memory-distiller
Distill repeated user preferences, successful patterns, and durable working rules into reusable memory notes or prompt-ready context blocks. Use when a user wants to capture habits, preserve preferences, summarize lessons from prior work, or convert raw conversation/task outcomes into structured memory.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/danxbuidl/danxbuidl-memory-distillerMemory Distiller
Overview
Use this skill when the user wants to turn raw interaction history into stable, reusable memory. The goal is not to summarize everything. The goal is to keep only the parts that are durable enough to improve future work.
Read references/output-format.md when the user wants a structured output
template, a prompt-ready context block, or a reusable memory profile format.
Read references/example-prompts.md when the user needs prompt examples,
variation ideas, or help choosing the right invocation pattern.
Quick Start
If the user does not specify a format, default to this flow:
- extract candidate memories from the source material
- keep only durable and evidence-backed items
- rewrite them as future-facing rules
- return:
- stable preferences
- working rules
- anti-patterns
- one short reusable context block
If the user already has a memory document, switch into review mode instead of rebuilding everything from scratch.
When To Use
Use this skill when the user asks to:
- capture recurring preferences or habits
- preserve successful working patterns
- record constraints, defaults, or anti-patterns
- turn task outcomes into future-facing rules
- clean up or refine an existing memory/profile document
- produce a compact context block for reuse in future prompts
Do not use this skill for:
- one-off conversational summaries
- temporary task state that will expire quickly
- guesses about user preferences that are not supported by evidence
- hidden or background memory injection into runtime code paths
Output Selection
Choose the narrowest output that matches the user's goal:
- memory profile
- use when the user wants a compact long-term preference document
- cleaned memory list
- use when the user already has notes and wants to remove weak items
- prompt-ready context block
- use when the user wants a short block to reuse in future prompts
- review and rewrite report
- use when the user wants to know what should be kept, rewritten, or removed
Read references/output-format.md before producing any structured output.
Core Rule
Only preserve information that looks durable.
Good candidates:
- stable preferences
- repeated defaults
- persistent constraints
- explicit dislikes
- reusable procedures
- recurring failure-avoidance rules
Weak candidates:
- one-off requests
- temporary deadlines
- transient debugging state
- personal guesses not explicitly supported by the source material
When a memory candidate is uncertain, mark it as tentative or exclude it.
Evidence Threshold
Prefer memories that are supported by one of these:
- an explicit user statement
- a repeated pattern across multiple examples
- a successful workflow that clearly generalizes
- a durable constraint that is unlikely to change soon
Prefer to exclude items that are supported only by:
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-danxbuidl-danxbuidl-memory-distiller": {
"enabled": true,
"auto_update": true
}
}
}