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Found 6,486 Skills
Collect agency leads from Google Maps — agency name, address, phone, website, rating, reviews. Use when the user wants to prospect marketing, design, or consulting agencies locally.
De-slop pass for any text. Scans for the statistical fingerprints of AI writing (negative parallelism / "not X but Y", em-dash density, rule-of-three, false ranges, puffery vocabulary, uniform cadence, hedged both-sidesing), rewrites by meaning, then re-scans until the text is clean and sits in the right register for its genre: academic article, tweet, reddit post, email, blog, docs, marketing. Use when the user says "deslopify", "deslop", "de-slop this", "remove the AI tells", "humanize this", "make this not sound like AI", or invokes /deslopify. Also use before publishing any agent-drafted prose.
Build, extend, and deploy Decentraland SDK7 scenes. This is the entry-point skill — it contains agent behavioral guidelines, the composite-first rule, and an index of all individual topic skills. Install this alongside the individual skills you need, or use `--skill '*'` to install everything.
通过 Agent 对话帮助中国高考考生完成志愿填报决策：先做有科学依据的性格与职业兴趣测评，再研究适合的职业、专业和行业，最后结合省份、选科、分数/位次与官方招生数据生成可追溯来源的 HTML 报告。用户提到高考志愿、college application、选大学、选专业、性格测试、职业方向、行业前景、投档线、录取概率、冲稳保或志愿模拟时使用。
Apply physics forces to the player in Decentraland scenes. Impulses (one-shot pushes), knockback (push away from a point with falloff), continuous forces (wind tunnels, anti-gravity, lift, hover), timed forces, and repulsion fields. Use when the user wants launch pads, knockback on hit, wind zones, gravity fields, or lifting/floating/hovering the player. THIS is also the right skill when an agent's first instinct is to mutate `Transform` on `engine.PlayerEntity` to move/lift/push the player — that does NOT work (player Transform is engine-controlled and read-only); use the Physics API instead. Do NOT use for player movement speed (see player-avatar AvatarLocomotionSettings) or platform movement (see animations-tweens).
Guided journey from a working-but-untested vibe-coded prototype to a production-ready product with tests, clean structure, a business-rules boundary, and resilience at scale. Orchestrates nine skills phase by phase - working-with-legacy-code, clean-code, refactoring-patterns, software-design-philosophy, clean-architecture, pragmatic-programmer, release-it, system-design, ddia-systems - asking the user questions at every decision point and recording results in the project docs/ folder (TESTING.md, TECH-DEBT.md, RELIABILITY.md, IMPROVE-CODE-QUALITY-PLAN.md) so the journey resumes across sessions. Use when the user wants to harden an AI-generated prototype, add tests before refactoring, make code safe to change, or says 'this works on my machine but I am scared to touch it'. For a large aged codebase, use remove-technical-debt; to decide structure before building, use design-code-architecture; for a product and UX pass, use improve-app. For one framework in isolation, invoke that skill directly.
Use to reverse-engineer why a piece of content went viral (or overperformed) — yours or someone else's — and extract the repeatable mechanism to apply to your own content. Run when the user says "why did this go viral," "break down this viral post/video," "reverse engineer," "what made this work," or wants to learn from viral content. Sources the observable signal first (intake, transcript, screenshots, top comments, visible stats — an agent usually can't watch a video from a link) and never fabricates what it can't see. Reads brand-profile and audience first, deconstructs the piece layer by layer, isolates the real driver, runs a replicability check, extracts the transferable principle, and applies it to the user's niche via the content skills. Mechanism, never a copy; flags non-replicable virality; visible signals only (no WoopSocial analytics). Single-POST teardown only: for the account-level competitive landscape use competitor-analysis; for riding a live trend use trend-jacking.
Query OpenRouter's Benchmarks API for model benchmark rankings and scores. Use when the user asks for benchmark-backed model selection, model rankings by coding/intelligence/agentic ability, Artificial Analysis or Design Arena ELO/win-rate results, benchmark citations, or wants to call GET /api/v1/benchmarks. Also use alongside openrouter-models when the user asks what model should power an app, product, workflow, or use case and benchmark evidence could inform or rule out part of the recommendation, including creative writing, editing, coding, design, agentic, or intelligence-heavy apps. Do not use for OpenRouter usage analytics, billing/spend analysis, generation metadata, provider uptime/latency, generic model pricing/capability lookup without any selection or benchmark-relevance decision, or creating an evaluation suite for a local app.
Author a working Claude Code hook from a plain-English description of what it should guarantee or do. You describe the behavior ("never let the agent edit my migrations", "don't stop until the tests pass", "log every command"); this skill picks the right lifecycle event, writes the hook script, and wires it into .claude/settings.json. Use when you want a deterministic guarantee or automation in your AI Layer and don't want to write the hook by hand. The meta-tool for the hooks primitive.
Instruments an existing Android project (Kotlin or Java) with the Dynatrace Mobile Agent for basic monitoring. Covers zero-to-first-event setup only: Gradle plugin, agent config, and user privacy opt-in. Do not use for advanced Dynatrace configuration beyond initial instrumentation.
Sets up and configures the Unity AI Navigation system — NavMesh surfaces, NavMesh agents, obstacles, links, modifiers, areas and costs. Use when creating walkable navigation meshes, adding pathfinding agents, setting up patrol routes, configuring obstacle avoidance and carving, connecting separate NavMeshes with links, coupling navigation with animation, or troubleshooting navigation issues.
Embed screenshots, images, diagrams, GIFs, and screen recordings in GitHub PRs and issues — or stage them ahead of a PR, collect them into one attachments comment, or get a durable public link to share a visual with a person. Use this whenever a visual needs to end up in a PR description, issue body, or PR/issue comment, in front of a teammate, or saved for a PR that doesn't exist yet. Triggers include "attach a screenshot to the PR", "add a before/after to the issue", "include a screenshot of …", "share a GIF of the flow", "record the bug and put it in the issue", "get me a link I can paste in Slack", "stage screenshots for the PR", "attach this when I open the PR", "save this for the PR", "collect the PR's media", or having just captured or changed something visual that a shot would make clearer — even mid-task, before a PR exists. Also applies when an agent has no local filesystem and is uploading via the hosted MCP (agents.uploads.sh). Reach for this instead of drag-and-drop or github.com/user-attachments (agents can't upload there) and instead of hand-rolling cloud-storage uploads. Capture the visual with whatever browser or screenshot tooling you have; this skill covers hosting and embedding it.