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Changelog

and this project adheres to Semantic Versioning.

[0.3.0] - 2026-09-30

Added

  • lineage new <name> [--template python|rust]: creates a runnable guarded-agent project (a Python refund-support agent for the guard server, or a Rust in-process deploy agent), with a policy, a scripted model, and tests.
  • Lineage Mastery: ten runnable levels, from a first guarded action to production (examples/mastery_0*.rs, examples/python/lesson0*.py), with a docs course at docs.lineagrs.tech/mastery.
  • Documentation: Lineage in pictures, Why Lineage, project setup, running a project, building an app, and an examples gallery, with diagrams generated by docs/book/tools/diagrams.py.
  • Landing page: a story section, an animated request flow, and an in-browser guard playground with a real SHA-256 hash chain and tamper detection.
  • Website at lineagrs.tech, documentation at docs.lineagrs.tech, and static Linux x86-64 binaries (lineage, guard-server) with SHA-256 checksums and a verifying install script.
  • apps/deepseek-payments-agent: an accounts-payable agent on DeepSeek V4.x. A deepseek-flash clerk and a deepseek-v4-pro fraud reviewer work under the guard, whose budget is the agent’s spending authority. Layered approval runs hard rules, then the model, then humans above a limit. The bank enforces guard approvals itself (exact input match, single use). Includes offline scenarios and 19 tests.
  • Guard actions keep their requested input (GET /v1/agents/:id/actions/:action_id returns it), so tool backends can check that what they execute is exactly what was approved.
  • guard-server no longer requires GUARD_ADMIN_TOKEN: without it, the server uses keys/admin.token in its data directory, creating it on first start. The Python client finds the token (find_admin_token, connect_admin) and explains setup problems: server not running, token mismatch, or missing key.
  • Approvals take an optional note, signed into the log (Guard::approve_with_note, {"approver", "note"}).
  • apps/guarded-agent: an incident-response agent on Claude Opus 5.5 where every model turn and tool call passes through the guard. Includes a prompt-injection scenario, secret redaction, an exfiltration monitor that reports harm, human approvals, a scripted model for offline runs, and integration tests.
  • Operator console in guard-server at /: agents, approval queue, audit log, log verification, and terminate. It is served with a strict Content Security Policy and renders agent data as text only.
  • audit module: persistent, SHA-256 hash-chained, Ed25519-signed audit logs (JSON Lines), with offline verification, checkpoints to detect truncation, and a single-writer file lock.
  • guard module: a policy gate for AI agents. Tool allowlists, a finite budget, rate limits, per-tool call caps, human approval, scars, and permanent termination. State is rebuilt by replaying the verified audit log, so restarts cannot refund budget or revive an agent.
  • lineage audit CLI: keygen, pubkey, append, show, verify.
  • apps/guard-server: HTTP API for the guard with per-agent tokens, an approval queue, quarantine of tampered logs, a Docker image, and a dependency-free Python client.
  • guarded_agent example.

Changed

  • Breaking: the finance module is behind the finance feature and the lineage binary behind cli. Both are on by default. Use default-features = false for the lean core.
  • Breaking: minimum Rust version is 1.89.
  • Dependencies only used by examples (ratatui, crossterm, plotters, hyper, …) are now dev-dependencies; unused image and governor were removed.
  • reqwest uses rustls, so OpenSSL is no longer needed to build.
  • The lineage binary uses the library instead of recompiling the core modules.
  • Status reports moved to docs/archive/, reference docs to docs/, and scripts to scripts/.

Fixed

  • Guard::open terminates an agent whose log shows its scar limit reached or budget spent, but whose terminated record is missing (cut off the end), so deleting that record can’t revive it.
  • Graveyard signing keys were derived from a timestamp and could be guessed; they now come from the OS CSPRNG.
  • Unit tests in finance::data_providers, finance::visualization, and finance::ml::market_data did not compile.
  • The colors, metrics_server, and phase3_training_with_evolution examples did not compile.

Security

  • .env (containing an API key) and .lineage/keys/tombstone.key were committed in earlier versions. Both are now untracked and ignored. Rotate any key that was in them.

[0.2.0] - 2026-02-01

🚀 Added

Lineage Finance Module (NEW!)

A complete evolutionary trading platform extending Lineage core with:

  • FinanceAgent (src/finance/agent.rs): Trading agents with finite capital, trade history, and lifecycle management
  • Irreversible Trade Operations (src/finance/trade.rs): Buy/sell execution with no rollback, P&L calculations, leverage support
  • Financial Scar Mechanics (src/finance/scars.rs): Permanent damage from losses with cost multipliers, leverage restrictions
  • Spawning & Inheritance (src/finance/spawning.rs): Successful agents spawn offspring inheriting optimized traits
  • Cryptographic Trust Scoring (src/finance/trust_scoring.rs): Performance-based trust with tiered grants and permissions
  • Multi-Agent Arena (src/finance/arena.rs): Competition simulations with market state evolution
  • Advanced Features (src/finance/advanced.rs): Blockchain hooks, evolutionary AI framework, real-time adaptation, irreversible governance

Examples

  • decentralized_trading_agent (examples/decentralized_trading_agent.rs): Full-featured demo showcasing all finance modules:
    • Agent lifecycle demo (capital depletion, trade recording)
    • Spawning mechanics (inheritance, cost calculation)
    • Trust scoring (performance-based, permission grants)
    • Arena competition (market simulation, agent ranking)
    • Advanced features (blockchain integration, evolutionary strategies, governance)

Documentation

Key Features

✅ Irreversible State: Trades execute once with permanent consequences
✅ Finite Resources: Agents operate under capital constraints
✅ Permanent Scars: Losses permanently increase transaction costs
✅ Evolutionary Dynamics: Successful lineages spawn optimized descendants
✅ Trust-Based Access: Cryptographic trust scores determine resource availability
✅ Multi-Agent Competition: Arena simulations with emergent behavior
✅ Auditability: Sealed graveyard archives for regulatory compliance
✅ Extensibility: Trait-based design for custom strategies

Architecture

  • 8 new modules under src/finance/
  • Integration with existing Lineage core (Identity, Metabolism, ScarTissue, Trust)
  • ~1800 lines of production-ready Rust
  • Comprehensive example demonstrating all features
  • Zero compiler warnings

Testing

  • All 120 existing Lineage tests pass
  • New finance modules compile cleanly
  • Example executable runs without errors

Roadmap (Phase 2)

  • Evolutionary AI integration (PyTorch via tch-rs)
  • Blockchain deployment (Solana/Ethereum)
  • Real-time market adaptation (Chainlink oracles)
  • Community governance DAOs
  • Permadeath economy mechanics

[0.1.0] - 2026-01-30

Initial Release

Core Lineage framework with:

  • Unique, immutable agent identities
  • Append-only tamper-proof history
  • Finite energy system
  • Permanent scar mechanics
  • Trust scoring
  • Genealogical spawning
  • 12 interactive examples
  • 120 comprehensive tests

Release Notes

v0.2.0 Highlights

Position: This release establishes Lineage as a foundational framework for evolutionary finance. By combining irreversible state transitions with trading mechanics, we’ve created a platform where:

  1. AI agents must account for consequences — No reset buttons forces evolutionary pressure
  2. Trust is cryptographically proven — Not assumed; earned through verifiable history
  3. Success breeds success — Spawning mechanisms create lineages of increasingly optimized traders
  4. Failure teaches permanently — Scars compound, forcing strategic adaptation

Narrative: “We built trading bots that actually die—and their descendants learn from it.” This positions Lineage to disrupt traditional algorithmic trading by introducing Darwinian evolution to DeFi.

Contribution Notes

For contributors interested in Phase 2 (evolutionary AI, blockchain integration):

  1. Check FINANCE_IMPLEMENTATION_ROADMAP.md for feature status
  2. Open GitHub issues for feature requests
  3. See CONTRIBUTING.md for guidelines
  4. Phase 2 features are marked with 🔄 (planned) or 📋 (design phase)

Last Updated: February 1, 2026