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(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
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Builder->Evaluators->Arbitration->accept (Phase 7b)
A deterministic, poll-based watcher (internal/scheduler.StoryOrchestrator,
sibling to the Phase 5 Scheduler) that drives a story.Story through its
execution pipeline, rather than relying on an LLM agent to correctly
orchestrate its own fan-out via tool calls.
Mechanism: polling, not a handleRunResult hook. Every task the orchestrator
watches (a story's root/Builder task, 4 Evaluators, Arbitration) is
top-level (no ParentTaskID), and executor.Pool.handleRunResult only ever
lands a top-level task at READY or BLOCKED -- never COMPLETED directly, since
that transition normally requires a human/chatbot POST /api/tasks/{id}/accept
in a different package. A handleRunResult hook would never observe it;
polling doesn't care how/whether a task reached a given state.
Stages: Builder COMPLETED -> spawn 4 role-typed Evaluator tasks
(evaluator_quality/security/correctness/performance, DependsOn: [builder],
no ParentTaskID -- true DAG siblings, not delegated subtasks) + story ->
VALIDATING. Each Evaluator COMPLETED -> emit KindEvalVerdict (attached to
the story's ID, so one GET /api/stories/{id}/events call surfaces every
verdict). All 4 Evaluators COMPLETED -> spawn 1 Arbitration task
(role: planner, DependsOn: all 4 evaluator IDs). Arbitration COMPLETED ->
emit KindArbitrationDecided, story -> REVIEW_READY. POST
/api/stories/{id}/accept (mirrors handleAcceptTask) -> DONE, emits
KindHumanAccepted.
Fixes a gap caught before merging: since none of Builder/Evaluators/
Arbitration have a ParentTaskID, none of them auto-complete -- each would
otherwise need a separate manual /api/tasks/{id}/accept, meaning 6 human
clicks per story before ever reaching the intended single story-level gate.
StoryOrchestrator.autoAccept now transitions each of these specific tasks
READY->COMPLETED itself (via the same validated Store.UpdateTaskState path
acceptTask uses), scoped only to tasks already established as part of a
story's pipeline (root task, or role-matched dependents from
ensureEvaluators/ensureArbitration) -- never a blanket sweep of unrelated
READY tasks. This makes POST /api/stories/{id}/accept the system's only
required human touchpoint for the whole chain, matching the design goal
that story (not task/subtask) is the human-interaction atom.
Idempotency: structural for task-creation stages (ensureEvaluators/
ensureArbitration check ListDependents for already-existing role-matched
tasks before creating -- crash/restart-safe); story.Status=="VALIDATING"
gates the Arbitration->REVIEW_READY write (nothing further downstream to
check structurally there); an in-memory handledVerdicts set (mirrors
Scheduler.handled) dedupes per-evaluator KindEvalVerdict emission across
poll ticks, resetting harmlessly on restart.
Documented simplification: finalizeArbitration never parses the Arbitration
summary for approve/reject -- always routes to REVIEW_READY; NEEDS_FIX is
manually settable via PUT /api/stories/{id}. A later phase could close this
with a dedicated verdict-reporting AgentChannel method instead of parsing
free text.
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
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Two parts:
Part A (fixes a gap from Phase 1): Groq/OpenRouter/OpenAI were documented in
docs/api-keys-setup.md as usable once configured, but nothing actually
constructed runners for them. internal/cli/cloudrunners.go consolidates
anthropic/google/groq/openrouter/openai NativeRunner construction into one
table-driven registerCloudRunners() helper, replacing the two hand-written
per-provider blocks in serve.go/run.go. Groq/OpenRouter/OpenAI reuse
openaicompat (no new adapter code) at SandboxKind: "docker".
Part B: the token-husbanding harness's core routing mechanism.
- internal/role: RoleConfig/Tier/Rung -- a role's system prompt and a
multi-tier (provider, model) escalation ladder, versioned via config_json.
- storage: new role_configs table (draft/active/retired, UNIQUE(role,
version)) with transactional activate-retires-prior-active semantics;
new executions.escalation_rung column.
- task.AgentConfig.Role string -- purely additive; every existing task shape
(Agent.Role == "") is unaffected, proven by TestPool_Execute_NonRoleTask_Unaffected
plus the full pre-existing suite passing unchanged.
- executor.Pool.execute(): role-typed tasks with no Agent.Type yet resolve
tier 0 of their active ladder (round-robin across multi-candidate tiers,
skipping rate-limited providers, falling back to soonest-clearing) before
the existing pickAgent/Classifier path runs; SystemPrompt applies to
Agent.SystemPromptAppend. Already-resolved role tasks (scheduler resubmits)
get their escalation_rung re-derived read-only via findTierIndex.
- internal/scheduler: polls role-typed FAILED tasks, retries at the same
rung under MaxRetries or escalates to the next tier's first candidate when
budget.Accountant.Allow() permits (emitting event.KindEscalated), else
leaves the task FAILED with a final:true KindEscalated event. An
in-memory per-execution-ID "handled" set keeps the poll loop convergent.
Started by `serve` only, config knob [scheduler].poll_interval_seconds.
- internal/api: POST/GET /api/roles/{role}/versions, POST
/api/roles/{role}/activate -- unauthenticated, matching the existing
projects/tasks REST endpoints' auth posture (only chatbot MCP, agent MCP,
and WebSocket are api_token-gated in this codebase today).
Documented as stored-but-not-yet-enforced (CLAUDE.md Design Debt, matching
how task.Priority/RetryConfig are already documented): RoleConfig.Tools/
SandboxKind don't affect dispatch yet; DefaultBudgetUSD is read narrowly as
the scheduler's escalation cost estimate, not enforced at initial dispatch;
scheduler escalation always targets Candidates[0] (no round-robin, unlike
initial-dispatch tier-0 resolution); the scheduler's dedupe is per-process
and resets on restart (idempotent, harmless).
go build/vet/test -race -count=1 all pass, 21 packages.
Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01V1moSNCJRcP6kykA4tyUSs
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