- Add Mission type and MissionManager for recurring thread scheduling
- Add ReliabilityTracker for per-capability success/failure/latency tracking
- Add reflection executor that spawns CodeAct threads for post-completion reflection
- Extend PolicyEngine with provenance-aware taint checking (LLM-generated data
requires approval for financial/external-write effects)
- Extend Store trait with mission CRUD methods
- Add conversation surface tracking, compaction token fix, context memory injection
- Wire new modules through lib.rs re-exports and bridge adapters
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
When code fails with NameError/UnboundLocalError (model trying to
access variables from a previous step), the error output now includes:
[HINT] Variables don't persist between code blocks. Use the `state`
dict to access data from previous steps. Available keys: ["web_search",
"last_return"]
This teaches the model to use `state["web_search"]` instead of `result`
after a NameError, reducing wasted steps from 3-4 to 1.
Also integrates RetrievalEngine into context building and ThreadManager:
- build_step_context() now accepts optional RetrievalEngine to inject
relevant memory docs (Lessons, Specs, Playbooks) into LLM context
- RetrievalEngine uses keyword matching with doc-type priority scoring
- Memory docs from reflection (Phase 4) now feed back into future threads
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
After every thread completes, ThreadManager now automatically runs:
1. Retrospective trace analysis (non-LLM, always):
- Detects 8 issue categories (tool errors, code errors, missing
outputs, excessive steps, hallucination risk, etc.)
- Logs issues at warn level when found
2. Trace file recording (when ENGINE_V2_TRACE=1):
- Writes full JSON trace to engine_trace_{timestamp}.json
3. LLM reflection (when enable_reflection=true):
- Calls reflection pipeline to produce Summary, Lesson, Issue docs
- Saves docs to store for future context retrieval
- Enabled by default in the bridge router
All three run inside the spawned tokio task after exec.run() completes,
before saving the final thread state. No external wiring needed.
Removed duplicate trace recording from the router — it's now handled
by ThreadManager automatically.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
Enable with ENGINE_V2_TRACE=1 to get full execution traces and
automatic issue detection after each thread completes.
Trace recording (executor/trace.rs):
- build_trace(): captures full thread state — messages (with full
content), events, step count, token usage, detected issues
- write_trace(): writes JSON to engine_trace_{timestamp}.json
- log_trace_summary(): logs summary + issues at info/warn level
Retrospective analyzer detects 8 issue categories:
- thread_failure: thread ended in Failed state
- no_response: no assistant message generated
- tool_error: specific tool failures with error details
- code_error: Python errors (NameError, SyntaxError, etc.) in output
- missing_tool_output: tool results exist but not in system messages
- excessive_steps: >10 steps (may be stuck in loop)
- no_tools_used: single-step answer without tools (hallucination risk)
- mixed_mode: text responses without code blocks (prompt not followed)
Thread state now saved to store after execution completes (for trace
access after join_thread).
Usage:
ENGINE_V2=true ENGINE_V2_TRACE=1 cargo run
# After each message: trace JSON + issue log in terminal
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
Engine v2 now shows live progress in the CLI (and any channel):
- "Thinking..." when a step starts
- Tool name + success/error when actions execute
- "Processing results..." when a step completes
Implementation:
- ThreadManager holds a broadcast::Sender<ThreadEvent> (capacity 256)
- ExecutionLoop.emit_event() writes to thread.events AND broadcasts
- ThreadManager.subscribe_events() returns a receiver
- Router uses tokio::select! to listen for events while waiting for
thread completion, forwarding them as StatusUpdate to the channel
This replaces the polling approach with zero-latency event streaming.
Agent.channels visibility widened to pub(crate) for bridge access.
102 tests passing, zero clippy warnings.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
The engine was creating a fresh ThreadManager and InMemoryStore per
message, losing all context between turns. A follow-up question like
"what are the latest 10 issues?" had no memory of the prior "how many
issues" response.
Fixes:
- EngineState (ThreadManager, ConversationManager, InMemoryStore) now
persists across messages via OnceLock, initialized on first use
- ConversationManager builds message history from prior conversation
entries (user messages + agent responses) and passes it to new threads
- ThreadManager.spawn_thread_with_history() accepts initial_messages
that are prepended before the current user message
- System notifications (thread started/completed) are filtered out of
the history (not useful as LLM context)
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
The ExecutionLoop was sending empty messages to the LLM because the
thread was spawned with the user's input as the goal but no messages.
Fixes:
- ThreadManager.spawn_thread() now adds the goal as an initial user
message before starting the execution loop
- ExecutionLoop.run() injects a default system prompt if none exists
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
Conversation is now a UI layer, not an execution boundary. Multiple
threads can run concurrently within one conversation; threads can
outlive their originating conversation.
New types (types/conversation.rs):
- ConversationSurface: channel + user + entries + active_threads
- ConversationEntry: sender (User/Agent/System) + content + origin_thread_id
- ConversationId, EntryId (UUID newtypes)
- EntrySender enum (User, Agent{thread_id}, System)
ConversationManager (runtime/conversation.rs):
- get_or_create_conversation(channel, user) — indexed by (channel, user)
- handle_user_message() — injects into active foreground thread or spawns new
- record_thread_outcome() — adds agent/system entries, untracks completed threads
- get_conversation(), list_conversations()
This enables the key architectural insight: a user can ask "what's the
weather?" while a deployment thread is still running. Both produce entries
in the same conversation.
85 tests passing, zero clippy warnings.
Co-Authored-By: Claude Opus 4.6 (1M context) <[email protected]>
