feat(pipeline): implement Pipeline DSL system for automated workflows

Add complete Pipeline DSL system including:
- Rust backend (zclaw-pipeline crate) with parser, executor, and state management
- Frontend components: PipelinesPanel, PipelineResultPreview, ClassroomPreviewer
- Pipeline recommender for Agent conversation integration
- 5 pipeline templates: education, marketing, legal, research, productivity
- Documentation for Pipeline DSL architecture

Pipeline DSL enables declarative workflow definitions with:
- YAML-based configuration
- Expression resolution (${inputs.topic}, ${steps.step1.output})
- LLM integration, parallel execution, file export
- Agent smart recommendations in conversations

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

crates/zclaw-pipeline/src/actions/skill.rs

@@ -0,0 +1,20 @@
+//! Skill execution action
+
+use std::collections::HashMap;
+use serde_json::Value;
+
+use super::ActionError;
+
+/// Execute a skill by ID
+pub async fn execute_skill(
+    skill_id: &str,
+    input: HashMap<String, Value>,
+) -> Result<Value, ActionError> {
+    // This will be implemented by injecting the skill registry
+    // For now, return an error indicating it needs configuration
+
+    Err(ActionError::Skill(format!(
+        "Skill '{}' execution requires skill registry configuration",
+        skill_id
+    )))
+}