Skip to content

/dream

Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use

shell
$ npx -y skills add yonatangross/orchestkit --skill dream --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.
  • You can call itInvoke it directly when you want it.
  • Slash command/dream
How auto-invocation works

Context preview

The summary Claude sees to decide when to auto-load this skill.

Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use

SKILL.md

dream.SKILL.md
name: dream
license: MIT
compatibility: "Claude Code 2.1.220+"
description: "Nightly memory consolidation — prunes stale entries, merges duplicates, resolves contradictions, rebuilds MEMORY.md index. Use when memory files have accumulated over many sessions and need cleanup. Do NOT use for storing new decisions (use remember) or searching memory (use memory)."
argument-hint: "[--dry-run]"
tags: [memory, maintenance, consolidation]
version: 1.0.0
author: OrchestKit
user-invocable: true
allowed-tools: [Read, Write, Edit, Glob, Grep, Bash]
complexity: medium
context: inherit
persuasion-type: collaborative
effort: low
model: sonnet
triggers:
  keywords: [dream, consolidate, "clean memory", "prune memory", "memory cleanup", "stale memories", "merge memories", "memory maintenance", "tidy memory", "stale memory entries", "memory files", "prune memories"]
  examples:
    - "consolidate my memory files"
    - "clean up stale memory entries"
    - "run dream to prune old memories"
  anti-triggers: [remember, save, store, search, recall, "load context", implement, explore]

Dream - Memory Consolidation

Deterministic memory maintenance: detect stale entries, merge duplicates, resolve contradictions, rebuild the MEMORY.md index. All pruning decisions are based on verifiable checks (file exists? function exists? duplicate content?), not LLM judgment.

Argument Resolution

DRY_RUN = "--dry-run" in "$ARGUMENTS"  # Preview changes without writing

Overview

Memory files accumulate across sessions. Over time they develop problems:

  • **Stale references** — memories pointing to files, functions, or classes that no longer exist
  • **Duplicates** — multiple memories covering the same topic with overlapping content
  • **Contradictions** — newer memories superseding older ones without cleanup
  • **Index drift** — MEMORY.md index out of sync with actual memory files

This skill fixes all four problems using deterministic checks only.

> **Cadence (CC 2.1.142+):** Reactive compaction now sizes its first summarize attempt to the actual overflow, so long sessions stall mid-turn far less often. The "run nightly" cadence can relax toward "run when memory files accumulate" — consolidation is no longer needed to head off compaction inefficiency.

---

STEP 1: Discover Memory Files

# Find the memory directory (agent-specific or project-level)
# Agent memory lives in: .claude/agent-memory/<agent-id>/
# Project memory lives in: .claude/projects/<hash>/memory/
# Also check: .claude/memory/

memory_dirs = []
Glob(pattern=".claude/agent-memory/*/MEMORY.md")
Glob(pattern=".claude/projects/*/memory/MEMORY.md")
Glob(pattern=".claude/memory/MEMORY.md")

# For each discovered MEMORY.md, glob all *.md files in that directory
for dir in memory_dirs:
    Glob(pattern=f"{dir}/../*.md")  # All memory files alongside MEMORY.md

Read every discovered memory file. Parse frontmatter (`name`, `description`, `type`) and body content. Build an in-memory inventory:

inventory = [{
    "path": "/abs/path/to/file.md",
    "name": frontmatter.name,
    "type": frontmatter.type,  # user, feedback, project, reference
    "description": frontmatter.description,
    "body": body_text,
    "file_refs": [],      # extracted file paths
    "symbol_refs": [],    # extracted function/class names
    "topics": [],         # key phrases for duplicate detection
}]

---

STEP 2: Detect Staleness

For each memory file, extract references and verify they still exist.

2a: File Path References

Extract paths that look like file references (patterns: paths with `/` and file extensions, backtick-wrapped paths):

# Regex-like extraction from body text:
# - Paths containing / with common extensions: .py, .ts, .tsx, .js, .json, .md, .yaml, .yml, .sh
# - Backtick-wrapped paths: `src/something/file.ts`
# - Quoted paths in frontmatter descriptions

**Classify each ref's SCOPE before verifying it.** `Glob` only sees the current repo, so a path that lives anywhere else can never match and would otherwise be scored as missing. A memory about `~/.claude` hooks, a homebrew cask, a cmux config, or another repo is not stale just because this repo does not contain it.

def scope(ref):
    # Anything rooted outside the working repo is UNVERIFIABLE, not missing.
    if ref.startswith(("~", "/", "$")):          return "UNVERIFIABLE"
    if ref.startswith(("http://", "https://")):  return "UNVERIFIABLE"
    if re.match(r'^[A-Za-z0-9_.-]+/', ref) and not (REPO / ref.split("/")[0]).exists():
        return "UNVERIFIABLE"   # first segment is not a real top-level dir here
    return "REPO_RELATIVE"

verifiable = [r for r in file_refs if scope(r) == "REPO_RELATIVE"]
external   = [r for r in file_refs if scope(r) == "UNVERIFIABLE"]

missing = []
for ref in verifiable:
    Glob(pattern=ref)
    # If no match → missing.append(ref)

**The staleness ratio is computed over `verifiable` ONLY.** `external` refs are recorded for the report and never counted toward pruning. A memory with zero verifiable refs is `EVERGREEN` no matter how many external paths it names.

2b: Symbol References

Extract function/class names (patterns: `function_name()`, `ClassName`, `def function_name`):

for symbol in symbol_refs:
    Grep(pattern=symbol, path=".", output_mode="files_with_matches", head_limit=1)
    # If no match → mark as STALE_SYMBOL_REF

2c: Staleness Classification

| Finding | Classification | Action | |---------|---------------|--------| | **Zero VERIFIABLE refs** (none, or all UNVERIFIABLE) | EVERGREEN | Keep | | All verifiable refs valid, all symbols found | FRESH | Keep | | Some verifiable refs missing | PARTIALLY_STALE | Flag for review | | All verifiable refs missing AND all symbols missing | FULLY_STALE | Prune candidate |

Only memories classified as FULLY_STALE are auto-pruned. PARTIALLY_STALE memories are reported but kept — the user decides.

2d: Prune guards — checked A

Read more
Read it on GitHub ↗

Showing the first part of this file.

Ships withorchestkit

The Complete AI Development Toolkit for Claude Code — 114 skills, 37 agents, 212 hooks. Production-ready patterns for full-stack development.

Get the whole plugin, auto-invoked
Stats
212
Stars
0
Views
22
Forks
Active
Maintenance
TypeScript
Language
MIT
License
32m ago
Last commit
7mo ago
Created

Repo: yonatangross/orchestkit

Other skills on orchestkit.