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Found 5,452 Skills
Content recycling — resurface, update, and repost proven evergreen content over time. Use when someone wants to "get more mileage out of old posts," "recycle/repost our best content," "resurface evergreen pieces," "update and republish an old post," or build a recycling queue of proven winners. Recycles the INSIGHT refreshed (new hook/format/updated data) on a deliberate cadence — never an identical repost. Distinct from cross-platform-repurposing (same moment, many platforms) and captions-and-clipping (long-form -> short clips). Reads brand-profile + voice-builder first. The agent drafts the refresh; a human reviews; WoopSocial schedules/publishes (delete+recreate, no update); winners are picked from native analytics; nothing is fabricated.
Use when you need to check feature flag states, compare channels, or debug why a feature behaves differently across release channels.
Use for Desktop Commander MCP capabilities — persistent shells and REPLs, long-running processes, filesystem beyond the workspace, structured files (.xlsx, .docx, .pdf, images) and large local data files such as CSVs, ripgrep search at scale, SSH, or cross-turn state.
Use when the user asks to "set up conversion values so tROAS optimizes profit not orders", "map margin onto my purchase value", "build value rules for lead / phone / signup conversions", or "stop bidding to revenue when I care about profit"; defines and QAs the conversion VALUE model — per-conversion values, margin/net-value adjustment, static-vs-dynamic value rules, proxy values for non-revenue actions, and a value-vs-count sanity check — as a value-model spec plus a pre-launch value QA sheet. Not for whether the tag fires or UTMs are clean — use conversion-signal-qa; not for cross-platform double-count de-dup — use attribution-reconciler; not for scoring R1/R2 — that is a scored veto in ad-account-auditor. 付费广告转化价值建模/利润出价/价值规则QA
Deterministic issue-relationship graph over GitHub native sub-issues + dependencies — compute the ready set / parent-rollup candidates / close-kick targets as pure calculation (scripts, no LLM judgment), write real edges when creating spin-off issues, and mutually exclude terminal actions across parallel agents via claim-comment fencing. Called by issue-sweep (candidate injection), issue-review (edge writing + rollup), and the future agent:ready producer routine.
Xiaohongshu Daily Viral Notes tracks daily trends across various fields on Xiaohongshu, monitors real-time popularity changes in different sectors, identifies emerging content directions, and predicts the next wave of viral traffic opportunities. Finally, based on the day's viral content, it extracts reusable topics, scripts, and presentation formats to generate creative inspiration. It supports category-based queries for daily popular notes, allowing users to search for the most popular Xiaohongshu notes of the day by categories such as beauty, fashion, food, etc., and quickly grasp the top content in each track.
Use when the user mentions migrating deep links, switching away from Branch or AppsFlyer, replacing their deep linking SDK, setting up Detour deep linking for the first time, or asks how Branch/AppsFlyer concepts map to Detour. Covers the complete migration end to end - Detour Dashboard configuration, Universal Links and App Links setup, SDK swap with code examples, and analytics migration. Works across Android, iOS, React Native, and Flutter.
Multi-perspective in-depth analysis. Use multiple Sub-agents to act as consultants with different thinking frameworks, conduct independent analysis on the same material, then cross-summarize consensus and differences, and produce a structured diagnostic report. Triggered when the user says "Help me with multi-perspective analysis", "Multi-dimensional analysis", "Look at it from multiple perspectives", or "Help me diagnose it".
Use before emailing a PostHog customer, replying to one, or joining a call, and for any request to research a PostHog account. Fires on "/posthog-customer-deep-dive" and on natural language like "deep dive on X", "look up this customer", "help me reply to Y", "prep me for my call with Z", from an email address, domain, account name, or Vitally account id. Researches the account across Vitally and project 2 usage queries, then drafts an email (first touch, follow-up, or reply) or a call-prep brief, every recommendation carrying a live docs link.
Profile, audit, and optimize frontend page performance with emphasis on animation work, memory-leak risks, long-session slowdowns, CSS animations, canvas/WebGL requestAnimationFrame loops, marquees, skeletons, GSAP/Three/Matter effects, timers, listeners, and observers. Use when the user asks to make animations performant, pause offscreen animations, look for memory leaks, profile pages that slow the computer over time, fix janky scrolling, reduce CPU/GPU use, or repeat the "only play in view" optimization on React/Vite/Next/frontend pages using Codex Browser.
NOTE: molecule and target inputs and your NGC_API_KEY are transmitted to external NVIDIA-hosted API endpoints on every call. Use local NIM containers for confidential or proprietary data. Run a complete computational drug discovery pipeline using NVIDIA BioNeMo NIMs: generate drug-like molecules with GenMol, dock them to a protein target with DiffDock, then predict binding affinity with Boltz2. Use this skill whenever the user wants to generate and screen small molecule drug candidates, perform hit discovery, optimize leads against a protein target, or do virtual screening combining molecule generation, docking, and affinity prediction. Triggers on: drug discovery pipeline, hit discovery, lead optimization, virtual screening, molecule generation, molecular docking, binding affinity, GenMol, DiffDock, Boltz2, SMILES, SAFE notation, NIM microservice. This is a multi-step pipeline composing three BioNeMo NIMs.
Use this skill for OpenFold2, NVIDIA's BioNeMo NIM microservice for monomer protein structure prediction. Invoke whenever the user mentions OpenFold2, AlphaFold2-like monomer folding, protein sequence-to-structure prediction, A3M MSAs, mmCIF templates, hosted NVIDIA API calls, or local Docker deployment.