Agent Skills

recipes

★ 13

by deepgram

Find focused, runnable Deepgram recipes for a specific feature × language. Use whenever someone wants a minimal working code snippet for ONE feature (transcribe URL, diarize, smart-format, voice agent connect, etc.) rather than a full starter app. Recipes are under 50 lines, read DEEPGRAM_API_KEY from env, and ship with a runnable example_test. Covers Python, JavaScript, Go, .NET, Java, Rust, and the Deepgram CLI.

docs

★ 13

by deepgram

Find the right Deepgram documentation for any task. Use whenever someone needs help locating docs, understanding which API to use, or wants to ask questions about Deepgram. Covers all product areas: speech-to-text, text-to-speech, voice agents, audio intelligence, and self-hosted deployments.

examples

★ 13

by deepgram

Find working Deepgram integration examples with third-party platforms and frameworks. Use whenever someone wants to integrate Deepgram with Twilio, LiveKit, LangChain, Vercel AI SDK, Discord, Vonage, Pipecat, Expo, FastAPI, Cloudflare Workers, Slack, Telegram, LlamaIndex, Zoom, Next.js, Nuxt, Django, SvelteKit, NestJS, Spring Boot, CrewAI, Riverside, SignalWire, and more. Examples are full runnable integration demos, not minimal feature snippets.

api

★ 13

by deepgram

Deepgram API reference for speech-to-text, text-to-speech, voice agents, audio intelligence, and account management. Use whenever building with Deepgram APIs — REST or WebSocket. Covers authentication, all endpoints, query parameters, request/response schemas, and WebSocket message formats. Reference files are organized by domain: listen (STT), speak (TTS), agent (voice agents), read (text/audio intelligence), models, projects, auth, and self-hosted.

agentspace

★ 12

by agentspace-so

See what your AI agent is doing, from anywhere. The agent keeps writing — logs, code, generated outputs, screenshots, artifacts. One command turns the folder into a live URL you (or a teammate) open in any browser to watch files evolve, edit in place, or comment — no sync, no zip, no account. Workspaces stay live 24 hours anonymously; one email claim keeps them permanent. Hosted on Cloudflare. Triggers on "show me what the agent is doing", "open the agent's folder", "share this folder", "give me a link", "hand off this workspace", or any ask to make an agent's local file state visible from another device or to another person.

find-skills

★ 12

by agentspace-so

Discover, vet, and install agent skills by searching ACROSS every major registry at once — skills.sh, clawhub.ai, and GitHub — presenting each board on its own native metric (installs / stars) with the top entry per board, security-scanning the top candidates' real SKILL.md for risky patterns, and flagging what's already installed. Use when the user asks "how do I do X", "find a skill for X", "is there a skill that…", "what skill should I install for…", or wants to extend the agent with a capability that might already exist as a published skill. Unlike single-registry search, this surfaces the best of every platform side by side, so you recommend the genuinely relevant, popular, well-maintained, and SAFE one — not whatever ranked first on one site.

cra-to-next-migration

★ 11

by vercel

Comprehensive guide for migrating Create React App (CRA) projects to Next.js. Use when migrating a CRA app, converting React Router to file-based routing, or adopting Next.js patterns like Server Components, App Router, or image optimization.

axiom-sre

★ 10

by axiomhq

Expert SRE investigator for incidents and debugging. Uses hypothesis-driven methodology and systematic triage. Can query Axiom observability when available. Use for incident response, root cause analysis, production debugging, or log investigation.

controlling-costs

★ 10

by axiomhq

Analyzes Axiom query patterns to find unused data, then builds dashboards and monitors for cost optimization. Use when asked to reduce Axiom costs, find unused columns or field values, identify data waste, or track ingest spend.

query-metrics

★ 10

by axiomhq

Runs metrics queries against Axiom MetricsDB via scripts. Discovers available metrics, tags, and tag values. Use when asked to query metrics, explore metric datasets, check metric values, or investigate OTel metrics data.

building-dashboards

★ 10

by axiomhq

Designs and builds Axiom dashboards via API. Covers chart types, APL and metrics/MPL query patterns, SmartFilters, layout, and configuration options. Use when creating dashboards, migrating from Splunk, or configuring chart options.

spl-to-apl

★ 10

by axiomhq

Translates Splunk SPL queries to Axiom APL. Provides command mappings, function equivalents, and syntax transformations. Use when migrating from Splunk, converting SPL queries, or learning APL equivalents of SPL patterns.

agent-friendly-apis

★ 9

by vercel

Companion skill for the Agent-Friendly APIs course on Vercel Academy. Use when the user mentions "agent-friendly APIs", "API documentation", "llms.txt", "the course", "teach me", or asks about agent-friendly docs, documentation patterns, or building Claude Code skills in the context of the Academy course.

filesystem-agents

★ 9

by vercel

Companion skill for the Building Filesystem Agents course on Vercel Academy. Use when the user mentions "filesystem agents", "the course", "teach me", or asks about ToolLoopAgent, Vercel Sandbox, or bash tools in the context of the Academy course.

happyhorse-1-0

★ 8

by runcomfy-com

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

codex-pet

★ 8

by runcomfy-com

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into `${CODEX_HOME:-$HOME/.codex}/pets/<name>/` and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as `runcomfy run openai/gpt-image-2/edit` to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no `$imagegen`, no OPENAI_API_KEY required, only RUNCOMFY_TOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

video-inpainting

★ 8

by runcomfy-com

Region edits across video frames on RunComfy via the `runcomfy` CLI — remove an object that appears across many frames, clean up wires or watermarks, replace a region with matching motion. Routes across Wan 2-7 edit-video (default, prompt-driven region edits with spatial language), Lucy Edit Restyle (identity-stable region-aware restyle), and Seedream 4-0 edit-sequential (when treating the clip as a frame stack). Picks the right route based on whether the change is prose-driven, identity-locked, or needs frame-by-frame still inpaint chained into a video. Triggers on "video inpaint", "video inpainting", "remove from video", "mask region in video", "clean up video", "remove object from clip", "video patch", "frame-by-frame edit", "remove watermark from video", "remove passing person", or any explicit ask to edit a region across video frames.

ai-avatar-video

★ 8

by runcomfy-com

Create AI avatar, talking-head, and lip-sync videos on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar), Wan-AI Wan 2-7 (audio-driven mouth sync via `audio_url` on a portrait), HappyHorse 1.0 (Arena #1 t2v / i2v with in-pass audio), and Seedance v2 Pro (multi-modal cinematic with reference audio + reference subject). Picks the right model for the user's actual intent — UGC voiceover, virtual presenter, dubbed product demo, lip-synced character, dialog scene — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "talking head", "lip sync", "avatar video", "make X speak", "audio to video", "audio driven avatar", "virtual presenter", "AI spokesperson", "dubbed video", "UGC avatar", "HeyGen alternative", "Synthesia alternative", "digital human", "make this portrait talk", "video from voiceover", or any explicit ask to put words in a face.

vercel-react-best-practices

★ 8

by vercel

React and Next.js performance optimization guidelines from Vercel Engineering. This skill should be used when writing, reviewing, or refactoring React/Next.js code to ensure optimal performance patterns. Triggers on tasks involving React components, Next.js pages, data fetching, bundle optimization, or performance improvements.

image-to-video

★ 8

by runcomfy-com

Animate any still image on RunComfy — this skill is a smart router that matches the user's intent to the right i2v model in the RunComfy catalog. Picks HappyHorse 1.0 I2V (Arena #1, native audio, identity preservation) for general animations, Wan 2.7 with `audio_url` for custom-voiceover lip-sync, or Seedance 2.0 Pro for multi-modal animation from image + reference video + reference audio. Bundles each model's documented prompting patterns so the caller gets sharper output without burning iterations on the wrong model. Calls `runcomfy run <vendor>/<model>/image-to-video` (or endpoint variant) through the local RunComfy CLI. Triggers on "image to video", "image-to-video", "i2v", "animate image", "make this move", or any explicit ask to turn a still into video.

signoz-modifying-dashboards

★ 6

by signoz

Modify an existing SigNoz dashboard: add or remove panels, edit a panel's query, threshold, or unit, rename the dashboard, change a panel type (graph ↔ table ↔ value), rearrange the layout, add or edit variables, or update tags. Make sure to use this skill whenever the user says "add a panel to my dashboard", "change the query on this panel", "remove the latency widget", "rename my dashboard", "update the filters", "rearrange the layout", "add a variable", "change panel type from graph to table", or otherwise asks to change something on a dashboard that already exists, even if they don't say "modify" or "edit" explicitly.

signoz-mcp-setup

★ 6

by signoz

Initialize or repair SigNoz MCP server configuration for Agent Plugins v1, Claude Code, Codex, Cursor, VS Code/GitHub Copilot, Claude Desktop, Gemini CLI, Devin CLI, Grok Build, Windsurf, Zed, Antigravity CLI, OpenCode, or another MCP client. Use this skill before any SigNoz docs, query, dashboard, alert, or view workflow when `signoz_*` tools are unavailable, or when the user says "setup SigNoz MCP", "configure SigNoz plugin", "wrong region", "change SigNoz region", "MCP auth failed", or asks to connect SigNoz Cloud or a self-hosted MCP endpoint, even if they do not mention the plugin.

signoz-searching-docs

★ 6

by signoz

Look up information in SigNoz documentation. Make sure to use this skill whenever the user asks "how do I", "where in the docs", "what does the docs say about", "find docs for", or otherwise needs reference material on SigNoz instrumentation, OpenTelemetry setup, self-hosted deployment, API endpoints, auth headers, or troubleshooting steps — even if they don't say the word "docs" explicitly. Docs lookup only — for actions inside SigNoz, the agent will pick the matching `signoz-*` action skill.

signoz-investigating-alerts

★ 6

by signoz

Diagnose why a SigNoz alert fired by correlating the alert's own signal with neighbor signals (error rate, latency, throughput, CPU/memory), traces, and logs around the fire window, and rank likely causes. Make sure to use this skill whenever the user asks "why did this alert fire", "what caused alert X", "investigate this alert", "RCA for the alert that paged me", "what's wrong with [service]" in the context of a recent fire, or otherwise asks for a root-cause analysis of a firing or recently-fired alert. Read-only; does not modify any alert or notification.

signoz-setting-up-observability

★ 6

by signoz

Run the full end-to-end observability setup for a service after its telemetry is already flowing into SigNoz: sequence SLI/SLO capture, data exploration (RED/USE), focused dashboards, saved Explorer views, burn-rate and absent-data alerts, and a tuning loop into one opinionated, SLO-aware workflow. Make sure to use this skill whenever the user says "set up observability after ingestion", "now that data is flowing, give me dashboards and alerts", "onboard this service to SigNoz end-to-end", "I want the full monitoring setup for X", or asks to go from raw telemetry to a complete dashboard + alerts + views package, even if they don't say "observability" explicitly. This is the orchestration layer: for a single artifact (just a dashboard, just one alert, just a saved view, or one static threshold alert, or a one-off query) use signoz-creating-dashboards, signoz-creating-alerts, signoz-managing-views, or signoz-generating-queries directly.

signoz-creating-alerts

★ 6

by signoz

Create a new SigNoz alert rule from a natural-language intent: threshold, anomaly, log-volume, error-rate, latency, or absent-data alerts across metrics, logs, traces, and exceptions. Make sure to use this skill whenever the user says "alert me when…", "notify me if…", "set up monitoring for…", "page me on…", "create an alert for…", or asks for a new alert/notification rule, even if they don't say the word "alert" explicitly. Also use it when someone asks to be notified about error rates, latency spikes, log volume, CPU/memory pressure, or anomalous behavior on a service or host.

signoz-explaining-alerts

★ 6

by signoz

Describe what an existing SigNoz alert rule does in plain language: the signal it watches, the threshold and evaluation behavior, the notification routing, and a one-line fire-frequency summary so the user knows whether the alert has been active. Make sure to use this skill whenever the user asks "what does this alert do", "explain alert X", "walk me through this rule", "how does my [Y] alert work", "is this alert configured correctly", or otherwise asks for an interpretation of an existing alert's configuration. Static explanation only; for diagnosing a specific firing incident, use `signoz-investigating-alerts`.

signoz-creating-dashboards

★ 6

by signoz

Create a new SigNoz dashboard from a natural-language intent: import a curated template (PostgreSQL, Redis, JVM, k8s, hostmetrics, APM, LLM, etc.) when one fits, or build a custom dashboard from scratch with metric / trace / log panels. Make sure to use this skill whenever the user says "create a dashboard for…", "set up monitoring for…", "build me a dashboard…", "I need observability for…", "import a dashboard template", or asks to track / visualize a service, database, cluster, or AI/LLM platform, even if they don't explicitly say "dashboard". Also use it when someone wants to "monitor", "watch", or "see metrics for" a technology and the natural answer is a dashboard.

signoz-managing-views

★ 6

by signoz

Use when the user wants to create, list, get, update, rename, or delete a SigNoz saved Explorer view. Trigger on phrases like "save this query as a view", "save this filter", "bookmark this search", "list my saved views", "show me views for traces/logs/metrics/meter", "rename the X view", "update my saved view to also filter Y", "delete the X view", or any request to manage Explorer saved views, even if they don't say "view" explicitly. Also use when someone wants to share a recurring Explorer query with their team and asks how to "save" or "bookmark" it.

signoz-explaining-dashboards

★ 6

by signoz

Explain what an existing SigNoz dashboard shows in plain operational language: the panels, queries, variables, and what to watch for on each. Make sure to use this skill whenever the user asks "explain this dashboard", "what does my [X] dashboard show", "walk me through the panels", "what should I watch for on this dashboard", or "help me understand this dashboard", or otherwise asks for an interpretation of a dashboard's contents, even if they don't say "explain" explicitly. Also use it when someone is onboarding to a service and wants to understand what its existing observability looks like.