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auto-dream

Background memory consolidation — overnight review, merge, and injection payload for memory files.

Install / Use

npx skills add notque/vexjoy-agent --skill auto-dream

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

82/100

Supported Platforms

Universal

Our assessment of auto-dream

auto-dream scores 82/100 on our quality scale, 3284th of 4,546 Development & Engineering skills we index.

Its SKILL.md is 5.5 KB long, well organised into 16 sections with 2 code examples: a solid amount of guidance for an agent.

It has 425 GitHub stars, a meaningful sign that others use it.

Substance
26/30
Structure
18/20
Description
12/15
Adoption
11/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 12 days ago, so auto-dream is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

Safety scan

Review

Our scan of the whole file found 1 pattern worth reviewing before you install auto-dream.

  • mediumDisables the agent's permission promptsline 107
    - `--permission-mode auto` (never `--dangerously-skip-permissions`)

Automated pattern scan on 2026-10-15. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.

auto-dream compared with similar skills

All 4 of these similar skills score higher than auto-dream; compare them before choosing.

SkillScoreStarsUpdatedFormat
auto-dream (this skill)by notque8242512d agoSKILL.md
taste-skillby Leonxlnx10097.0ktodayCLAUDE.md
ai-job-searchby MadsLorentzen10046.9ktodayCLAUDE.md
claude-howtoby luongnv8910041.9ktodayCLAUDE.md
algorithmic-artby anthropics100177.9k22d agoSKILL.md

Frequently asked questions

How do I install auto-dream?
Run npx skills add notque/vexjoy-agent --skill auto-dream. The install tabs above show the steps for each supported agent.
Which AI agents does auto-dream work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is auto-dream safe to use?
Our scan of the whole file found 1 pattern worth reviewing before you install auto-dream. It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is auto-dream still maintained?
The repository was last updated 12 days ago, so auto-dream is actively maintained.

name: auto-dream description: Background memory consolidation — overnight review, merge, and injection payload for memory files. user-invocable: true command: dream context: fork allowed-tools:

  • Read
  • Write
  • Edit
  • Glob
  • Grep
  • Bash routing: triggers:
    • dream
    • consolidate memories
    • clean up memories
    • memory maintenance
    • memory consolidation
    • deduplicate memories category: meta-tooling pairs_with: []

Background memory consolidation cycle. Scans memory files, finds stale, duplicate, and conflicting entries, consolidates them, synthesizes cross-session insights, builds an injection-ready payload for the next session start, and writes a dated dream report.

When to invoke

  • User says "run dream", "consolidate memories", "clean up memories", "memory maintenance", "deduplicate memories"
  • Cron job at 2 AM nightly via wrapper script: scripts/auto-dream-cron.sh --execute
  • Manual trigger for testing: ./scripts/auto-dream-cron.sh (dry-run by default)

Instructions

When invoked interactively (not via cron), read skills/meta/auto-dream/dream-prompt.md and execute its phases directly. The prompt is self-contained -- it describes the full cycle including safety constraints, file paths, and output formats.

For cron invocation: the dream prompt is passed directly to claude -p and runs as a standalone headless session with no CLAUDE.md, no hooks, no project context. All instructions are embedded in the prompt.

Phases

  1. SCAN — Read all memory files and the recent git log. Write the scan document to ~/.claude/state/dream-scan-{date}.md.
  2. ANALYZE — Identify stale, duplicate, conflicting memories and cross-session patterns. Write analysis to ~/.claude/state/dream-analysis-{date}.md.
  3. CONSOLIDATE — Apply consolidation actions (max 5 changes). Archive stale/merged files, update MEMORY.md atomically.
  4. SYNTHESIZE — Create insight memories from cross-session patterns (max 2 new memories per cycle).
  5. SELECT — Build the injection-ready payload for session start. Write to ~/.claude/state/dream-injection-{project-hash}.md.
  6. REPORT — Write the dream summary to ~/.claude/state/last-dream.md.

Safety constraints (always enforced)

  • Never delete files — archive to memory/archive/, never rm
  • Write the REPORT before executing any CONSOLIDATE filesystem operations
  • Maximum 5 memory changes per cycle — excess items deferred to next cycle
  • Flag conflicts for human review, never auto-resolve
  • Preserve YAML frontmatter when merging; use merged_from field for provenance
  • Memory files are the only write target. Knowledge reaches an agent or skill file through a reviewed human edit, never through this cycle.
  • In dry-run mode (the default), CONSOLIDATE and SYNTHESIZE describe proposed changes only — no filesystem writes. The wrapper script sets DREAM_DRY_RUN_MODE=yes, substituted into the prompt at runtime.

Testing

# Dry run (read-only, no filesystem changes — dry-run is the default)
./scripts/auto-dream-cron.sh

# Full run (execute consolidation)
./scripts/auto-dream-cron.sh --execute

# Check output
cat ~/.claude/state/last-dream.md

# Verify cron registration
python3 ~/.claude/scripts/crontab-manager.py list

Cost estimate

~0.09 USD per nightly run with 50 memory files (~20-30K input tokens at Sonnet pricing). ~33 USD/year for automated overnight operation. Budget capped at 3.00 USD/run via wrapper script.

Cron setup

Use crontab-manager.py (not raw crontab -e) to install. The wrapper script handles PATH, lockfile, logging, budget cap, and dry-run/execute toggle.

# Preview the cron entry
python3 ~/.claude/scripts/crontab-manager.py add \
  --tag "auto-dream" \
  --schedule "7 2 * * *" \
  --command "/home/feedgen/vexjoy-agent/scripts/auto-dream-cron.sh --execute >> /home/feedgen/vexjoy-agent/cron-logs/auto-dream/cron.log 2>&1" \
  --dry-run

# Install (after dry-run testing passes)
python3 ~/.claude/scripts/crontab-manager.py add \
  --tag "auto-dream" \
  --schedule "7 2 * * *" \
  --command "/home/feedgen/vexjoy-agent/scripts/auto-dream-cron.sh --execute >> /home/feedgen/vexjoy-agent/cron-logs/auto-dream/cron.log 2>&1"

# Verify
python3 ~/.claude/scripts/crontab-manager.py verify --tag auto-dream

Note: schedule uses 2:07 AM (off-minute) per cron best practice — avoids load spikes from jobs firing at :00.

Wrapper script details

scripts/auto-dream-cron.sh follows the established headless cron pattern (see skills/content/reddit-moderate/scripts/reddit-automod-cron.sh):

  • flock lockfile prevents concurrent runs
  • --permission-mode auto (never --dangerously-skip-permissions)
  • --max-budget-usd 3.00 caps spend per run
  • --no-session-persistence for clean headless operation
  • envsubst templates dream-prompt.md with project-specific paths at runtime
  • tee to timestamped per-run log file
  • Dry-run by default, --execute for live runs
  • Exit code propagation via PIPESTATUS[0]

Deep References

Load when the task requires detailed guidance beyond the phases above.

| Signal | Reference | |--------|-----------| | Failed cron run, wrapper script setup, budget cap | references/headless-cron-patterns.md | | Memory file writes, YAML frontmatter, staleness, merging | references/memory-file-operations.md | | Dry-run validation, output file verification | references/dream-cycle-testing.md | | Cron log interpretation, rotation, phase markers | references/logging-patterns.md | | Concurrent runs, lockfile, partial write recovery | references/concurrency.md |

Related Skills

View on GitHub
GitHub Stars425
CategoryDevelopment
Updated12d ago
Forks48

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions