Install
$ agentstack add skill-broomva-control-metalayer-knowledge-graph-memory ✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.
Security review
✓ PassedNo issues found. Passed automated security review. · v0.1.0 How review works →
- ✓ Prompt-injection patterns
- ✓ Secret / credential exfiltration
- ✓ Dangerous shell & filesystem operations
- ✓ Untrusted network calls
- ✓ Known-malicious package signatures
What it can access
- ✓ Network access No
- ✓ Filesystem access No
- ✓ Shell / process execution No
- ✓ Environment & secrets No
- ✓ Dynamic code execution No
From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.
Verified badge
Passed review? Show it. Paste this badge into your README, it links to the public security report.
Reliability & compatibility
Declared compatibility
Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.
We're building live execution health for every listing: tool-call success rate, median latency, uptime, and last-checked timestamps, measured, not self-reported. It isn't live yet, so we don't show numbers we can't stand behind.
How agent discovery & health will work →About
Knowledge Graph Memory
> Broomva Stack Layer 2 (Memory & Consciousness) — part of the 24-skill Broomva Stack.
Bridge agent conversation logs into an Obsidian knowledge graph, giving every new session access to the full reasoning history of all prior sessions.
Default vault: ~/broomva-vault/ (symlinks into ~/broomva/ workspace per project).
Quick Start
Install the bridge script
Copy scripts/conversation_history.py into your project's scripts/ directory:
cp scripts/conversation_history.py /scripts/conversation-history.py
chmod +x /scripts/conversation-history.py
Generate conversation docs
python3 scripts/conversation-history.py --force # Full regeneration
python3 scripts/conversation-history.py # Incremental (skip existing)
python3 scripts/conversation-history.py --dry-run # Preview without writing
python3 scripts/conversation-history.py --limit 10 # Last 10 sessions only
Wire into git hooks
Add to .githooks/pre-push (or equivalent):
if [ -f scripts/conversation-history.py ] && command -v python3 >/dev/null 2>&1; then
echo "[pre-push] Updating conversation history..."
python3 scripts/conversation-history.py 2>/dev/null && \
git add docs/conversations/ 2>/dev/null || true
fi
Add smoke check
Add to your smoke gate script:
if [ -f docs/conversations/Conversations.md ]; then
echo "[ok] conversation history MOC present"
else
echo "[warn] docs/conversations/Conversations.md missing"
fi
What It Generates
Conversations.md (MOC)
An index of all sessions grouped by date:
## 2026-03-16
| Session | Branch | Turns | Duration | Topic |
|---------|--------|-------|----------|-------|
| [[session-2026-03-16-21f4eb55]] | `feature/sti-799` | 44 | 4h 15m | Implement AI Core... |
Per-Session Docs
Each session doc contains:
- YAML frontmatter — session_id, branch, tags, wikilinks
- Metadata table — date, duration, turns, tools, attribution stats
- Conversation thread — chronological timeline:
> [!quote]User prompts> [!info]Assistant reasoning (all text blocks, not truncated)> [!example]Tool calls (expandable, with full input details)
- Files touched — all files read/written/modified
- Commits — checkpoint IDs and timestamps
Data Sources
The bridge script reads two sources:
1. .entire/logs/entire.log — Event stream
Session lifecycle events (start/end/turn), checkpoints, attribution stats, phase transitions. Requires Entire to be installed. If not present, script exits gracefully with code 0.
2. ~/.claude/projects/{KEY}/*.jsonl — Transcripts
Full conversation transcripts from Claude Code. The project key is auto-derived from the repo path (slashes replaced with dashes). Each .jsonl file contains every user message, assistant response, tool invocation, and tool result.
Noise Filtering
The script filters out internal noise from raw transcripts:
- `` blocks — internal task system messages
toolUseResultentries — tool→assistant feedback (not real user prompts)- `` — system injections
- Messages [!quote] User (HH:MM)`
- Assistant reasoning:
> [!info] **Assistant** - Tool calls:
> [!example] Tool Callswith nested>> [!note] **ToolName** — descriptionper tool - Tool details are expanded by default (remove
-for collapsed)
CLAUDE.md Integration
Add to the "Context Acquisition" section:
### Conversation History as Context
Prior sessions are indexed in `docs/conversations/`. Use them to:
- Recall prior decisions before re-solving a problem
- Understand why code looks the way it does
- Resume interrupted work on a branch
- Avoid repeating mistakes from prior sessions
Search: `grep -rl "keyword" docs/conversations/`
Add to "On Session Start" protocol:
7. Scan `docs/conversations/Conversations.md` for prior sessions on current branch
AGENTS.md Integration
Add to working rules:
7. **Check conversation history for prior context** — before starting work on a branch,
scan `docs/conversations/` for prior sessions. Use `grep -rl "keyword" docs/conversations/`
or read `docs/conversations/Conversations.md` for a chronological index.
Graceful Degradation
| Scenario | Behavior | |----------|----------| | No .entire/ installed | Script exits with code 0, skip message | | No transcripts directory | Script exits with code 0, skip message | | Different developer machine | Transcripts dir auto-derived from repo path | | CI (no local sessions) | Smoke warns but doesn't block | | Pre-push without Entire | Clean skip, exit 0, || true in hook |
Lago Context Engine Integration
The knowledge graph memory now has a server-side persistence backend via Lago (core/life/lago/):
lago-knowledgecrate provides server-side frontmatter parsing, wikilink extraction, scored search, and BFS graph traversallago-authcrate provides JWT auth middleware with shared-secret validation (AUTH_SECRET)- Per-user vaults: Each authenticated user gets a Lago session (
vault:{user_id}) for persistent.mdstorage - CLI:
lago memory {status,ls,search,read,store,ingest,delete}— ingest local vault files into Lago for remote access - broomva.tech dual-vault: Chat agent tools search both server vault (
VAULT_PATH) and user vault (LAGO_URL) with merged, ranked results
Setup
# Start lagod with auth enabled
LAGO_JWT_SECRET=$AUTH_SECRET cargo run -p lagod -- --http-port 8080
# Ingest vault files
lago memory ingest ~/broomva-vault/ --token $JWT
# Search from CLI
lago memory search "consciousness" --token $JWT
Environment Variables
| Variable | Where | Purpose | |----------|-------|---------| | LAGO_JWT_SECRET | lagod | Shared secret for JWT validation | | LAGO_URL | broomva.tech | Lago daemon URL (e.g. http://localhost:8080) | | AUTH_SECRET | broomva.tech | Signs JWTs for Lago auth (existing) | | BROOMVA_API_TOKEN | CLI | JWT token for lago memory commands |
Stack Integration
This skill is the persistence backbone for higher layers:
- Strategy (L7):
braindumpfiles notes into the vault through this bridge - Strategy (L7):
decision-logwrites structured decisions tovault/decisions/ - Strategy (L7):
weekly-reviewscans vault changes generated by this bridge - Strategy (L7):
morning-briefingreads action items from vault notes - Foundation (L1):
control-metalayer-loopgovernance policies inform what gets persisted - Persistence (L0): Lago context engine provides server-side search, graph traversal, and per-user vault storage
Source & license
This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.
- Author: broomva
- Source: broomva/control-metalayer
- License: MIT
Install and usage instructions live in the source repository linked above.
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Versions
- v0.1.0 Imported from the upstream source.