OpenClawdy

Memory Infrastructure for Autonomous Agents

Give your agent persistent memory that survives sessions. Store facts, preferences, decisions, and learnings - recall them semantically whenever needed. Advanced features include reputation tracking, cross-agent memory pools, and time-travel snapshots.

Installation

openclaw skill install openclawdy

Or add to your agent config:

skills:
  - url: https://openclawdy.xyz/SKILL.md
    name: openclawdy

Authentication

OpenClawdy uses wallet-based authentication. Your agent's wallet address serves as its unique identity - no API keys needed.

Before using memory tools, ensure your agent has a wallet configured. Each wallet gets an isolated memory vault.

---

Core Tools

memory_store

Store information for later retrieval.

Parameters:

• content (required): The information to remember
• type (optional): Category of memory - one of: fact, preference, decision, learning, history, context. Default: fact
• tags (optional): Array of tags for organization

Example:

Store this as a preference: User prefers TypeScript over JavaScript for all new projects

Remember this fact with tags ["project", "tech-stack"]: The current project uses Next.js 14 with PostgreSQL

Response:

{
  "success": true,
  "data": {
    "id": "mem_abc123",
    "content": "User prefers TypeScript over JavaScript",
    "type": "preference",
    "tags": [],
    "createdAt": "2025-02-10T12:00:00Z"
  }
}

---

memory_recall

Retrieve relevant memories using semantic search. Finds memories by meaning, not just keywords.

Parameters:

• query (required): What to search for
• limit (optional): Maximum results to return (1-20). Default: 5
• type (optional): Filter by memory type

Example:

Recall memories about programming language preferences

What do I know about the user's coding style? Limit to 3 results.

Response:

{
  "success": true,
  "data": [
    {
      "id": "mem_abc123",
      "content": "User prefers TypeScript over JavaScript",
      "type": "preference",
      "relevance": 0.95,
      "createdAt": "2025-02-10T12:00:00Z"
    }
  ]
}

---

memory_list

List recent memories without semantic search.

Parameters:

• type (optional): Filter by memory type
• limit (optional): Maximum results (1-100). Default: 20
• offset (optional): Pagination offset. Default: 0

Example:

List my recent memories

Show all preference memories, limit 10

---

memory_delete

Delete a specific memory by ID.

Parameters:

• id (required): The memory ID to delete

Example:

Delete memory mem_abc123

---

memory_clear

Clear all memories in the vault. Use with caution - this is irreversible.

Example:

Clear all my memories (I confirm this action)

---

memory_export

Export all memories as JSON for backup.

Example:

Export all my memories

---

memory_stats

Get usage statistics for your agent.

Example:

Show my memory usage stats

Response:

{
  "success": true,
  "data": {
    "address": "0x1234...",
    "tier": "free",
    "memoriesStored": 150,
    "recallsToday": 45,
    "limits": {
      "maxMemories": 1000,
      "maxRecallsPerDay": 100
    }
  }
}

---

Advanced Tools

memory_reputation

Track which memories lead to good outcomes. Store memories with reputation scores, update based on success/failure, recall memories ranked by proven effectiveness.

Actions:

store_ranked

Store a memory with an initial reputation score.

Parameters:

• action: store_ranked
• content (required): The information to store
• type (optional): Memory type. Default: fact
• reputation (optional): Initial score 0.0-1.0. Default: 0.5

Example:

Store ranked memory: "Use retry logic for API calls" with reputation 0.8

recall_ranked

Retrieve memories sorted by reputation (most effective first).

Parameters:

• action: recall_ranked
• query (required): What to search for

Example:

Recall ranked memories about error handling strategies

Response:

{
  "success": true,
  "data": [
    {
      "id": "mem_xyz",
      "content": "Use exponential backoff for retries",
      "reputation": 0.92,
      "usage_count": 15,
      "success_rate": 0.93
    }
  ]
}

update_reputation

Update a memory's reputation based on outcome.

Parameters:

• action: update_reputation
• memory_id (required): The memory to update
• outcome (required): success, failure, or neutral
• impact (optional): Weight of this outcome (0.0-1.0)

Example:

Update reputation for mem_xyz: outcome was success

---

memory_pool

Cross-Agent Memory Pools - Share knowledge between multiple agents. Create pools, store shared memories, recall from collective intelligence. Perfect for agent teams and swarms.

Actions:

create

Create a new shared memory pool.

Parameters:

• action: create
• pool_name (required): Name for the pool

Example:

Create memory pool: "research-team"

Response:

{
  "success": true,
  "data": {
    "pool_id": "pool_abc123",
    "name": "research-team",
    "created_at": "2025-02-10T12:00:00Z"
  }
}

store

Store a memory in a shared pool.

Parameters:

• action: store
• pool_id (required): The pool ID
• content (required): Information to share
• type (optional): Memory type

Example:

Store in pool pool_abc123: "Found bug in authentication module - fix applied"

recall

Search memories in a shared pool.

Parameters:

• action: recall
• pool_id (required): The pool ID
• query (required): What to search for

Example:

Recall from pool pool_abc123: authentication issues

list

List all accessible pools.

Parameters:

• action: list

Example:

List my memory pools

---

memory_snapshot

Memory Time Travel - Snapshot and restore agent memory states. Debug decisions by viewing past states, compare memory changes, restore to previous checkpoints. Essential for high-stakes agents.

Actions:

create

Create a snapshot of current memory state.

Parameters:

• action: create
• name (required): Descriptive name for the snapshot

Example:

Create memory snapshot: "before-major-update"

Response:

{
  "success": true,
  "data": {
    "snapshot_id": "snap_abc123",
    "name": "before-major-update",
    "memory_count": 150,
    "created_at": "2025-02-10T12:00:00Z"
  }
}

restore

Restore memory state from a snapshot.

Parameters:

• action: restore
• snapshot_id (required): The snapshot to restore
• mode (optional): read_only (view only) or overwrite (replace current). Default: read_only

Example:

Restore snapshot snap_abc123 in read_only mode

list

List all snapshots.

Parameters:

• action: list

Example:

List my memory snapshots

compare

Compare two snapshots or a snapshot with current state.

Parameters:

• action: compare
• snapshot_id (required): First snapshot
• compare_to (optional): Second snapshot ID or current. Default: current

Example:

Compare snapshot snap_abc123 to current state

Response:

{
  "success": true,
  "data": {
    "added": 12,
    "removed": 3,
    "modified": 5,
    "unchanged": 130,
    "diff": [...]
  }
}

---

Memory Types

Type	Use For	Example
fact	Objective information	"Project uses Next.js 14"
preference	User/agent preferences	"User prefers dark mode"
decision	Past decisions made	"Chose PostgreSQL over MongoDB"
learning	Lessons learned	"This API requires auth header"
history	Historical events	"Deployed v2.1 on Jan 15"
context	General context	"Working on e-commerce project"

Best Practices

When to Store

• User states a preference → Store as preference
• Important decision made → Store as decision
• Learned something new → Store as learning
• Key project fact → Store as fact

When to Recall

• Starting a new session → Recall recent context
• Before making suggestions → Check preferences
• Encountering similar problem → Check learnings

Using Reputation

• After successful action → Update with outcome: success
• After failed approach → Update with outcome: failure
• When recalling strategies → Use recall_ranked for proven approaches

Using Pools

• Team of agents working together → Create shared pool
• Knowledge that benefits multiple agents → Store in pool
• Looking for collective wisdom → Recall from pool

Using Snapshots

• Before major changes → Create snapshot
• Debugging unexpected behavior → Compare to past state
• Rolling back mistakes → Restore from snapshot

Example Workflow

# Session 1: User mentions preference
User: "I always want you to use TypeScript"
Agent: [Stores as preference: "User prefers TypeScript for all code"]

# Session 2: New task
User: "Create a new API endpoint"
Agent: [Recalls preferences about coding]
Agent: "I'll create this in TypeScript based on your preference."

# Session 3: Learning from outcome
Agent: [Used retry logic, it worked]
Agent: [Updates reputation: memory_id=mem_xyz, outcome=success]

# Session 4: Making decisions
Agent: [Recalls ranked memories about error handling]
Agent: [Uses highest-reputation approach first]

Pricing

Tier	Memories	Recalls/Day	Pools	Snapshots	Price
Free	1,000	100	1	3	$0
Pro	50,000	Unlimited	10	50	$10/mo
Enterprise	Unlimited	Unlimited	Unlimited	Unlimited	Custom

API Endpoints

Base URL: https://openclawdy.xyz/api

Core Endpoints

Method	Endpoint	Description
POST	/memory/store	Store a memory
POST	/memory/recall	Semantic search
GET	/memory/list	List memories
GET	/memory/{id}	Get specific memory
DELETE	/memory/{id}	Delete memory
GET	/memory/vault	Export all
DELETE	/memory/vault	Clear vault
GET	/agent/stats	Usage stats

Reputation Endpoints

Method	Endpoint	Description
POST	/memory/reputation/store	Store with reputation
POST	/memory/reputation/recall	Recall by reputation
POST	/memory/reputation/update	Update reputation

Pool Endpoints

Method	Endpoint	Description
POST	/memory/pool/create	Create pool
POST	/memory/pool/store	Store in pool
POST	/memory/pool/recall	Recall from pool
GET	/memory/pool/list	List pools

Snapshot Endpoints

Method	Endpoint	Description
POST	/memory/snapshot/create	Create snapshot
POST	/memory/snapshot/restore	Restore snapshot
GET	/memory/snapshot/list	List snapshots
POST	/memory/snapshot/compare	Compare snapshots

Authentication Headers

All requests require wallet signature authentication:

X-Agent-Address: 0x...      # Your wallet address
X-Agent-Signature: 0x...    # Signed message
X-Agent-Timestamp: 123...   # Unix timestamp (ms)

Message format to sign:

OpenClawdy Auth
Timestamp: {timestamp}

ACP Integration

OpenClawdy is available on the Agent Commerce Protocol (ACP). Other agents can purchase memory services directly:

Service	Fee	Description
memory_store	$0.01	Store a memory
memory_recall	$0.02	Semantic search
memory_reputation	$0.02	Reputation operations
memory_pool	$0.03	Pool operations
memory_snapshot	$0.05	Snapshot operations

Support

• Website: https://openclawdy.xyz
• Twitter: @openclawdy
• ACP Agent: OpenClawdy Memory

License

MIT