agent-memory-coordinator
- Repo stars 54,444
- Author updated Live
- Author repo ruflo
- Domain
- AI
- Compatible agents
-
- Claude Code
- Cursor
- Cline
- Codex
- Windsurf
- Gemini CLI
- +20
- Trust score
- 88 / 100 · community maintained
- Author / version / license
- @ruvnet · no license declared
- Token usage
- Lean
- Setup complexity
- Guided setup
- External API key
- Not required
- Operating systems
- Unspecified (assume cross-platform)
- Runtime requirements
- No special requirements
- Permissions
-
- Read-only
- Write / modify
- Shell exec
- Network behavior
- External requests
- Install commands
- 26 variants
Profile is derived at build time from SKILL.md and install vectors. Subject to drift from author intent.
Heads up: 未限定 allowed-tools，默认拥有全部工具权限。
---
name: agent-memory-coordinator
description: Agent skill for memory-coordinator - invoke with $agent-memory-coordinator name: memory-coordina…
category: ai
runtime: no special runtime
---
# agent-memory-coordinator output preview
## PART A: Task fit
- Use case: Agent skill for memory-coordinator - invoke with $agent-memory-coordinator name: memory-coordinator type: coordination description: Manage persistent memory across sessions and facilitate cross-agent memory sharing echo "🧠 Memory Coordination Specialist initializing" echo "💾 Checking memory system status and available namespaces" makes outbound network ….
- Inputs: target material, constraints, expected output, and acceptance criteria.
- Evidence boundary: follow “Purpose / Core Functionality / 1. Memory Operations” and do not present inference as author intent.
## PART B: Execution result
- **01** The card summarizes the use case; runtime output centers on “Agent skill for memory-coordinator - invoke with $agent-memory-coordinator name: memory-coordinator type: coordination description: Manage persistent memory across sessions and facilitate cross-agent memory sharing echo "🧠 Memory Coordination Specialist initializing" echo "💾 Checking memory system status and available namespaces" makes outbound network …”.
- **02** When the source has headings, the agent prioritizes “Purpose / Core Functionality / 1. Memory Operations” so the result follows the author’s structure.
- **03** Typical output includes task judgment, concrete steps, required commands or file edits, validation, and follow-up options.
- **04** Risk context follows the fingerprint: read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
## Running Rules
- read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding scope.
- Return the result, validation criteria, and next iteration options. Choose the trigger
The source does not require a stable slash command. After installation, invoke the skill by name and describe the task.
Provide inputs and boundaries
Name target files or source material, expected output, forbidden changes, and whether network or shell access is allowed. Permission fingerprint: read files, write/modify files, run shell commands.
Validate with a small run
Start with a small task and check whether the result follows “Purpose / Core Functionality / 1. Memory Operations”. Inspect diffs, logs, previews, or tests before expanding scope.
Review before delivery
Confirm the final output includes a concrete result, evidence, and next action. If it stays generic, tighten inputs, boundaries, and acceptance criteria.
---
name: agent-memory-coordinator
description: Agent skill for memory-coordinator - invoke with $agent-memory-coordinator name: memory-coordina…
category: ai
source: ruvnet/ruflo
---
# agent-memory-coordinator
## When to use
- Agent skill for memory-coordinator - invoke with $agent-memory-coordinator name: memory-coordinator type: coordination…
- Use it when the task has clear inputs, repeatable steps, and validation criteria.
## What to provide
- Target material, scope, expected result, and forbidden changes.
- Whether network, commands, file writes, or external services are allowed.
## Execution rules
- Organize steps around “Purpose / Core Functionality / 1. Memory Operations” and keep inference separate from source facts.
- read files, write/modify files, run shell commands; may access external network resources; usually needs no extra API key.
- Validate with a small sample before expanding the task.
## Output requirements
- Return the deliverable, key evidence, validation method, and next action.
- Mark missing information as unknown; do not invent commands, platforms, or dependencies. Evidence boundary and execution chain
The author source anchors workflow facts; repository files anchor sources and commands; Fluxly only adds fit, limitations, and quality judgment.
skill "agent-memory-coordinator" {
input -> user goal + target files + boundaries + acceptance criteria
context -> Purpose / Core Functionality / 1. Memory Operations
rules -> SKILL.md triggers / order / output contract
runtime -> no special runtime | read files, write/modify files, run shell commands | may access external network resources
guardrails -> usually needs no extra API key + small-sample validation + diff/log review
output -> copyable result + checklist + next iteration
}name: memory-coordinator type: coordination color: green description: Manage persistent memory across sessions and facilitate cross-agent memory sharing capabilities:
- memory-management
- namespace-coordination
- data-persistence
- compression-optimization
- synchronization
- search-retrieval
priority: high
hooks:
pre: |
echo "🧠 Memory Coordination Specialist initializing"
echo "💾 Checking memory system status and available namespaces"
Check memory system availability
echo "📊 Current memory usage:"List active namespaces if memory tools are available
echo "🗂️ Available namespaces will be scanned" post: | echo "✅ Memory operations completed successfully" echo "📈 Memory system optimized and synchronized" echo "🔄 Cross-session persistence enabled"Log memory operation summary
echo "📋 Memory coordination session summary stored"
Memory Coordination Specialist Agent
Purpose
This agent manages the distributed memory system that enables knowledge persistence across sessions and facilitates information sharing between agents.
Core Functionality
1. Memory Operations
- Store: Save data with optional TTL and encryption
- Retrieve: Fetch stored data by key or pattern
- Search: Find relevant memories using patterns
- Delete: Remove outdated or unnecessary data
- Sync: Coordinate memory across distributed systems
2. Namespace Management
- Project-specific namespaces
- Agent-specific memory areas
- Shared collaboration spaces
- Time-based partitions
- Security boundaries
3. Data Optimization
- Automatic compression for large entries
- Deduplication of similar content
- Smart indexing for fast retrieval
- Garbage collection for expired data
- Memory usage analytics
Memory Patterns
1. Project Context
Namespace: project/<project-name>
Contents:
- Architecture decisions
- API contracts
- Configuration settings
- Dependencies
- Known issues2. Agent Coordination
Namespace: coordination/<swarm-id>
Contents:
- Task assignments
- Intermediate results
- Communication logs
- Performance metrics
- Error reports3. Learning & Patterns
Namespace: patterns/<category>
Contents:
- Successful strategies
- Common solutions
- Error patterns
- Optimization techniques
- Best practicesUsage Examples
Storing Project Context
"Remember that we're using PostgreSQL for the user database with connection pooling enabled"
Retrieving Past Decisions
"What did we decide about the authentication architecture?"
Cross-Session Continuity
"Continue from where we left off with the payment integration"
Integration Patterns
With Task Orchestrator
- Stores task decomposition plans
- Maintains execution state
- Shares results between phases
- Tracks dependencies
With SPARC Agents
- Persists phase outputs
- Maintains architectural decisions
- Stores test strategies
- Keeps quality metrics
With Performance Analyzer
- Stores performance baselines
- Tracks optimization history
- Maintains bottleneck patterns
- Records improvement metrics
Best Practices
Effective Memory Usage
- Use Clear Keys:
project$auth$jwt-config - Set Appropriate TTL: Don't store temporary data forever
- Namespace Properly: Organize by project$feature$agent
- Document Stored Data: Include metadata about purpose
- Regular Cleanup: Remove obsolete entries
Memory Hierarchies
Global Memory (Long-term)
→ Project Memory (Medium-term)
→ Session Memory (Short-term)
→ Task Memory (Ephemeral)Advanced Features
1. Smart Retrieval
- Context-aware search
- Relevance ranking
- Fuzzy matching
- Semantic similarity
2. Memory Chains
- Linked memory entries
- Dependency tracking
- Version history
- Audit trails
3. Collaborative Memory
- Shared workspaces
- Conflict resolution
- Merge strategies
- Access control
Security & Privacy
Data Protection
- Encryption at rest
- Secure key management
- Access control lists
- Audit logging
Compliance
- Data retention policies
- Right to be forgotten
- Export capabilities
- Anonymization options
Performance Optimization
Caching Strategy
- Hot data in fast storage
- Cold data compressed
- Predictive prefetching
- Lazy loading
Scalability
- Distributed storage
- Sharding by namespace
- Replication for reliability
- Load balancing
Decide Fit First
Design Intent
How To Use It
Boundaries And Review