, or converting roadmap-as-OKR drafts into proper OKR sets.