langchain-architecture
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.
planning-with-files
Implements Manus-style file-based planning for complex tasks. Creates task_plan.md, findings.md, and progress.md. Use when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls.
Full skill instructions
Work like Manus: Use persistent markdown files as your "working memory on disk."
When using this skill:
${CLAUDE_PLUGIN_ROOT}/templates/task_plan.md, findings.md, progress.md) should be created in your project directory — the folder where you're working| Location | What Goes There |
|---|---|
Skill directory (${CLAUDE_PLUGIN_ROOT}/) | Templates, scripts, reference docs |
| Your project directory | task_plan.md, findings.md, progress.md |
This ensures your planning files live alongside your code, not buried in the skill installation folder.
Before ANY complex task:
task_plan.md in your project — Use templates/task_plan.md as referencefindings.md in your project — Use templates/findings.md as referenceprogress.md in your project — Use templates/progress.md as referenceNote: All three planning files should be created in your current working directory (your project root), not in the skill's installation folder.
Context Window = RAM (volatile, limited)
Filesystem = Disk (persistent, unlimited)
→ Anything important gets written to disk.
| File | Purpose | When to Update |
|---|---|---|
task_plan.md | Phases, progress, decisions | After each phase |
findings.md | Research, discoveries | After ANY discovery |
progress.md | Session log, test results | Throughout session |
Design LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.
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