mnemos

Mnemos — Task-Scoped Memory Lifecycle

What It Does

Mnemos prevents lossy context compaction from destroying the structured knowledge you need most. It treats your working memory as a typed graph (MnemoGraph) where different types of knowledge have different eviction policies:

• GoalNodes and ConstraintNodes are NEVER evicted — they survive all compaction
• ResultNodes are compressed (summary kept) before eviction
• ContextNodes are evictable when their activation weight drops
• CheckpointNodes persist to disk for session resume

Fatigue Model

Mnemos monitors 4 dimensions of "agent fatigue" — all passively observed from hook data, no manual input needed:

Dimension	Weight	Signal Source	What It Measures
Token utilization	0.40	Statusline JSON	How full the context window is
Scope scatter	0.25	PreToolUse file paths	How many directories the agent is bouncing between
Re-read ratio	0.20	PreToolUse Read calls	How often the agent re-reads files it already read (context loss)
Error density	0.15	PostToolUse outcomes	What fraction of tool calls are failing (agent struggling)

Fatigue states and actions:

State	Score	Action
FLOW	0.0–0.4	Normal operation
COMPRESS	0.4–0.6	Micro-consolidation runs (compress 3 ResultNodes, evict 1 cold ContextNode)
PRE-SLEEP	0.6–0.75	Checkpoint written, consolidation runs
REM	0.75–0.9	Emergency checkpoint, consider wrapping up
EMERGENCY	0.9+	Checkpoint written, hand off immediately

How To Use

Automatic (hooks handle everything):

1. Statusline writes fatigue.json on every API call
2. PreToolUse hook reads fatigue before every edit, auto-checkpoints at 0.60+
3. PreCompact hook writes emergency checkpoint, compaction marker, and tells summarizer what to preserve
4. SessionStart "compact" fires immediately after compaction, re-injects full checkpoint (primary restore)
5. SessionStart "startup|resume" loads last checkpoint on new/resumed sessions
6. PreToolUse fallback (no matcher) detects compaction marker if SessionStart didn't fire
7. Stop hook writes final checkpoint for next session

Post-Compaction Recovery (Three-Layer Defense):

When Claude Code compacts the context (~83% full), Mnemos uses three layers:

• Layer 1 (PreCompact): Outputs strong preservation instructions with inline checkpoint content for the summarizer. Writes .mnemos/just-compacted marker.
• Layer 2 (SessionStart "compact"): PRIMARY re-injection. Fires immediately when Claude resumes after compaction — before any agent action. Consumes the marker and injects the full checkpoint into the fresh context. This is the recommended approach per the RFC (Wake State Reconstruction).
• Layer 3 (PreToolUse fallback): If SessionStart doesn't fire (older versions, edge cases), the first tool call triggers mnemos-post-compact-inject.sh which detects the marker and injects. Safety net only.

The result: after compaction, you'll see a "CONTEXT RESTORED AFTER COMPACTION" block with your goal, constraints, what you were working on, and progress. Resume from there.

Manual CLI:

mnemos init                    # Initialize .mnemos/
mnemos status                  # Show node counts + fatigue
mnemos fatigue                 # Detailed fatigue breakdown
mnemos checkpoint --force      # Write checkpoint now
mnemos resume                  # Output checkpoint for context
mnemos consolidate             # Run micro-consolidation
mnemos nodes --type goal       # List active GoalNodes
mnemos add goal "Build auth"   # Add a GoalNode
mnemos bridge-icpg             # Import iCPG ReasonNodes
mnemos ingest-claude --all     # Ingest Claude Code transcripts (see below)
mnemos haze --recent 10        # Show per-session haziness scores

Claude Transcript Ingestion & Haziness

Mnemos can ingest Claude Code session transcripts (the per-session JSONL under ~/.claude/projects/) and score each session's haziness — a measure of how much the agent struggled. The Stop hook does this automatically on session exit; it is also available manually.

What's stored: only structural fields (roles, tool names, file paths, error flags, timestamps) plus a redacted, 200-char preview of each turn. Full content is never persisted, and secrets (API keys, tokens, PEM blocks, JWTs, credentials) are redacted before anything touches disk.

Haziness is a weighted score over five dimensions, each in [0,1]:

Dimension	Weight	What it measures
correction_density	0.30	User corrections per eligible user turn
redo_ratio	0.25	Edits re-touched after an error
first_try_error_rate	0.20	Edits followed by errors within 3 turns
orphan_tool_use_rate	0.15	Tool calls with no matching result
backtrack_norm	0.10	git revert/reset --hard/restore calls

The composite maps to a band: clear < 0.25 ≤ cloudy < 0.50 ≤ hazy < 0.75 ≤ lost.

mnemos ingest-claude --all              # ingest every transcript + score
mnemos ingest-claude --session <id>     # one session by id
mnemos ingest-claude --transcript <f>   # a specific JSONL file
mnemos haze --recent 10                 # table of recent sessions
mnemos haze --session <id>              # per-dimension breakdown

Ingestion is idempotent (resumes via last_line_offset). Opt out per project with touch .mnemos/claude-log.disabled.

Agent Instructions

When working on a task:

1. Create a GoalNode at the start: mnemos add goal "what you're trying to achieve" --task-id session-1
2. Add ConstraintNodes for invariants: mnemos add constraint "API backward compatibility" --scope src/api/
3. Check fatigue before long operations: mnemos fatigue
4. Checkpoint at sub-goal boundaries: mnemos checkpoint
5. On session resume: the SessionStart hook automatically loads your checkpoint

iCPG Integration

Mnemos bridges with iCPG (Intent-Augmented Code Property Graph):

• mnemos bridge-icpg imports active ReasonNodes as GoalNodes
• Postconditions/invariants become ConstraintNodes
• Checkpoint includes iCPG state (active intent, unresolved drift)

Storage

Everything lives in .mnemos/ (gitignored):

• mnemo.db — SQLite MnemoGraph
• fatigue.json — Live token metrics (updated per API call by statusline)
• signals.jsonl — Behavioral signal log (appended by PreToolUse + PostToolUse hooks)
• checkpoint-latest.json — Most recent checkpoint
• checkpoints/ — Archived checkpoints