Loading...
Loading...
Found 13,195 Skills
Expert knowledge of the Hermes Agent ecosystem, skills, plugins, tools, integrations, and deployment patterns for building and extending AI agents
Run an Anthropic Claude Managed Agent — a cloud agent harness (container + filesystem + tools), the cloud counterpart of the local wasm-agent runtime
Product Requirement Prompts (PRP) methodology for AI-assisted development with validation loops and autonomous execution
Check if the development environment is configured properly; if not, first confirm the office location (Chongqing/Beijing), identify the current operating system, system tools, package managers, and eliteforge-* skill environment variable declarations, report them categorized as missing_required, missing_conditional, optional_unset, then attempt to automatically install essential commands and complete configurations such as hosts, Git global settings, Git HTTPS, npm/pip private sources, and pipx packages. Use this skill when the user mentions "check environment configuration", "prepare development environment", "missing commands/hosts/private sources/Git configurations/package management tools/skill environment variables". Trigger threshold: Only use this skill when the user explicitly states that the current project complies with the "璀璨工坊规范" (Bright Workshop Specification) or "eliteforge specification".
Guides CI/CD for agent skills repositories and skill packages—pipeline design (build, test, validate, package), GitHub Actions for PR checks and release promotion, environment gates, secrets hygiene (no secrets in repo), skill-creator integration (quick_validate.py, package_skill.py), .skill artifact strategy, rollback, and operational runbooks for skill releases. Use when the user mentions CI/CD, CI/CD engineer, pipeline design, GitHub Actions, skill validation CI, package skills, release pipeline, deploy skills, PR checks, continuous integration, or skill release workflow—not application-only CI without skill packaging (devops), pre-flight plan go/no-go (build-validator), IDP or golden paths (platform-engineer), org-wide SLO and error-budget programs without pipeline ownership (site-reliability-engineer), or portfolio catalog governance without pipeline YAML (ai-skill-manager).
Create and manage agent graphs — directed graphs of configs connected by edges with handoff logic. Use when building multi-agent workflows where configs route to each other.
Give your AI agents capabilities through tools (function calling). Helps you identify what your AI needs to do, create tool definitions, and attach them to AI Config variations.
Agentic and machine-to-machine payments on Stellar. Covers x402 (HTTP 402 paid APIs via OZ Channels facilitator, fee-sponsored clients) and MPP (Machine Payments Protocol) in both Charge mode (per-request Soroban SAC) and Channel mode (off-chain commits, high-frequency). Defaults to USDC (SEP-41 SAC) on `stellar:testnet`/`stellar:pubnet` (CAIP-2). Use when selling a paid API to AI agents, building an x402 client, or designing a payment-channel architecture for high-frequency agent traffic.
Use this skill when pricing, ranking, or researching X/Twitter KOLs for a creator marketing campaign, especially when the user provides handles, asks for batch KOL analysis, wants outreach recommendations, or wants an agent-native version of the KOL Pricing framework. Prefer UnifAPI MCP tools for public X data, then run the deterministic pricing workflow before drafting outreach.
Use Po Once's organization-scoped agent API to list connected accounts, upload media, create content, schedule or publish posts, inspect status, and delete eligible scheduled posts through a local helper script.
Chinese Git Commit Skill. Analyze changes and generate Chinese conventional commit messages. Triggered when the user says "submit", "commit", "submit code", "submit changes", or "/commit-zh". Executed entirely by the main agent, no subagents used.
Manages and orchestrates prompts in Agent Platform. Use when you need to create, list, retrieve, version, or delete managed prompts in Agent Platform. Don't use for model training, model deployment to endpoints, or managing non-Agent Platform prompts.