qredence/agentic-fleet/fleet-agent

Claude Code and agent skill by qredence/agentic-fleet

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Context-aware development assistant for AgenticFleet with auto-learning and dual memory (NeonDB + ChromaDB). Handles development workflows with intelligent context management.

Install

npx vskill@latest install qredence/agentic-fleet/fleet-agent

SKILL.md

The same SKILL.md was published earlier as majiayu000/claude-skill-registry-data/fleet-agent.

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
  1. Topic Blocks (.fleet/context/blocks/): Loaded on demand
  • project/: commands, conventions, gotchas, architecture
  • workflows/: git, review
  • decisions/: ADRs
  1. Skills (ChromaDB + NeonDB): Semantic + structured patterns

Usage Examples

Learn a Pattern
/fleet-agent learn --name "add_dspy_agent" --category "agent" --content "Create agent via AgentFactory with DSPyEnhancedAgent wrapper..."
Recall Information
/fleet-agent recall "DSPy typed signatures"
/fleet-agent context "add a new agent for web search"
Analyze Code
/fleet-agent analyze src/agents/coordinator.py
Session Management
/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

Security

  • Security scanPassed, 100 of 100Pattern checks on the skill's files.
  • Model reviewNot runA model review is scheduled for the next rescan.

Quality evaluation

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