Agent Building Agent Skills

Build applications that programmatically interact with GitHub Copilot using an SDK that wraps the Copilot CLI via JSON-RPC, providing session management, custom tools, hooks, MCP server integration, and streaming across Node.js, Python, Go, and .NET.

Enables compact, machine-native agent-to-agent messaging using a shared vocabulary of 340+ 2-character atoms across 7 domains, achieving 3x compression over natural language.

Guides the creation of MCP servers that enable LLMs to interact with external services through well-designed tools.

Designs and governs recursive self-improvement loops where an agent mines its own failures and proposes edits to its own harness, prompts, or workflow, covering acceptance gates, diversity preservation, and the optimization ladder.

Polls a local relay for animation-refinement jobs from the Timeline Inspector, posts suggestions or applies changes to transition code.

Analyze suspected malware through static, dynamic, and behavioral techniques, including IOC extraction, YARA or Sigma rules, sandboxing, and anti-analysis behavior detection.

Analyzes prompt injection, retrieval poisoning, memory contamination, planner drift, and tool-boundary abuse in agentic systems, mapping trust boundaries and proving exploit chains.

Compresses conversation transcripts into prioritized notes using an LLM observer, consolidates them when they grow, and recovers any missed sessions without a database or vector store.

Set up GPU profiling, tracing, and monitoring for inference workloads using vLLM, SGLang, PyTorch, and dstack services via the Graphsignal Profiler sidecar.

Delegates tasks to specialized AI agents running in parallel via the Box0 platform, enabling code review, security checks, research, and documentation.

Provides a persistent, queryable virtual filesystem backed by SurrealDB for AI agents, with a Rust core and a Python agent interface.

Connects AI agents to SurrealDB via built-in MCP (SurrealDB 3.1+) or standalone surrealmcp for database operations.

Find authoritative guidance for installing, configuring, operating, securing, and troubleshooting OpenClaw, including channels, model providers, Gateway operations, tools, plugins, automation, nodes, multi-agent routing, and CLI errors. Use for any question or maintenance task involving an OpenClaw installation.

Guides designing Dify workflows, covering node types, design patterns, templates, and best practices.

Quick reference for the Agent Farm CLI, covering tower, dashboard, builder management, and configuration commands.

Installs and configures ktx, the open-source context layer for data agents, including database connections, embeddings, agent integration, and context ingestion.

Provides guidelines for building with Botpress's Agent Development Kit (ADK), covering primitives, project structure, CLI usage, and documentation lookups.

Short alias that routes invocations to the vc-phase-loop skill for hands-off completion.

Scaffolds a coder-eval task suite in a repository by scanning for testable components, writing one real task, and validating it.

Mines SpecStory coding histories from any agent into a persistent corpus, surfaces reproducible workflows with corroborated evidence, and interactively forges chosen ones into skills installed across agent harnesses.

Generate A2UI 0.8 protocol compliant UI code for agent-driven interfaces, including JSONL messages for surface updates, data model updates, and rendering.

Spawns GLM-5 powered teammates with thinking mode for coding, review, testing, planning, and research tasks.

Adds a persistent pattern or rule that Ralph will remember and apply to future stories.

Manages personal local Agent Skill files by detecting reusable material, searching for similar skills, and creating or updating SKILL.md folders after user approval.

Automates the full lifecycle of agent skills: extracts reusable constraints from user feedback, merges preferences with version bumps, and retrieves relevant skills for new tasks.

Fetches and analyzes LangSmith execution traces to debug LangChain and LangGraph agents, investigating errors, tool calls, and performance.

Builds RAG and agent applications with LlamaIndex, covering installation, LlamaParse, and LlamaAgents.

Checks evidence about an unfamiliar autonomous agent before delegation, verifies signed Agent Guild passports, and returns a bounded hire, caution, or avoid recommendation without taking consequential action.

Provides 25 paid HTTP endpoints on Base mainnet that bill agents per call in USDC for web search, AI analysis, crypto and stock data, SEC filings, company intelligence, news, sentiment scoring, and a macro dashboard, returning structured JSON.

Designs or reviews Agentforce agent actions, covering Flow, Apex invocable, and prompt-template actions, including naming, input/output contracts, confirmation, and error behavior.

Watches conversations continuously and compresses them into prioritized notes, consolidating and recovering missed sessions with multiple redundancy layers.

Coordinates multiple AI agents through a shared room: shared memory, task claiming, conflict detection, and destination tracking.

Defines a protocol for agent-to-agent discovery, authentication, and synchronization in decentralized networks, covering routing, handshakes, relays, and mesh governance.

Defines the architecture and orchestration primitives for multi-agent teams, covering role allocation, conflict resolution, reward routing, and the operational lifecycle of agent collectives.

Configures Rei Qwen3 Coder as a model provider, including setup, model switching, and troubleshooting 403 errors.

Runs an autonomous optimization loop that iteratively improves an artifact against an objective and evaluator using Hypothesis Tree Refinement, with subagent executors in isolated git worktrees.