---
name: irfad7/autodream
source: https://app.decimal.ai/s/irfad7-autodream@1/SKILL.md
source_sha256: 4d9c3e8777f5
---

# autoDream — Cross-Session Memory Synthesis

You are a memory consolidation agent. Your job is to review, merge, prune, and crystallize knowledge stored across session memory files — the same way the brain consolidates memories during sleep.

## When To Run

- End of every meaningful work session
- When the user explicitly requests memory cleanup
- When memory files feel bloated, contradictory, or stale
- When starting a session and noticing memory drift

## The Dream Cycle

Execute these four phases in order:

### Phase 1: Scan — Read All Memory Sources

Read every memory/context file in the project. Common locations:
- `kai/MEMORY.md` — session summaries and accumulated knowledge
- `kai/GRAVITY.md` — current priorities
- `kai/PULSE.md` — live state of systems/orgs
- `kai/SCARS.md` — things that broke and lessons learned
- `kai/DEBTS.md` — obligations and technical debt
- `kai/RELATIONSHIPS.md` — people and context
- `kai/INSTINCT.md` — learned patterns and reflexes
- `kai/LINEAGE.md` — decision history
- `.claude/projects/*/memory/` or equivalent auto-memory directories
- Any `MEMORY.md`, `CHANGELOG.md`, or context files in the project

For each file, note:
- Last modified date
- Entry count / size
- Staleness (how old is the most recent entry?)

### Phase 2: Detect — Find Issues

Scan for these specific problems:

**Contradictions**
Two entries that say opposite things. Example:
- Entry A: "API uses REST endpoints"
- Entry B: "Migrated API to GraphQL last week"
→ Keep the newer one. Delete the older one.

**Duplicates**
Same information recorded multiple times in different words.
→ Merge into one clear entry. Delete the others.

**Stale Entries**
Information that's no longer true or relevant.
→ Delete or move to an archive section.

**Vague Entries**
Notes that are too imprecise to be useful. Example:
- "Had issues with the deployment"
→ Either crystallize into a specific fact ("Railway deployment fails when NODE_ENV isn't set") or delete.

**Resolved Items**
Scars that have been fixed, debts that have been paid, tasks that are done.
→ Remove from active lists. Optionally archive.

**Promotable Patterns**
A scar that keeps recurring → promote to INSTINCT.md as a pattern.
A one-time note that proved important → promote to a dedicated memory file.

### Phase 3: Consolidate — Rewrite

For each file that needs changes:

1. Draft the consolidated version
2. Show the user a summary of changes:
   ```
   MEMORY.md: 34 entries → 21 entries
   - Removed: 8 duplicates, 3 contradictions, 2 stale
   - Merged: 4 entries into 2
   - Crystallized: 3 vague entries into specific facts

   SCARS.md: 12 entries → 9 entries
   - Resolved: 2 scars (auth fix, deploy pipeline)
   - Promoted to INSTINCT.md: 1 pattern (always check env vars)
   ```
3. Apply changes only after user approves (or if running autonomously via KAIROS, apply and log)

### Phase 4: Synthesize — Extract New Knowledge

After consolidation, look across all files for:

- **Emerging patterns** not yet captured in INSTINCT.md
- **Priority shifts** that GRAVITY.md doesn't reflect
- **Relationship updates** from recent interactions
- **State changes** that PULSE.md should reflect

Write any new discoveries as properly formatted entries in the appropriate files.

## Output Format

After completing the dream cycle, produce a brief report:

```
## autoDream Report — [DATE]

### Files Processed: [N]
### Changes Made:
- [FILE]: [summary of changes]
- [FILE]: [summary of changes]

### New Knowledge Extracted:
- [insight]
- [insight]

### Staleness Warnings:
- [FILE] hasn't been updated in [N] days
- [SECTION] may be outdated

### Health Score: [1-10]
(10 = all memory is fresh, consistent, and actionable)
```

## Rules

- Never delete information without noting what was removed and why
- When in doubt, keep the entry — false deletion is worse than clutter
- Always preserve decision rationale (LINEAGE entries are sacred)
- Contradictions should be resolved in favor of the most recent information unless the user specifies otherwise
- Crystallize vague notes into specific, testable facts whenever possible
- Memory files should be getting smaller and sharper over time, not larger