The hard part of LLM agents is not building function calling, skills, code interpreter, and document tools individually -- it is assembling them into a system that selects the right tool, writes code when needed, decomposes tasks, verifies results, and resists prompt injection. This post organizes the key papers into six engineering decisions: function calling reliability, tool/skill selection, code-as-action, multi-step planning, skill systems, and safety plus document generation.
Skill paths are almost always runtime-specific. AGENTS.md is the reliable way to share rules across agents. Put personal reusable capabilities in each agent's supported global directory; put project workflows inside the repo.
gstack is Garry Tan's open-source Claude Code skills toolkit. Its 20 specialized skills transform a solo developer into an entire engineering team — automating everything from product planning and design review to code review, QA, and deployment.
Skills are AgentSkills-compatible SKILL.md folders with a 6-tier loading priority. ClawHub is the public marketplace. Sub-agents can nest up to 5 levels deep.
Global skills live in ~/.claude/skills/, but they go missing in new sessions or the Desktop App? The problem usually isn't a missing file — it's that the skill descriptions aren't being loaded into context. This post clarifies the CLI vs Desktop App differences, the role of settings.json, and the most reliable fix.