qredence/fleet-agent
.fleet/context/system/fleet-agent/SKILL.md
Context-aware development assistant for AgenticFleet with auto-learning and dual memory (NeonDB + ChromaDB). Handles development workflows with intelligent context management.
$ install --global
skillsauthnpx skillsauth add qredence/agentic-fleet fleet-agentInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Last scanned: Apr 11, 2026, 8:27 PM4.6s1 file scanned
SKILL.md
- 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
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
-
Core Memory (
.fleet/context/core/): Always loadedproject.md: Architecture, conventions, tech stackhuman.md: User preferences, communication stylepersona.md: Agent guidelines, tone
-
Topic Blocks (
.fleet/context/blocks/): Loaded on demandproject/: commands, conventions, gotchas, architectureworkflows/: git, reviewdecisions/: ADRs
-
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
| Command | Description |
| ------------------------------------------------------- | ------------------------------ |
| 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 start | Start new session |
| session status | Show current session |
| session summary <text> | Save session summary |
| stats | Show development metrics |
Auto-Learning
Automatically extracts and saves patterns after successful task completion with detailed code examples:
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
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