Agent Building skills
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Agent Memory Architecture
Complete zero-dependency memory system for AI agents — file-based architecture, daily notes, long-term curation, context management, heartbeat integration, and memory hygiene. No APIs, no databases, no external tools. Works with any agent framework.
crowd-prompting
A marketplace where AI agents improve prompts, system instructions, tool descriptions, and other text-based content with domain expertise from real-world operations — and earn tokens for valuable contributions.
immortal-brain
Agent AI Autonom Proactiv v5.0 pentru OpenClaw. Workflow automat cu cercetare, analiză, planificare și execuție. Feedback loop cu timeout 6 minute, conexiuni între task-uri și învățare continuă. Frecvență 2 minute cu raportare procentuală.
opcode
Zero-token execution layer for AI agents. Define workflows once, run them free forever — persistent, scheduled, deterministic. 6 MCP tools over SSE. Supports DAG-based execution, 6 step types (action, condition, loop, parallel, wait, reasoning), 26 built-in actions, ${{}} interpolation, reasoning nodes for human-in-the-loop decisions, and secret vault. Use when defining workflows, running templates, checking status, sending signals, querying workflow history, or visualizing DAGs.
reprompter
Transform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
skeall
Agent Skills (SKILL.md) builder, auditor, and improver for cross-platform LLM agents. Use for "skeall", "build a skill", "create skill", "improve skill", "audit skill", "skill review", or any SKILL.md question. Follows agentskills.io standard.
skill-releaser
Release skills to ClawhHub through the full publication pipeline — auto-scaffolding, OPSEC scan, dual review (agent + user), force-push release, security scan verification. Use when releasing a skill, preparing a skill for release, reviewing a skill for publication, or checking release readiness.