Claude-skill-registry Distill Memory

Recognize breakthrough moments, blocking resolutions, and design decisions worth preserving. Detect high-value insights that save future time. Suggest distillation at valuable moments, not routine work.

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/distill-memory" ~/.claude/skills/majiayu000-claude-skill-registry-distill-memory && rm -rf "$T"

manifest: skills/data/distill-memory/SKILL.md

Distill Memory

When to Suggest (Moment Detection)

Breakthrough: Extended debugging resolves, user relief ("Finally!", "Aha!"), root cause found

Decision: Compared options, chose with rationale, trade-off resolved

Research: Investigated multiple approaches, conclusion reached, optimal path determined

Twist: Unexpected cause-effect, counterintuitive solution, assumption challenged

Lesson: "Next time do X", preventive measure, pattern recognized

Skip: Routine fixes, work in progress, simple Q&A, generic info

Memory Quality

Good (atomic + actionable):

"React hooks cleanup must return function. Caused leaks."
"PostgreSQL over MongoDB: ACID needed for transactions."

Poor: Vague "Fixed bugs", conversation transcript

Tool Usage

Use

nmem

CLI to create memories:

nmem m add "Insight + context for future use" \
  -t "Searchable title (50-60 chars)" \
  -i 0.8

Content: Outcome/insight focus, include "why", enough context

Importance: 0.8-1.0 major | 0.5-0.7 useful | 0.3-0.4 minor

Note: For programmatic use, add

--json

flag to get JSON response

Examples:

# High-value insight
nmem m add "React hooks cleanup must return function. Caused memory leaks in event listeners." \
  -t "React Hooks Cleanup Pattern" \
  -i 0.9

# Decision with context
nmem m add "Chose PostgreSQL over MongoDB for ACID compliance and complex queries" \
  -t "Database: PostgreSQL" \
  -i 0.9

Suggestion

Timing: After resolution/decision, when user pauses

Pattern: "This [type] seems valuable - [essence]. Distill into memory?"

Frequency: 1-3 per session typical, quality over quantity

Troubleshooting

nmem

is not available:

Option 1 (Recommended): Use uvx

# Install uv
curl -LsSf https://astral.sh/uv/install.sh | sh

# Run nmem (no installation needed)
uvx --from nmem-cli nmem --version

Option 2: Install with pip

pip install nmem-cli
nmem --version