read-working-memory▌
nowledge-co/community · updated Apr 8, 2026
Daily briefing of active focus areas, priorities, and recent knowledge changes for cross-session continuity.
- ›Load at the beginning of each session to understand current context and recent work across tools
- ›Surfaces active focus areas ranked by recent activity, flagged priorities, and unresolved contradictions or stale information
- ›Works via nmem wm read CLI command for both local and remote knowledge bases, with fallback to local file access
- ›Includes deep links to specific memories
Read Working Memory
Start every session with context. Your Working Memory is a daily briefing synthesized from your knowledge base.
When to Use
At session start:
- Beginning of a new conversation
- Returning to a project after a break
- When context about recent work would help
During session:
- User asks "what am I working on?" or "what's my context?"
- User references recent priorities or decisions
- Need to understand what's been happening across tools
Skip when:
- Already loaded this session
- User explicitly wants a fresh start
- Working on an isolated, context-independent task
Usage
Read Working Memory via nmem CLI (works for both local and remote):
nmem wm read
Fallback for local-only (when nmem is not installed):
cat ~/ai-now/memory.md
What You'll Find
The Working Memory briefing contains:
- Active Focus Areas — Topics you're currently engaged with, ranked by recent activity
- Priorities — Items flagged as important or needing attention
- Unresolved Flags — Contradictions, stale information, or items needing verification
- Recent Activity — What changed in your knowledge base since the last briefing
- Deep Links — References to specific memories for further exploration
How to Use This Context
- Read once at session start — don't re-read unless asked
- Reference naturally — mention relevant context when it connects to the current task
- Don't overwhelm — share only the parts relevant to what the user is working on
- Cross-tool continuity — insights saved in other tools (Cursor, Claude Code, Codex) appear here
Troubleshooting
If nmem is not in PATH: pip install nmem-cli or pipx install nmem-cli
If Nowledge Mem is on a remote server, create ~/.nowledge-mem/config.json with {"apiUrl": "...", "apiKey": "..."}, or set NMEM_API_URL and NMEM_API_KEY environment variables.
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.5★★★★★38 reviews- ★★★★★Hana Lopez· Dec 20, 2024
read-working-memory fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Kiara Anderson· Dec 16, 2024
read-working-memory reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Mateo Thompson· Dec 12, 2024
read-working-memory is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Shikha Mishra· Dec 4, 2024
I recommend read-working-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Rahul Santra· Nov 23, 2024
Solid pick for teams standardizing on skills: read-working-memory is focused, and the summary matches what you get after install.
- ★★★★★Kiara Rahman· Nov 7, 2024
Registry listing for read-working-memory matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Advait Jain· Nov 3, 2024
Keeps context tight: read-working-memory is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Kiara Diallo· Oct 26, 2024
Useful defaults in read-working-memory — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Advait Gonzalez· Oct 22, 2024
I recommend read-working-memory for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Pratham Ware· Oct 14, 2024
read-working-memory is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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