grim:mem:dream-sequence
Dream Memory Sequence: Run a periodic memory-consolidation review.
Skill by MindGoblinStudios
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/mindgoblinstudios-grim-mem-dream-sequence
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/grim-mem-dream-sequence
What's inside
- Skill name
grim:mem:dream-sequence- Description
- Dream Memory Sequence: Run a periodic memory-consolidation review. Synthesize recent work and chat history, propose durable memory candidates, flag stale or duplicate memory for cleanup, and surface missing-context questions. Never edits memory without user confirmation.
- License
- MIT
- Instructions
- 44 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- name: only lowercase letters, digits and single hyphens allowed
Files (6)
- SKILL.md
- openai.yaml · agents/
- dream-sequence-icon-large.png · assets/
- dream-sequence-icon-med.png · assets/
- dream-sequence-icon-small.png · assets/
- icon-generation-2026-08-22.md · assets/prompts/
SKILL.md (first lines)
# Dream Memory Sequence ## Purpose Consolidate and improve the memory system, the way sleep consolidates a day's experiences. Run this weekly, or after an intense stretch of work. Memory flows in one direction: `memory/MEMORY.md` is the fast-capture surface where corrections and preferences land mid-session, and the dream sequence is the consolidation pass. Durable items that have proven themselves get promoted out of memory into the right `docs/` file (or `AGENTS.md`, per `grim:dev:autodocs`), then pruned from memory. Memory stays small; docs accumulate the distilled knowledge. ## Inputs Review before summarizing: - `memory/MEMORY.md` (and the project's memory system docs, if any) - `docs/README.md` and any recently changed docs - Recent chat or session history from the last 7 to 14 days, when the harness makes it available ## Consolidation Pass - Revisit the previous consolidation candidates using existing run notes. Check which were applied, superseded, declined, or still need a decision before proposing them again. - Distill what changed in understanding: a durable lesson, a corrected belief, the intent behind a decision, or missing context that matters next time. - Check candidates against their canonical home for contradictions and duplication. Preserve sources and uncertainty where they matter, and make the useful context easy to retrieve. - Reuse relevant evidence and refresh changed or consequential facts. Keep broader cleanup and system experiments with their existing owner unless they affect memory's accuracy or usefulness. - Keep declined ideas retired unless the user reopens them. Do not invent candidates to fill a report; stay quiet when there is no meaningful update or action. ## Report Respond in the current conversation. Scheduled runs use their configured destination. Don't send additional copies elsewhere unless requested. Return a report with: - A synthesis of what changed since the previous pass, highlighting the most important things to remember - Durable memory candidates, to be added to memory - Promotion candidates: memory entries that have matured into doc material, with the target `docs/` file for each (prune from memory once promoted) - Stale, duplicate, or low-signal memory cleanup suggestions - The top 3 missing-context questions that would help the system better understand the user's life, goals, and projects - Suggested next steps ## Rules - Do not silently edit any docs, skills, memory files, commits, or external systems until the user confirms. - Distill, don't transcribe: one bullet per durable fact. Preserve intent and distinguish observations from decisions. - Prefer correcting an existing memory entry over adding a near-duplicate.
From MindGoblinStudios/grim-tome, MIT.
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Signals
- Stars
- 34
- Forks
- 4
- Open issues
- 0
- Last commit (this folder)
- Oct 18, 2026 (10 days ago)
- Last release
- Aug 25, 2026 (2 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/MindGoblinStudios/grim-tome
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
grim:mem:dream-sequence skill. Agent Mart. https://agentmart.dev/skills/mindgoblinstudios-grim-mem-dream-sequence (last updated 2026-10-24)