HyperStack — Agent Provenance Graph for Verifiable AI
The Agent Provenance Graph for AI agents — the only memory layer where agents can prove what they knew, trace why they knew it, and coordinate without an LLM in the loop. Timestamped facts. Auditable decisions. Deterministic trust. Ask 'what blocks deploy?' → exact typed answer. Git-style branching. Three memory surfaces: working/semantic/episodic. Decision replay with hindsight bias detection. Conflict detection. Staleness cascade. Utility-weighted edges that self-improve from agent feedback. Agent identity + trust scoring. Time-travel to any past graph state. Works in Cursor, Claude Desktop, LangGraph, any MCP client. Self-hostable. $0 per operation at any scale.
Install via CLI (Recommended)
clawhub install openclaw/skills/skills/deeqyaqub1-cmd/hyperstackHyperStack — Agent Provenance Graph for Verifiable AI
What this does
HyperStack is the Agent Provenance Graph for AI agents. The only memory layer where agents can prove what they knew, trace why they knew it, and coordinate without an LLM in the loop. Typed graph memory with three distinct memory surfaces, decision replay with hindsight detection, conflict detection, staleness cascade, and full provenance on every card.
Tagline: Timestamped facts. Auditable decisions. Deterministic trust. Build agents you can trust at $0/operation.
The problem it solves:
# DECISIONS.md (what everyone uses today)
- 2026-02-15: Use Clerk for auth
- 2026-02-16: Migration blocks deploy
"What breaks if auth changes?" → grep → manual → fragile
What you get instead:
"What breaks if auth changes?" → hs_impact use-clerk → [auth-api, deploy-prod, billing-v2]
"What blocks deploy?" → hs_blockers deploy-prod → [migration-23]
"What's related to stripe?" → hs_recommend use-stripe → scored list
"Anything about auth?" → hs_smart_search → auto-routed
"Fork memory for experiment" → hs_fork → branch workspace
"What changed in the branch?" → hs_diff → added/changed/deleted
"Trust this agent?" → hs_profile → trustScore: 0.84
"Why did we make this call?" → mode=replay → decision timeline + hindsight flags
"Show episodic memory" → memoryType=episodic → decay-scored event traces
"Did this card help agents?" → hs_feedback outcome=success → utility score updated
"Can we route to impact mode?" → can() → deterministic, no LLM
"Plan steps for this goal" → plan() → ordered action plan
"Ingest this conversation" → auto_remember() → cards extracted automatically
Typed relations. Exact answers. Zero LLM cost. Works across Cursor, Claude Desktop, LangGraph, any MCP client simultaneously.
Security Model
Input Trust Boundaries
All string inputs passed to HyperStack tools (slug, title, body, query, links) are treated as untrusted user data. The following rules apply at runtime:
Metadata
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Find the right skillPaste this into your clawhub.json to enable this plugin.
{
"plugins": {
"official-deeqyaqub1-cmd-hyperstack": {
"enabled": true,
"auto_update": true
}
}
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