| name | knowledge-distiller |
| description | Analyzes conversation sessions to extract key insights, decisions, and technical details, then saves them to the knowledge base. Use this skill when asked to "summarize what I learned today," "record key points from recent sessions," or "sync current project context to long-term memory." |
Knowledge Distiller
This skill provides a systematic workflow for retrieving conversation sessions, extracting valuable information (entities, relationships, and insights), and persisting them in the Knowledge Base. It transforms transient dialogue into structured, long-term memory.
Prerequisites
- The agent session must have the optional
history and knowledge builtin services enabled. If tool calls fail with a "not enabled" error, enable them via Assistants settings or agent__update before running this workflow.
- Runtime tool names use the
server__tool format shown below (for example history__list, knowledge__record_knowledge). Match names from the session tool list.
Execution Triggers
Use this skill when the user says:
- "Summarize my learnings from today's sessions."
- "Extract important technical decisions from my recent work."
- "Update the knowledge base with the context we just discussed."
- "Keep track of the project preferences established in this session."
Workflow
1. Define the Analysis Scope
Determine which sessions to analyze based on the user's request:
- Temporal: Today (from 00:00:00 to 23:59:59 ISO-8601).
- Recent: The last N sessions from the history.
- Current: Focus only on the active or most recent session.
Use history__list to retrieve the relevant sessionId list if the scope is broader than the current session.
2. Context Preview & Filtering
For each target session:
- Use
history__readSession to preview message summaries.
- Filter for high-value content such as:
- Architecture decisions or design patterns discussed.
- Specific error causes and their confirmed resolutions.
- Library versions, API endpoints, or configuration keys.
- Explicit user preferences or project-specific naming conventions.
3. Deep Extraction (Distillation)
If a session contains valuable information, use history__readMessage for full detail.
Identify and structure the following components:
- Entities: Technologies (e.g., "Tauri 2.0"), Projects (e.g., "LibrAgent"), or Concepts.
- Relationships: Link entities (e.g., "LibrAgent"
USES "SeaORM").
- Content: A concise, stand-alone summary of the knowledge.
4. Structured Recording
Use the knowledge__record_knowledge tool to persist the findings:
- content: The distilled summary.
- entities/relationships: Structured data for the graph.
- source: Reference the source
sessionId or date for traceability.
- tags: Include
["distilled", "auto-knowledge", "context-sync"].
Safety & Efficiency
- De-duplication: Before recording, use
knowledge__search_knowledge to check if similar knowledge already exists to avoid redundant entries.
- Relevance: Skip sessions that are purely social or don't contain reusable technical/project context.
References
