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12 daysfeat(story,role): add retro ceremony -- closes the self-improvement loop ↵Claude Sonnet 5
(Phase 8) The final mechanism the versioned role-config model (Phase 5) was built for: when a story reaches DONE, StoryOrchestrator spawns a retro-role task that reflects on the story's full history and proposes draft role_configs versions for a human to review and activate via the existing (unchanged) POST /api/roles/{role}/activate. - AgentChannel gains a 6th method, ProposeRoleConfig(ctx, role.RoleConfig) (version, err), following ProposeEpic's precedent (Phase 7c): a structured tool call, not summary-parsing. storeChannel.ProposeRoleConfig calls the same Store.CreateRoleConfig the human-facing POST /api/roles/{role}/versions endpoint already uses (proposed_by: "retro"), landing a new draft row without touching whatever's currently active. Wired through both transports exactly like ProposeEpic: internal/agentloop/tools.go (native loop) and internal/executor/agentmcp.go (MCP). - StoryOrchestrator.Tick now routes a story at status DONE to a new processRetro stage instead of processStory -- a sibling stage, not a continuation, since the Builder->Evaluators->Arbitration chain is long settled by then. processRetro only *reads* that settled pipeline (read-only findEvaluators/findArbitration counterparts to ensureEvaluators/ensureArbitration -- it never spawns/mutates Builder-pipeline tasks) to locate the Arbitration task the retro task depends on, then spawns (idempotently -- checks for an existing retro-role dependent first) one retro-role task with instructions assembled from the story's spec/acceptance-criteria, full task tree, per- task cost/escalation history, active role_configs per role encountered, and the story's own event stream (evaluator verdicts, arbitration decision). - event.KindRetroCaptured (attached to the story's ID, matching KindEvalVerdict/KindArbitrationDecided's convention) fires once the retro task completes (auto-accepted like every other pipeline task), aggregating every event.KindRoleConfigProposed the retro task recorded (one per propose_role_config call) into {task_id, proposals: [{role, version}], summary} -- the summary is the "capturing lessons" half of this ceremony, the proposals are the versioned-config half. - Human activation is completely untouched: drafts land through the identical CreateRoleConfig/config_json path Phase 5's endpoints already handle, confirmed via existing role-endpoint tests passing unmodified. go build/vet/test -race -count=1 all pass, full suite (20 packages) -- one run hit a known, pre-existing, intermittent flake under full-suite load (unrelated to this phase's files) that did not reproduce on two immediate reruns, both in isolation and full-suite. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs
12 daysfeat(story,scheduler): add epic-proposal tool + AskUser-timeout escalation ↵Claude Sonnet 5
(Phase 7c) Two independent pieces, completing Phase 7. Epic-proposal tool: AgentChannel gains a 5th method, ProposeEpic(ctx, EpicProposal{Name, Description, StoryIDs}) (epicID, err), implemented on storeChannel -- matches an existing epic by exact name or creates one (DiscoverySource: "agent"), sets epic_id on each resolvable story (skips, doesn't fail, on an unresolved ID), emits KindEpicProposed attached to the epic's own ID with payload {epic_id, name, story_ids}. Wired into both transports exactly like Phase 6 wired role into spawn_subtask: a new propose_epic tool in the native tool-use loop (internal/agentloop/tools.go) and the MCP transport (internal/executor/agentmcp.go). This is the mechanism for a discovery/planner-role agent to act on its own judgment that several stories it's been given form one cohesive initiative -- the judgment itself lives in the calling agent's instructions/model, not in this code. AskUser-timeout escalation: extends the existing Scheduler (Phase 5's retry-then-escalate watcher) rather than adding a new component, since "stuck task needs escalation" is exactly what it already does. Finds role-typed BLOCKED tasks whose question has been outstanding longer than SchedulerConfig.AskUserTimeoutSeconds (default 10 minutes) using task.UpdatedAt as the outstanding-since timestamp -- no new column needed, since UpdateTaskQuestion already stamps it the instant a question is recorded and nothing else touches the row while BLOCKED. Resolves the next ladder tier from the latest execution's EscalationRung, records the system-authored fallback answer as an audit-trail task.Interaction, clears the question, sets the new tasks.needs_review flag, emits KindEscalated (now carrying a trigger field: "failure" vs "ask_user_timeout" for the existing failure-retry path vs this one), and resumes via Pool.SubmitResume at the escalated tier -- degrading to same-tier resume with final:true if the ladder's exhausted or no role config exists, since unblocking the task takes priority over having somewhere higher to escalate to. GET /api/tasks?needs_review=true surfaces auto-decided tasks for human review. go build/vet/test -race -count=1 all pass, full suite (20 packages), run twice to rule out flakiness in the new tests. (One pre-existing, unrelated test -- TestHandleRunTask_CascadesRetryToFailedDeps, a tempdir-cleanup race -- appeared once under full-suite load per the implementing agent's report and did not reproduce in this verification's runs either; not a regression from this work.) Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs
13 daysfeat(executor): add DAG auto-cascade-fail + role-typed subtask spawning ↵Claude Sonnet 5
(Phase 6) Two prerequisites for safe parallel evaluator fan-out (later phase): 1. Auto-cascade-fail: previously, a failed task's dependents just sat PENDING/QUEUED forever (or until something eventually tried to dispatch them and discovered the dependency was dead). Pool.cascadeFail now fires right after a task lands in a terminal failure state (FAILED/TIMED_OUT/ CANCELLED/BUDGET_EXCEEDED, from handleRunResult, the budget-gate reject path, and the checkDepsReady dependency-failure path), recursively cancelling every not-yet-run dependent (PENDING/QUEUED only -- RUNNING and terminal states are left alone) with a message referencing the upstream failure. A visited-set guards recursion, which turned out to be load-bearing rather than defense-in-depth: task creation does not prevent dependency cycles anywhere in this codebase. Correction to an earlier assumption: internal/executor's waitForDependencies is dead code, never called. The live mechanism is checkDepsReady, invoked synchronously in execute() with a self-requeue via time.AfterFunc. Added a freshness re-check (GetTask, bail if no longer QUEUED) at the top of that block so a task cascade-cancelled while sitting in the requeue loop stops silently instead of hitting an invalid CANCELLED->CANCELLED transition or, worse, still getting dispatched. 2. storeChannel.SpawnSubtask hardcoded Agent.Type: "claude" on every spawned child regardless of what role it should play -- a hard blocker for a Planner/Builder task spawning role-typed evaluator subtasks. SubtaskSpec (internal/agentchannel) gains a Role field; when set, the child task gets Agent.Role instead of a hardcoded Type, so Phase 5's role-resolution picks provider/model from that role's escalation ladder. spec.Role == "" (every existing caller) preserves today's exact behavior byte-for-byte -- proven by an explicit regression test, not just new-feature coverage. Threaded the new `role` parameter through both spawn_subtask transports: the native tool-use loop (internal/agentloop/tools.go) and the MCP tool exposed to ContainerRunner-driven claude/gemini agents (internal/executor/agentmcp.go). go build/vet/test -race -count=1 all pass, full suite (20 packages). Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs
13 daysrefactor(executor): extract provider-neutral tool-use loop (Phase 1)Claude Sonnet 5
Splits LocalRunner's OpenAI-specific agentic loop into reusable, provider- agnostic pieces so later phases can add native Anthropic/OpenAI/Google/Groq/ OpenRouter adapters without duplicating the control flow: - internal/provider: neutral Provider/ChatRequest/ChatResponse types, plus an openaicompat adapter wrapping the existing internal/llm.Client unchanged - internal/sandbox: Sandbox interface + HostSandbox (git clone/push/cleanup, read_file/write_file/run_bash/glob), lifted verbatim from local.go/localtools.go - internal/agentloop: the extracted tool-use loop (request/response/tool- dispatch/loop, ask_user blocking, stream-json envelope, summary fallback) - internal/agentchannel: AgentChannel/SubtaskSpec/BlockedError/ErrAgentBlocked moved out of internal/executor so agentloop can use them without an import cycle; internal/executor re-exports via type aliases, so no call site changes - internal/executor/nativerunner.go: NativeRunner replaces LocalRunner, wiring agentloop.Loop + openaicompat + HostSandbox together - config.Providers map[string]ProviderConfig added (unused until Phase 2+) Zero intended behavior change: go test -race ./... passes across all packages, and end-to-end stream-json/summary/changestats output was verified byte-compatible against a fake OpenAI-compatible server. Adds test coverage for sandbox tool-dispatch (git clone/push, read/write/bash/glob) that LocalRunner never had. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs