AgentSkillsCN

fleet-agent

带有自动学习和双重内存（NeonDB + ChromaDB）的Context-aware开发助手，适用于AgenticFleet，可智能管理上下文以处理开发工作流。

SKILL.md
--- frontmatter
name: fleet-agent
description: Context-aware development assistant for AgenticFleet with auto-learning and dual memory (NeonDB + ChromaDB). Handles development workflows with intelligent context management.
focus: development, context-management, pattern-learning, code-analysis
triggers:
  - "add an agent"
  - "create a workflow"
  - "DSPy signature"
  - "test code"
  - "memory operations"
  - "code analysis"
  - "pattern extraction"
capabilities:
  - Context-aware block loading (keyword-based)
  - Dual database search (NeonDB structured + ChromaDB semantic)
  - Pattern extraction with detailed code examples
  - Basic code analysis (DSPy signatures, agents, workflows, tools)
  - Session tracking in NeonDB
  - Auto-learning enabled

Fleet Agent

A context-aware development assistant for AgenticFleet that maintains persistent memory across sessions using a hybrid NeonDB + ChromaDB architecture.

Memory Architecture

Dual Storage

  • •ChromaDB (Semantic): Skills, patterns, code snippets with embedding-based search
  • •NeonDB (Structured): Sessions, users, analytics, skill metadata with SQL queries

Context Layers

  1. •

    Core Memory (.fleet/context/core/): Always loaded

    • •project.md: Architecture, conventions, tech stack
    • •human.md: User preferences, communication style
    • •persona.md: Agent guidelines, tone
  2. •

    Topic Blocks (.fleet/context/blocks/): Loaded on demand

    • •project/: commands, conventions, gotchas, architecture
    • •workflows/: git, review
    • •decisions/: ADRs
  3. •

    Skills (ChromaDB + NeonDB): Semantic + structured patterns

Usage Examples

Learn a Pattern

code
/fleet-agent learn --name "add_dspy_agent" --category "agent" --content "Create agent via AgentFactory with DSPyEnhancedAgent wrapper..."

Recall Information

code
/fleet-agent recall "DSPy typed signatures"
/fleet-agent context "add a new agent for web search"

Analyze Code

code
/fleet-agent analyze src/agents/coordinator.py

Session Management

code
/fleet-agent session start
/fleet-agent session status
/fleet-agent session summary "Completed agent creation workflow"

Commands

CommandDescription
learn --name <name> --category <cat> --content <code>Save pattern to both databases
recall <query>Search NeonDB + ChromaDB
context <task>Load relevant context blocks
analyze <file>Analyze code structure
session startStart new session
session statusShow current session
session summary <text>Save session summary
statsShow development metrics

Auto-Learning

Automatically extracts and saves patterns after successful task completion with detailed code examples:

yaml
name: pattern_add_dspy_signature
category: dspy
description: How to create a DSPy signature with TypedPredictor
implementation: |
  class TaskAnalysisOutput(BaseModel):
      complexity: Literal["low", "medium", "high"]

  class TaskAnalysis(dspy.Signature):
      task: str = dspy.InputField(desc="Task to analyze")
      analysis: TaskAnalysisOutput = dspy.OutputField()

Implementation

Main script: .fleet/context/scripts/fleet_agent.py

Invocation: uv run python .fleet/context/scripts/fleet_agent.py <command>

Dependencies: neon_memory.py, chroma_driver.py, memory_loader.py

See Also

  • •memory-system-guide.md: Complete memory system documentation
  • •.fleet/context/MEMORY.md: Memory hierarchy and commands