read-working-memory

nowledge-co/community · updated Apr 8, 2026

$npx skills add https://github.com/nowledge-co/community --skill read-working-memory
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summary

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
skill.md

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

  1. Read once at session start — don't re-read unless asked
  2. Reference naturally — mention relevant context when it connects to the current task
  3. Don't overwhelm — share only the parts relevant to what the user is working on
  4. 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)
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general reviews

Ratings

4.538 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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