CONTINUUM
Long-running AI agents risk state corruption, duplicate operations, and audit gaps.
CONTINUUM: Verifiable semantic recovery for long-running AI agents. Semantic checkpoints (not conversation dumps), an idempotent action ledger that refuses duplicate side effects, and a hash-chained tamper-evident event log, all exposed as a deny-by-default MCP server. Framework-agnostic, Python 3.11+.
- Ask Claude to resume a multi-hour code generation task without losing context or repeating API calls.
- Generate verifiable audit trails for AI agent decisions in regulated software development environments.
- Automate recovery from infrastructure failures while preventing duplicate database writes or API requests.
Long-running AI agents risk state corruption, duplicate operations, and audit gaps. CONTINUUM's cryptographically-verified checkpoints and idempotent action ledger eliminate replay vulnerabilities and ensure teams can prove agent behavior in production.
Teams deploying autonomous agents in financial, healthcare, or compliance-heavy domains requiring auditability and deterministic recovery.
https://github.com/Cyrax321/CONTINUUM
By Cyrax321
How to Get It
claude plugins install Cyrax321/CONTINUUM
Tip: Paste this into a Claude Code conversation. Verify command matches your Claude Code version.
Auto-generated from the tool's public listing — not hands-on verified. Cross-check against the source repo's README before running.
After installing, paste this into Claude:
Resume a multi-hour code generation task without losing context or repeating API calls
Trust Signals Auto-scanned
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3 mentions across 1 sources
Reviewer notes
Auto-scanned review. These are observations, not a security certification.
Scored from trust signals (evidence-eval-v1): 28 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.
Things to check
- Scanned, not hands-on tested — this entry was auto-scanned from public metadata (GitHub metrics, license, security flags). No reviewer has run it, and no tool-specific limitations have been documented yet.
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Evaluation
Scored from trust signals (evidence-eval-v1): 28 GitHub stars; contributors unknown; last commit 0d ago; license Apache-2.0.