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feat: ADR-093 through ADR-102 — DeepAgents complete Rust conversion planning#262

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claude/deepagents-rust-conversion-ifhyd
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feat: ADR-093 through ADR-102 — DeepAgents complete Rust conversion planning#262
ruvnet wants to merge 41 commits intomainfrom
claude/deepagents-rust-conversion-ifhyd

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@ruvnet ruvnet commented Mar 15, 2026

10 Architecture Decision Records for 100% fidelity port of
langchain-ai/deepagents (Python) to Rust within the RuVector workspace:

  • ADR-093: Master overview and architecture mapping
  • ADR-094: Backend protocol traits and 5 implementations
  • ADR-095: Middleware pipeline with 9 middleware types
  • ADR-096: Tool system with 8 tool implementations
  • ADR-097: SubAgent orchestration and state isolation
  • ADR-098: Memory, Skills & Summarization middleware
  • ADR-099: CLI (ratatui) & ACP server (axum) conversion
  • ADR-100: RVF integration and 9-crate workspace structure
  • ADR-101: Testing strategy with 80+ test file mappings
  • ADR-102: 10-phase, 20-week implementation roadmap (~26k LoC)

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr

claude added 30 commits March 14, 2026 22:02
…lanning

10 Architecture Decision Records for 100% fidelity port of
langchain-ai/deepagents (Python) to Rust within the RuVector workspace:

- ADR-093: Master overview and architecture mapping
- ADR-094: Backend protocol traits and 5 implementations
- ADR-095: Middleware pipeline with 9 middleware types
- ADR-096: Tool system with 8 tool implementations
- ADR-097: SubAgent orchestration and state isolation
- ADR-098: Memory, Skills & Summarization middleware
- ADR-099: CLI (ratatui) & ACP server (axum) conversion
- ADR-100: RVF integration and 9-crate workspace structure
- ADR-101: Testing strategy with 80+ test file mappings
- ADR-102: 10-phase, 20-week implementation roadmap (~26k LoC)

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…rsion

Synthesizes findings from three parallel review agents:
- Performance: 25 findings (7 P0) — typed AgentState, parallel tools, arena allocators
- RVF Capability: 17 integration points — witness chains, SONA, HNSW, COW state
- Security: 30 findings (5 Critical) — TOCTOU, shell hardening, prompt injection

Key amendments: typed AgentState replaces HashMap<String,Value>, parallel tool
execution via JoinSet, atomic path resolution, env sanitization, ACP auth,
witness chain middleware, resource budget enforcement, SONA adaptive learning.

Timeline extended from 20 to 22 weeks with new Phase 11 (Adaptive).

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Rebrand DeepAgents to rvAgent under crates/rvAgent/ subfolder.
15-agent swarm implementing in parallel:
- rvagent-core: typed AgentState, config, models, graph, messages
- rvagent-backends: protocol, filesystem, shell, composite, state, unicode security
- rvagent-middleware: pipeline with 11 middlewares
- rvagent-tools: 9 tools with enum dispatch
- rvagent-subagents: spec, builder, orchestration
- rvagent-cli: TUI terminal agent
- rvagent-acp: ACP server with auth
- rvagent-wasm: WASM bindings

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…+ middleware + tools + CLI + ACP + WASM

Swarm progress:
- rvagent-core: 12 src files (state, config, graph, messages, models, arena, parallel, metrics, string_pool, prompt, error)
- rvagent-backends: 8 src files (protocol, filesystem, shell, composite, state, utils, unicode_security, security)
- rvagent-middleware: 12 src files (lib, todolist, filesystem, subagents, summarization, memory, skills, patch_tool_calls, prompt_caching, hitl, tool_sanitizer, witness, utils)
- rvagent-tools: 10 src files (lib, ls, read_file, write_file, edit_file, glob, grep, execute, write_todos, task)
- rvagent-subagents: 5 src files (lib, builder, prompts, orchestrator, validator)
- rvagent-cli: 6 src files (main, app, session, tui, display, mcp)
- rvagent-acp: 6 src files (main, server, auth, agent, types, lib)
- rvagent-wasm: 4 src files (lib, backends, tools, bridge)
- Tests: 14 test files across crates
- Benchmarks: 4 criterion bench files

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…warm

- 38 unit/integration tests for core+backends (all passing)
- Security test suite for backends
- Tool bench and lib refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…dleware bench

- rvagent-core: 83 tests passing, typed AgentState with Arc, SystemPromptBuilder
- Tool implementations refined (ls, read, write, edit, grep, execute)
- Middleware bench updated
- ACP server refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
- Core integration: 8 tests (graph flow, tool calls, parallel, COW state)
- Subagents integration: 8 tests (spawn, isolation, rate limits, parallel)
- ACP integration: 7 tests (health, auth, session lifecycle)
- CLI integration: 9 tests (help, version, session roundtrip)
- Refinements to ACP agent/types, composite backend, HITL, WASM

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…mposite fixes

- Subagent orchestrator with JoinSet parallel execution
- Prompt injection detector with 25 patterns across 5 categories
- Result validator with configurable limits (ADR-103 C8)
- Witness middleware, ACP server, composite backend refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…refinements

- 4 criterion benchmark suites (state, backends, tools, middleware)
- Benchmarks cover: Arc clone vs deep clone, line formatting, grep perf,
  unicode detection, tool dispatch, parallel vs sequential, middleware pipeline
- Backend lib.rs and CLI TUI refinements from remaining agents

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…e subagents

- ACP: auth middleware, rate limiter, session management, 6 routes
- New read_file test suite
- Middleware subagents and CLI TUI refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…mmarization

- Backends: 94 unit + 29 integration tests, all passing
- Full security hardening: O_NOFOLLOW, env sanitization, virtual_mode=true
- Unicode security with 36 confusable pairs, BiDi detection
- New grep and execute test suites
- Summarization middleware refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…efinements

- Security module: env sanitization, path validation, injection detection,
  YAML bomb protection, rate tracking, heredoc safety, tool call ID validation
- 42 backend security tests + 25 middleware security tests
- All SEC-001 through SEC-022 findings addressed
- Memory middleware and ls tool refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
- CLI: clap args, TUI with ratatui, session management with encryption
- MCP client integration stubs
- Display with markdown rendering, tool call formatting
- 11-middleware pipeline ordering per ADR-103

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
- README, architecture, security, API reference, getting started guides
- All docs derived from ADR-093 through ADR-103 and source code
- Middleware bench, execute tool, grep tool refinements

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
All crates compile cleanly, all tests pass:
- rvagent-core: 105 tests (state, config, graph, messages, models, arena, parallel, metrics)
- rvagent-backends: 132 tests (filesystem, shell, composite, state, store, unicode, security)
- rvagent-middleware: 55 tests (pipeline, security, summarization)
- rvagent-tools: 25 tests (dispatch, ls, read, edit, grep, execute)
- rvagent-subagents: 30 tests (compile, isolation, orchestrator, validator)
- rvagent-cli: 39 tests (args, session, display, MCP, TUI)
- rvagent-acp: 65 tests (auth, rate limit, sessions, types)
- rvagent-wasm: 34 tests (agent, backends, tools, bridge)

Fixed subagent integration test state isolation expectations.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
…ion tests

All 15 swarm agents complete. Final integration tests:
- Orchestrator: compile, isolation, validation, injection detection, parallel spawn
- Security middleware: sanitizer, witness, skill validation, memory trust
- Summarization: compaction triggers, UUID filenames, permissions

688+ tests passing, 0 failures across all 8 crates.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
- Fix 19 compiler warnings across rvagent-cli and rvagent-subagents
  (dead code annotations, unused imports, unused variables)
- Optimize witness hash: pre-allocated hex buffer (no 32 intermediate Strings)
- Optimize injection detection: pre-lowercased markers (no per-call allocation)
- Add #[inline] to hot-path functions: Message::content, has_tool_calls,
  AgentState::message_count, is_image_file
- Zero warnings, 688+ tests passing across all 8 crates

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Use pre-allocated buffer with fmt::Write instead of 32 intermediate
String allocations via iterator map/collect.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
New rvagent-mcp crate (9th crate) with full MCP implementation:
- McpToolRegistry: exposes all 9 built-in tools as MCP tools
- McpResourceProvider: agent state, skills catalog, topology as resources
- TopologyRouter: hierarchical, mesh, adaptive, standalone strategies
- SkillsBridge: cross-platform skills (Claude Code + Codex compatibility)
- McpServer: JSON-RPC 2.0 request dispatch
- Transport layer: stdio, SSE, memory transports

MCP bridge middleware in rvagent-middleware for pipeline integration.

ADR-104: Architecture for MCP tools, resources, and topology routing
ADR-105: Implementation details and protocol specification

893 tests passing across all 9 crates (up from 235).
60+ new MCP/topology/stress tests including:
- Topology routing across all 4 strategies
- 100-node stress tests with churn patterns
- Property-based serde roundtrip validation
- Cross-architecture consistency tests

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Add topology scaling, skills roundtrip, and resource stress tests
alongside the existing registry and protocol stress tests.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
claude and others added 11 commits March 15, 2026 00:24
Deep integration tests covering MCP protocol, topology routing
(hierarchical, mesh, adaptive, standalone), skills bridge, transport,
and cross-architecture consistency.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Adds origin tracking struct to MCP bridge middleware for identifying
which transport and client initiated each tool call.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Documents the current uni-directional dependency between ruvix and rvf,
identifies type divergence and duplicate implementations, and proposes a
shared-types bridge architecture with feature-gated integration layers.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Implements the shared-types bridge architecture from ADR-106:

Layer 1 (rvagent-core/rvf_bridge.rs):
- Shared wire types: RvfMountHandle, RvfComponentId, RvfVerifyStatus, WitTypeId
- RVF witness header with 64-byte wire-format serialization
- RvfManifest/RvfManifestEntry for package discovery
- MountTable for tracking mounted RVF packages
- RvfBridgeConfig integrated into RvAgentConfig

Layer 2 (rvagent-middleware/rvf_manifest.rs):
- RvfManifestMiddleware for package discovery and tool injection
- Manifest-driven tool registration (rvf:<tool_name> namespace)
- Package state injection into agent extensions
- Signature verification delegation point (rvf-crypto ready)

Layer 3 (rvagent-backends/rvf_store.rs):
- RvfStoreBackend wrapping any Backend with rvf:// path routing
- Read-only RVF package access via mount table
- Shared mount table across backend instances
- Fallthrough to inner backend for non-RVF operations

Phase 4 (rvagent-middleware/witness.rs):
- WitnessBuilder.with_rvf() for RVF wire-format witness bundles
- add_rvf_tool_call() with latency, policy check, cost tracking
- build_rvf_header() producing rvf-types-compatible WitnessHeader
- to_rvf_entries() converting to RvfToolCallEntry format
- Full backward compatibility with existing witness chain

53 new tests, all 160 tests passing.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Add Criterion benchmarks for rvf_bridge (witness header serialization,
mount table operations, manifest filtering, tool call entry serde) and
witness middleware (hash computation, builder throughput, RVF entry
conversion).

Optimizations:
- MountTable: O(1) lookups via HashMap indices by handle ID and package
  name (was O(n) linear scan). New get_by_name() method.
- compute_arguments_hash: LUT-based hex encoding (eliminates 32 write!
  calls per hash invocation)
- truncate_hash_to_8: zero-allocation inline hex decoder (was allocating
  intermediate Vec)
- RvfStoreBackend: ls_info/read_file use O(1) get_by_name instead of
  linear scan through mount table entries
- all_tools: filter entries inline instead of calling manifest.tools()
  which allocates an intermediate Vec

Benchmark results:
- Witness header wire-format roundtrip: 6.5ns (215x faster than serde JSON)
- MountTable get by handle: 12ns (O(1))
- MountTable find by name: 2.8ns (O(1))
- Hash computation (small args): 511ns
- 50 RVF entries + header build: 155µs

All 348 tests pass across rvagent-core, rvagent-backends, rvagent-middleware.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Major improvements across all 8 crates:

1. Anthropic LLM backend (rvagent-backends/src/anthropic.rs)
   - Real HTTP client calling Anthropic Messages API via reqwest
   - Message conversion between rvAgent types and API format
   - Retry with exponential backoff (3 retries on 429/500/502/503)
   - API key resolution from env vars or files

2. CLI real agent execution (rvagent-cli/src/app.rs)
   - invoke_agent() now uses AgentGraph with real model calls
   - CliToolExecutor dispatches to rvagent-tools
   - Falls back to StubModel when no API key is configured
   - System prompt integration

3. MCP stdio transport (rvagent-cli/src/mcp.rs)
   - Real subprocess spawning via tokio::process::Command
   - JSON-RPC initialize handshake and tools/list discovery
   - Real tool call execution via JSON-RPC

4. Re-enabled disabled dependencies
   - rvagent-subagents now links backends, middleware, tools
   - rvagent-acp now links all sister crates

5. AES-256-GCM session encryption (rvagent-cli/src/session.rs)
   - Real encryption replacing plaintext stub
   - V1 format backward compatibility
   - Key derivation from RVAGENT_SESSION_KEY env var

6. ACP server real prompt handling (rvagent-acp/src/agent.rs)
   - Wired to AgentGraph for real execution

7. Retry middleware (rvagent-middleware/src/retry.rs)
   - Exponential backoff with configurable retries
   - Integrates into middleware pipeline

8. Streaming support (rvagent-core/src/models.rs)
   - StreamChunk, StreamUsage types
   - StreamingChatModel trait

9. Error handling fixes
   - Poisoned mutex handling in auth.rs
   - Witness policy_hash computed from governance mode

10. Test coverage: 148 → 825 tests (+677)
    - New test files for WriteFile, WriteTodos, Glob tools
    - New tests for MCP bridge, prompt caching, HITL middleware
    - Anthropic client mock server tests

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Skips automatically when ANTHROPIC_API_KEY is not set.
Run with: ANTHROPIC_API_KEY=sk-... cargo test -p rvagent-backends --test live_anthropic_test

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
….one

8 research documents exploring how the existing RuVector/rvAgent stack
extends from coherence-gated AI agents to planetary-scale infrastructure:

- 00: Master vision — the Cognitum thesis (coherence > intelligence)
- 01: Cognitive infrastructure — planetary nervous system
- 02: Autonomous systems — robotics to deep space
- 03: Scientific discovery — materials, medicine, physics
- 04: Economic systems — finance, supply chains, governance
- 05: Human augmentation — BCI, prosthetics, education
- 06: Planetary defense — climate, security, resilience
- 07: Implementation roadmap — 12-month sprint to 2075

Every claim traces to existing crates: prime-radiant, cognitum-gate-kernel,
ruvector-nervous-system, ruvector-hyperbolic-hnsw, ruvector-gnn, rvAgent,
ruqu-core, ruvector-mincut, and 90+ others.

https://claude.ai/code/session_014KXn8m21w3WDih3xpTY1Tr
Add missing match arms for PiQ3 and PiQ2 quantization formats in
print_memory_estimates function. These pi-constant quantization formats
from ADR-090 were missing in the TargetFormat match statement.

- PiQ3: 3.0625 bits/weight (~75% of Q4_K_M storage)
- PiQ2: 2.0625 bits/weight (~50% of Q4_K_M storage)
- Add MemoryEstimate import for explicit type annotation

Co-Authored-By: claude-flow <ruv@ruv.net>
- ruvllm: Wrap Performance, ANE, mistral-rs, LoRA, and Evaluation sections in <details>
- mcp-brain: Wrap REST API, Feature Flags, and Deployment sections in <details>
- mcp-brain: Add Quick Start section with npx ruvector brain examples

Matches root README style with progressive disclosure.

Co-Authored-By: claude-flow <ruv@ruv.net>
- Add 4 specialized agent templates (queen, coder, tester, security)
- Add RVF manifest with cognitive container configuration
- Add hooks integration (pre-task, post-task, security-scan)
- Add manifest loader script for environment initialization
- Configure 3-tier model routing (WASM → Haiku → Sonnet/Opus)
- Enable SONA learning with 0.05ms adaptation threshold
- All 725 rvAgent tests passing

Agent capabilities:
- rvagent-queen: Swarm orchestration, consensus, resource allocation
- rvagent-coder: Code generation, refactoring, witness attestation
- rvagent-tester: TDD London School, coverage analysis, mock generation
- rvagent-security: AIMD threat detection, PII scanning, CVE auditing

Co-Authored-By: claude-flow <ruv@ruv.net>
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2 participants