AI Agents Marketplace
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golang-code-style
**Orchestration mode:** Fan out the sub-agents described in the "Parallelizing Code Style Reviews" section, each covering an independent style concern, when reviewing code style across a large codebase, and merge their findings. On Claude Code, use `ultracode` to opt into multi-agent orchestration explicitly. > **Community default.** A company skill that explicitly supersedes `samber/cc-skills-golang@golang-code-style` skill takes precedence. # Go Code Style Style rules that require human judgment — linters
agent-device
# agent-device For a normal app-driving task, start immediately. Do not probe first with `--help`, `--version`, `devices`, `appstate`, `snapshot`, or `screenshot`: ```bash agent-device open <app> --foreground ``` That starts the session and returns the initial interactive snapshot with `@refs`. Loop: act with `press|click|fill|longpress <target> ... --settle`, `scroll <direction> --settle`, or `back --settle`; continue from the printed diff, verify the named expectation (`wait text "..."`, `is`, `get`, or `
agent-platform-skill-registry
# Skill Registry This skill provides instructions for interacting with the **Skill Registry** on the Gemini Enterprise Agent Platform. ## Core Capabilities - **Skill Discovery** - Query the registry to easily search, list, get specific skills, and inspect revision histories. - **Skill Lifecycle Management** - Upload, update, or permanently delete skills. - **Operation Monitoring** - Utility to check the completion status of long-running state changes (LROs). - **Generate Skill** - Automate the initial scaff
emblem-market-research
# Emblem Market Research Crypto market intelligence powered by **EmblemAI**. Real-time data from CoinGecko, CoinGlass, Birdeye, and Nansen — trending tokens, derivatives analytics, on-chain smart money tracking, and token deep dives. **Requires**: `npm install -g @emblemvault/agentwallet` --- ## What This Skill Can Do | Capability | Tools Used | |-----------|------------| | Trending tokens (all chains) | `getTrendingCoins`, `birdeyeTrendingTokens` | | Token price lookup | `getCryptoPrice`, `searchCryptoByNa
emblem-memecoin-scout
# Emblem Memecoin Scout Memecoin discovery and risk assessment powered by **EmblemAI**. Real-time new token alerts, trending memecoins, rug-pull detection, holder analysis, and smart money tracking across Solana, Base, and Hedera. **Requires**: `npm install -g @emblemvault/agentwallet` --- ## What This Skill Can Do | Capability | Tools Used | Chains | |-----------|------------|--------| | Pump.fun new token launches | `getPumpFunTokens` | Solana | | LaunchLab / Bonk.fun new tokens | `discoverLaunchLabTokens
emblem-token-swap
# Emblem Token Swap Guided token swapping powered by **EmblemAI**. Swap tokens on Solana, Ethereum, Base, BSC, Polygon, and Hedera with automatic routing. Cross-chain bridging via ChangeNow. **Requires**: `npm install -g @emblemvault/agentwallet` --- ## What This Skill Can Do | Chain | Quote Tool | Swap Tool | Balance Tool | Token Search | |-------|-----------|-----------|-------------|--------------| | Solana | `splBuyIntent` (quote mode) | `splBuyIntent` (swap mode) | `solanaBalances` | `findSolanaSwapTok
agent-platform-prompt-management
## Usage Guide To use this skill effectively: 1. **Execute Operations via Python**: Run the Python snippets below using `run_command` in the execution environment to manage prompts in Agent Platform on behalf of the user. Do not delegate execution to the user or claim lack of access once approved. 2. **No File System Search**: Do not try to find Python files or scripts on the file system for these operations. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands or scripts on behalf of the
agent-platform-rag-engine-management
# Agent Platform RAG Engine Management This skill provides instructions on how to interact with Agent Platform RAG Engine using the Agent Platform Python SDK. You MUST use the `vertexai` Python SDK to perform RAG Engine operations, rather than raw REST calls or MCP tools, because this code is intended to be run by external clients. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands or scripts on behalf of the user, you must adhere to the following safety tiers based on the action reques
agent-platform-tuning-management
# Agent Platform Tuning Management This skill provides instructions on how to manage GenAI Tuning Jobs using the Agent Platform Python SDK. Use this skill when a user wants to check the status of their tuning runs, find an active tuning job, or cancel a job that is running too long. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested: 1. **Tier R: Read-only (`list`, `get`)** * **Rule**: No
agent-platform-inference
# Agent Platform GenAI Inference Skill This skill provides instructions for authenticating and connecting to Google Cloud Agent Platform to use Generative AI models. It covers: * **First-Party publisher models** (Gemini) — section 2. * **Third-Party publisher models** (OpenMaaS: Llama, DeepSeek, Qwen, etc.) — section 3. * **Custom endpoints** (any model on a numeric `projects/.../endpoints/<id>` resource — tuned Gemini models, OSS LLMs self-deployed from Model Garden via the `agent-platform-deploy` skill, a
agent-platform-endpoint-management
# Agent Platform Endpoint Management ## Overview This skill provides procedural knowledge for managing Agent Platform Endpoints. Endpoints are logical serving hosts that provide a stable URL for online predictions. You must create an endpoint before you can deploy a model to it. ## Safety & Confirmation Tiers (CRITICAL) Before executing any commands on behalf of the user, you MUST adhere to the following safety tiers based on the action requested: 1. **Tier R: Read-only (`list`, `describe`, `get`)** * No co
agent-development
# Agent Development for Claude Code Plugins ## Overview Agents are autonomous subprocesses that handle complex, multi-step tasks independently. Understanding agent structure, triggering conditions, and system prompt design enables creating powerful autonomous capabilities. **Key concepts:** - Agents are FOR autonomous work, commands are FOR user-initiated actions - Markdown file format with YAML frontmatter - Triggering via description field with examples - System prompt defines agent behavior - Model and c
agent-platform-alert-configuration
# Agent Platform Alert Configuration ## Critical Steps ### 1. Safety & Confirmation Tiers (CRITICAL) Before executing any commands or writing configurations on behalf of the user, you MUST adhere to the following safety tiers based on the action requested: 1. **Tier R: Read-only (`check_telemetry.py` / `gather_agent_info.py`)** * **Rule**: No confirmation needed. You may execute these scripts immediately to inspect telemetry status or gather agent configuration details. 2. **Tier B: Billing & Resource Creat
literature-review
# Literature Review Conduct deep literature reviews through multi-perspective dialogue and systematic search. ## Input - `$0` — Research topic or question - `$1` — Optional: specific focus or angle ## References - Multi-perspective dialogue prompts (STORM): `~/.claude/skills/literature-review/references/dialogue-prompts.md` - Literature review workflow (AgentLaboratory): `~/.claude/skills/literature-review/references/review-workflow.md` ## Scripts (from literature-search skill) ```bash # Search Semantic Sch
test-guard
# Test Guard You are reviewing generated or changed test code before it ships. Enforce the rules below after the first test-writing pass and before the tests are presented, committed, or merged. Be a sharp reviewer, not a pedantic one: flag what wastes maintenance effort or hides real bugs, ignore cosmetic preferences. These rules exist because coding agents over-generate tests. The common failure modes: mock-heavy unit tests that assert implementation details, near-duplicate test bodies that differ by one
agent-platform-troubleshooting
# Agent Platform Troubleshooting > [!IMPORTANT] **CRITICAL RULE**: You MUST ONLY use the reference files located > in this skill's `references/` directory (e.g., `references/field-manual.md`, > `references/known-issues.md`, `references/agent-registry.md`). Do NOT search > for or read other external playbooks or files outside this directory. The > files in the local `references/` directory contain workspace-specific fixes > and are the sole source of truth for this troubleshooting session. Diagnose issues ac
Tavily Search
Search the public web through Tavily and return structured results with URLs and snippets. Use when an agent needs current information, source discovery, link lookup, news or finance search, or a fallback for unavailable built-in web search. Do not use for private or authenticated pages.
agentx
# 🌟 AgentX The Starchild community forum. **Script skill** — call the functions in `core.skill_tools.agentx` from bash and read the returned JSON. Auth is automatic (container JWT); no API key needed. Read this file **before** the first call to get function signatures and posting rules. ## How to call ```bash python3 -c "from core.skill_tools import agentx; import json; print(json.dumps(agentx.list_posts(sort='hot')))" ``` Every function returns a dict: `{"success": true, ...}` or `{"success": false, "erro
agent-fs
# agent-fs CLI agent-fs is an agent-first filesystem with full versioning, full-text search (FTS5), and semantic search. It provides a CLI that outputs JSON, making it ideal for agent workflows. Files are organized in drives within orgs. ## Storage Backends agent-fs stores file bytes in a pluggable storage backend. The durable value — version history, comments, and search — lives in SQLite and works identically on every backend. | Backend | Setup | Versioning tier | `signed-url` | |---------|-------|-------