ActingWeb Memory
by @gregertw
Stores and retrieves personal preferences, decisions, and context across conversations using ActingWeb Personal AI Memory via MCP. Activates when the user me...
clawhub install managing-actingweb-memoryπ About This Skill
name: managing-actingweb-memory description: Stores and retrieves personal preferences, decisions, and context across conversations using ActingWeb Personal AI Memory via MCP. Activates when the user mentions remembering things, recalling past decisions, saving information for later, personalized recommendations, shared context with other people, controlling connected devices, or anything benefiting from long-term memory. Also activates when personal context would improve the response including trip planning, meeting prep, purchase decisions, diet and health topics, or any request where knowing user history and preferences matters. user-invocable: false
ActingWeb Memory System
You have access to ActingWeb Personal AI Memory β a persistent, cross-session memory system connected via MCP. It stores personal facts, preferences, and decisions that survive between conversations.
If you're new to this user or unsure about capabilities, call how_to_use() once to get a personalized guide with account status, memory statistics, and examples. This is a heavy call β use it at the start of your first interaction, not every conversation.
Setup
> If memory tools are already working, skip this. See setup guide for first-time setup or credential recovery.
1. Search Before Responding
This is the most important behavior. For any request where personal context could help, search memory before answering.
When to search:
How to search well:
search(query="coffee preferences"), not long sentencessearch(last_n=5) or search(recency_days=7)See memory best practices for retrieval patterns and interpreting search results.
2. Save Memories
When the user reveals something worth remembering, offer to save it. Focus on durable, decision-level information.
Good candidates to save:
How to save well:
save(preview=true) to show the user what would be saved before committingAuto-categorization: Memories are automatically categorized into the right type based on content. Call types() to see available categories. You don't need to specify a type unless you want to override the default.
See memory best practices for detailed guidance on writing effective memories.
3. Attribution
When a memory influences your response, mention it naturally: *"Since you prefer double Americanos..."* or *"Based on your note that the CTO opposes outsourcing..."*. For complex responses drawing on many memories, mention just the 1β2 most impactful ones.
4. Memory Maintenance
If the user says something that contradicts a saved memory, surface it: *"I have saved that you prefer X β has that changed?"* Offer to update or delete outdated memories.
If a response would benefit from context the user hasn't saved, suggest filling the gap. If a pattern of unsaved preferences emerges, suggest creating a custom category.
Working with specific memories:
memory_type:item_id (e.g., memory_food:1, memory_travel:3)get(), update(), and delete()get() returns a web dashboard URL for each memory β share with the user if they want to view or edit in the web interfaceget(ids=[...]), delete(ids=[...]), and save(items=[...]) for working with multiple memories at onceAvailable Tools
> Tool names below are shown without a server prefix. Depending on your MCP configuration, you may need to prefix these with your configured server name (e.g., actingweb:search instead of search).
Personal Memory:
search() β Find memories by keyword, semantic query, or browse by recency (last_n, recency_days)get() β Retrieve memory details by ID (single or batch), includes web dashboard URLssave() β Store new memories (single or batch, auto-categorized). Use preview=true to preview firstupdate() β Update an existing memory by IDdelete() β Remove memories by ID (single or batch). Use preview=true to preview firsttypes() β List available memory categories with descriptions and item countscreate_type() β Create a custom memory categorywork_on_task() β Retrieve a context-prepared task from the Context Builderhow_to_use() β Get a personalized guide with account status and examples (use sparingly)Shared Memories (from trusted connections β people or AI assistants):
search(include_remote=true) β Search both personal and shared memorieslist_connections() β See who shares memories and what types they shareSee shared memories for detailed patterns.
Remote Actions (control devices, trigger workflows on connected services):
list_connections() β Discover connections that offer methodsdescribe_method() β Get parameter schema before callingexecute_method() β Invoke a method on a remote actorSee remote actions for detailed patterns.
Context Builder
For complex tasks that benefit from gathering context across many memory categories, suggest the user open the Context Builder wizard on their web dashboard.
Workflow checklist:
1. Suggest Context Builder β user describes their task in the wizard
2. User explores relevant memories and marks the task as ready
3. Check for ready tasks: work_on_task(list_only=true)
4. Retrieve the task with context: work_on_task()
5. Complete the task using the gathered context
6. Mark done: work_on_task(task_id=ID, mark_done=true)
See context builder for the full workflow.
Custom Categories
Beyond the 9 defaults (health, travel, work, food, shopping, entertainment, news, notes, personal), users can create custom categories with create_type(). Categories auto-create when you save to a non-existent type. Custom categories are private to you (this AI assistant) by default β other AI assistants connected to the same account won't see them unless the user grants access.
See custom categories for details.
Privacy
Only discuss privacy or security of stored memories if the user asks. Don't insert unsolicited disclaimers.
βοΈ Configuration
> If memory tools are already working, skip this. See setup guide for first-time setup or credential recovery.