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(Phase 2)
Rewrites the planning preamble to point the agent at the four MCP tools
(ask_user/report_summary/spawn_subtask/record_progress) instead of the
CLAUDOMATOR_QUESTION_FILE / CLAUDOMATOR_SUMMARY_FILE conventions: ask_user ends
the turn, report_summary replaces the summary file, spawn_subtask replaces the
POST-to-/api/tasks planning step. Git discipline is retained.
ContainerRunner previously applied no preamble at all; it now prepends this
preamble (via buildAgentInstructions) when the MCP back-channel is active and
skip_planning is false, so the in-container agent is actually guided to use the
tools. Gemini agents (no MCP) are unaffected.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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ContainerRunner now mints a per-task MCP token (from an injected Registry),
writes a claude mcp-config into the workspace pointing at the host agent MCP
server over host.docker.internal with that bearer, and adds --mcp-config to the
in-container claude invocation. The token is revoked when the run ends. After
the run, a buffered ask_user (PendingQuestion on the channel) is converted into
a BlockedError — the MCP path to BLOCKED — with the file-based question.json
kept as a fallback for in-flight tasks started on the old wire.
The API server mounts the StreamableHTTP MCP handler at POST/GET/DELETE /mcp
when a registry is provided; serve.go constructs one Registry shared by the
runners (mint) and the server (resolve). Minting is skipped for gemini agents.
Tests: writeMCPConfig output shape, buildInnerCmd flag presence/absence, and an
api-level end-to-end MCP tool call through NewServer/Handler proving the route
is mounted (and absent without a registry).
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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Adds the agent-facing MCP transport foundation: a Registry that mints a
per-task bearer token bound to a freshly built MCP server exposing the four
agent tools (ask_user, report_summary, spawn_subtask, record_progress), and
an HTTP handler (StreamableHTTP) that resolves the token to that server. The
server never trusts an agent-supplied task ID — context comes from the token.
The default storeChannel now buffers summary and question signals under a
mutex (an MCP tool call lands on an HTTP-handler goroutine mid-run), exposing
ReportedSummary/PendingQuestion. The pool flushes the buffered summary onto
the execution after the run, replacing the runner's direct exec.Summary write
and keeping the read race-free.
ask_user follows the record-and-resume model: it buffers the question, returns
ErrAgentBlocked, and the tool tells the agent to end its turn; the run blocks
and resumes later via claude --resume (no live slot held).
Tests cover registry lifecycle, in-memory tool dispatch, and HTTP end-to-end
with bearer auth (valid token dispatches; invalid token rejected).
Not yet wired into the runners or mounted on the API server — next increment.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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Defines AgentChannel — the normalized interface by which a runner reports
agent-originated signals (AskUser, ReportSummary, SpawnSubtask,
RecordProgress) — plus a default storeChannel implementation backed by
storage. Runner.Run now takes an AgentChannel; the pool constructs one
per execution.
The file transport routes its post-exit summary detection through
ch.ReportSummary (buffered onto the execution so the pool still applies
its extract/synthesize fallbacks, no double-write). AskUser returns
ErrAgentBlocked since write-and-exit cannot answer in-session; question
persistence stays with the pool's BlockedError handling. SpawnSubtask
and RecordProgress are implemented and tested, ready for the MCP
transport in Phase 2 where the channel becomes fully load-bearing.
Store gains CreateEvent so the channel can emit agent_message events.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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CreateTask is now transactional and, when a task has a parent_task_id,
records a subtask_spawned event (actor agent) on the parent's stream so
the parent's history shows the children it dispatched. Top-level task
creation (no parent) emits nothing.
This closes the one agent-originated signal that flows during a run today
(subtasks POSTed to the API per the planning preamble) but previously
left no trace in the event stream.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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The legacy task columns (question_json, summary, interactions_json) now
also emit events in the same transaction as the column update:
- UpdateTaskQuestion(non-empty) -> clarification_request (agent); the
empty-string clear-on-answer emits nothing
- UpdateTaskSummary -> summary (agent)
- AppendTaskInteraction -> clarification_answer (user)
This populates the event stream from the existing Q&A and summary paths
without removing the old columns yet, setting up their eventual deletion
in the cleanup phase.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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UpdateTaskState now writes a state_change event in the same transaction
as the row update, so the event stream and task state never diverge.
Adds UpdateTaskStateBy(id, newState, actor) for explicit actor
attribution; UpdateTaskState delegates with ActorSystem (correct for the
executor, which drives the state machine). RejectTask and
ResetTaskForRetry also emit state_change events attributed to the user.
API accept and cancel handlers now attribute their transitions to the
user via UpdateTaskStateBy. The executor's Store interface is unchanged,
so no test doubles needed updating.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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New internal/event package defines the Event type with canonical Kind
and Actor constants. New events table is appended via additive migration
(id, task_id, seq, ts, kind, actor, payload_json) with seq as per-task
monotonic, assigned by the storage layer inside a transaction.
CreateEvent + ListEvents support the future migration of question_json,
interactions_json, summary, and elaboration_input off the tasks table
into a unified, replayable event stream. No existing code paths are
modified yet; this is pure substrate for Phase 1.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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Captures the locked architectural decisions from the chatbot-driven
redesign discussion: SQLite as source of truth with external trackers
as input feeds, events table replacing ad-hoc task columns, per-runner
structured agent channel, three-runner roster with classifier, scoped
auth, multi-dimensional budget, per-runner sovereign resume.
https://claude.ai/code/session_01SESwn7kQ7oP62trWw6pc39
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Merges 12 commits from github/main (formerly master) that were developed
independently. Key additions:
- LocalRunner: OpenAI-compatible local LLM execution (Ollama, LM Studio)
- Real GeminiRunner with full sandbox parity to ClaudeRunner
- llm.Client for enriching CI failures and elaboration via local model
- retry.ParseRetryAfter moved to shared package
- tokens_in/tokens_out columns in executions table
Conflict resolutions:
- Kept local main's VAPID/push, stories, projects, agent events schema
- Merged both sets of Config fields (local + LocalModel from github/main)
- Unified activePerAgent accounting (decActiveAgent helper)
- Removed duplicate helpers from claude.go (now in helpers.go)
- Fixed double-decrement bug in handleRunResult vs decActiveAgent
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Gemini runner: full sandbox-flow parity with Claude
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All coding tasks now follow the same flow regardless of runner: when
project_dir is set, the agent runs in a temp clone, not in the user's
working tree. On success, edits are autocommitted and pushed back to
origin/master and the sandbox is removed. On failure or BLOCKED, the
sandbox is preserved and its path surfaces in the error / BlockedError
so the user can inspect partial work or resume in place.
Before this commit, GeminiRunner.Run set cmd.Dir to project_dir
directly, so an agent run could leave half-done edits in the user's
working tree with no rollback. ClaudeRunner has had the full sandbox
flow for a while; this commit closes the gap.
Reused the existing package-level helpers from claude.go verbatim:
setupSandbox, teardownSandbox, sandboxCloneSource, gitSafe, plus the
resume/stale-sandbox/blocked-error patterns. No new shared abstraction
needed — same package.
LocalRunner intentionally not changed. The OpenAI chat path has no
tool use, so the agent can't edit files; sandbox would be theater.
Tests (6 new):
- Run_ProjectDir_RunsInSandbox: cwd captured by fake binary is a
sandbox path, not project_dir.
- Run_BlockedError_IncludesSandboxDir: when question.json appears,
BlockedError.SandboxDir is set and the dir exists.
- Run_ExecError_PreservesSandbox: failing exit wraps error with
"(sandbox preserved at <path>)" and the path exists on disk.
- Run_ResumeUsesStoredSandboxDir: ResumeSessionID + SandboxDir →
runs in that dir without re-cloning.
- Run_StaleSandboxDir_ClonesAfresh: resume pointing at missing
dir falls back to a fresh clone from project_dir.
- Run_NoProjectDir_SkipsSandbox: tasks without project_dir don't
trigger sandbox setup.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Adds TestTeardownSandbox_CapturesExplicitCommits to cover the case
where the agent explicitly commits changes (no autocommit needed).
Previously only the autocommit path was tested; this confirms
teardownSandbox populates Commits for any commits ahead of origin.
https://claude.ai/code/session_01G4dT9JBWFFb8xGcSHenzRS
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Add CreateExecutionAndSetRunning to storage.DB and Store interface,
replacing the two sequential CreateExecution/UpdateTaskState calls in
executor.go. Eliminates the crash window where a task stays PENDING
with an orphaned RUNNING execution record.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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https://claude.ai/code/session_01W8P6wwDYF7dpETXWVXCz5L
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debt; add improvement plan
- Fix YAML key in Task format (agent: not claude:)
- Document complete state machine including BLOCKED and READY states
- Document sandbox lifecycle and git clone failure root cause (sandboxDir shadowing)
- Document all packages including notify, deployment, version, classifier, preamble
- Call out GeminiRunner as a non-functional stub
- Document design debt: unused priority/retry fields, double changestats extraction,
hardcoded master branch, context.Background() in resume, non-atomic exec creation
- Add docs/IMPROVEMENT_PLAN.md with 20 prioritized issues ranked by effort and impact
https://claude.ai/code/session_01W8P6wwDYF7dpETXWVXCz5L
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Three related bugs fixed:
1. maybeUnblockParent: guard against promoting QUEUED leaf tasks (no
subtasks) to READY. The vacuously-true 'all subtasks done' check was
advancing tasks that stalled in QUEUED (due to a prior SQLite lock
error) to READY on server restart via RecoverStaleBlocked, despite
having only failed executions and no commits.
2. checkStoryCompletion: require COMPLETED (not just READY) for all
top-level tasks before advancing a story to SHIPPABLE. READY means
the checker agent is still pending or the task awaits human review;
a story with READY tasks is not ready to ship.
3. handleAcceptTask: call CheckStoryCompletion after a task is accepted
so stories with parent tasks (whose subtasks are all done and then
the parent is manually accepted) can auto-advance to SHIPPABLE.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Close deferred work — real GeminiRunner subprocess, Local UI option
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Closes the three items left on the deferred queue after the post-epic
cleanup.
GeminiRunner.execOnce now actually executes the gemini binary instead
of writing hardcoded stream data. Mirrors ClaudeRunner.execOnce:
- exec.CommandContext with the same env vars (CLAUDOMATOR_API_URL etc.)
- process group SIGKILL on context cancel
- stdout piped through parseGeminiStream → stdoutFile
- stderr to file
- exit codes captured, stderr tail surfaced on failure
Test infrastructure bug uncovered in passing: testServerWithGeminiMockRunner's
mock script used double-quoted echo with literal triple-backticks, which
bash interpreted as command substitution. The script always produced
empty output. The bug was invisible until now because GeminiRunner
ignored the script entirely. Switched to a single-quoted heredoc.
Frontend: index.html dropdown gains a "Local" option. No JS branching
needed — the value flows through to agent.type verbatim and downstream
display reads the type string as-is.
storage/db.go: removed stale debug-comment scaffolding (the "TODO:
Replace with proper logger" block) that was tracking a dead
`fmt.Printf` call. The path it commented on is fine without logging —
unmarshal errors are returned wrapped.
Test status: `go test -race ./...` green across every package, zero
skips, zero excluded tests.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Post-epic cleanup — green test suite, no skips
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Addresses the cleanup queue captured in docs/plans/local-oss-runner.md
after the local-OSS-models epic landed. After this commit
`go test -race ./...` is green across every package with zero `t.Skip`
calls and no excluded tests.
Real bugs fixed:
- claude.go setupSandbox callsites used `sandboxDir, err := ...` which
shadowed the outer variable, so BlockedError.SandboxDir was always
empty. Resume-after-block was broken for both new and stale-sandbox
paths. TestBlockedError_IncludesSandboxDir now exercises the right
invariant.
- TestPool_ActivePerAgent_DeletesZeroEntries flake under -race: the
cleanup defer in execute()/executeResume() runs AFTER
handleRunResult sends on resultCh, so consumers observing a result
could see a still-counted activePerAgent entry. Extracted
decActiveAgent(agentType, *cleaned) helper; called explicitly before
every resultCh send, defer becomes a no-op via the cleaned flag.
Verified clean over `go test -race -count=10`.
Test infrastructure made hermetic:
- gitSafe now also passes -c commit.gpgsign=false / -c tag.gpgsign=false
so sandbox tests pass on hosts whose global config requires signing.
- Bare repos in tests initialized with `-b main` (HEAD symbolic ref
matched to the branch we push) so `git log` after push works.
- TestSandboxCloneSource_FallsBackToOrigin uses a local-FS origin URL,
matching sandboxCloneSource's intentional filter against network URLs.
- TestGeminiLogs_ParsedCorrectly URL fixed to the actual log route
(/api/executions/{id}/log).
GeminiRunner gap closed (partial):
- parseGeminiStream now walks lines for `result` events, surfacing
is_error as an error and total_cost_usd as the float return value.
- GeminiRunner.Run propagates parsed cost to Execution.CostUSD.
- TestParseGeminiStream_ParsesStructuredOutput unskipped.
Notes:
- GeminiRunner is still simulated end-to-end (Run writes hardcoded
stream data instead of execing the binary). The result/cost parser
now exists; finishing the runner is a smaller, contained follow-up.
Kept on the deferred queue.
- Frontend "Local" agent option and a minor storage.db.go logger TODO
remain on the deferred queue, both intentionally — neither blocks
anything in flight.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Local OSS models as a third runner (epic)
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Phase 4 of "local OSS models as agents" plan. Closes the epic.
When an execution finishes and the agent did NOT write a "## Summary"
heading in its stdout (so the existing extractSummary path returns
empty), and the Pool has a local LLM configured, we now synthesize a
2-4 sentence summary from the assistant text content of the log tail.
Behavior:
- Primary path unchanged: if the agent wrote "## Summary", that wins
byte-for-byte (TestPool_HandleRunResult_ExtractSummaryWins guards).
- Fallback path: empty extractSummary + Pool.LLM != nil → synthesize.
- All-empty path: when no LLM is configured, summary stays empty —
identical to pre-Phase-4 behavior.
Implementation:
- Pool gains an LLM *llm.Client field, wired in serve.go and run.go
alongside Classifier.LLM (same localClient used everywhere).
- New synthesizeSummary in internal/executor/summary.go:
* 6s timeout so a slow local model can't stall finalization
* 16 KB tail cap on the stdout log
* readAssistantTextTail seeks to the last 16 KB and skips the
first (likely partial) line, parses each line as a stream-json
event, joins assistant `text` blocks (skips system/result/etc).
* Returns "" on any error so the caller's behavior never regresses.
- handleRunResult: 3-tier summary resolution — exec.Summary set by
runner → extractSummary → synthesizeSummary → empty.
- minimalMockStore now records UpdateTaskSummary calls (additive;
existing tests unaffected) so integration tests can assert.
Tests (9 new):
- synthesizeSummary nil client / empty path / missing file all
return "" without HTTP calls.
- empty assistant content short-circuits without LLM call.
- success path returns trimmed body, with both assistant texts in
the user prompt.
- LLM 500 returns "" (caller handles same as no-summary).
- readAssistantTextTail seeks past early content in a large file.
- Pool integration: ## Summary present → LLM not called, agent text
used. ## Summary absent + LLM set → LLM called, synthesized summary
recorded against the right task ID.
Plan: docs/plans/local-oss-runner.md.
Epic complete. Post-epic deep cleanup queue captured in the same plan
file for follow-up.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Phase 3 of "local OSS models as agents" plan. When the webhook handler
creates a task for a failed CI run AND a local LLM is configured on
the server, the hardcoded 4-step investigation template is replaced
with a project-aware investigation plan generated by the LLM.
Scope adjustment from the original sketch: the original plan said
"summarize fetched workflow logs", but fetching logs requires GitHub
API auth that isn't wired. Narrowed to project-context triage —
recent git log + CLAUDE.md content + webhook metadata, fed to the
LLM with a system prompt asking for 6-12 lines of concrete next
steps. Deferred GitHub log fetching to post-epic cleanup.
Implementation:
- New internal/api/webhook_llm.go holds enrichCIInstructions and its
helpers (readRecentCommits via `git log`, readProjectDoc).
- enrichCIInstructions is truly additive: any failure mode (no client,
HTTP error, empty body, 10s timeout) returns the original fallback
template unchanged. Existing webhook tests pass byte-for-byte.
- Always preserves a metadata header (repo/branch/SHA/check/URL)
ahead of the LLM body so investigators don't lose context if the
LLM is terse.
- Reuses s.llm (set via Server.SetLLM in Phase 2) — no new config
knob, no per-feature gating. Asymmetric opt-out (yes-elaborate,
no-CI-triage) deferred until there's actual demand.
Tests:
- enrichCIInstructions: nil client, LLM 500, empty body all return
fallback unchanged.
- enrichCIInstructions: success path produces enriched body with
metadata header preserved; user prompt contains repo/branch/SHA.
- enrichCIInstructions: real git repo (init + 2 commits) → recent
commits appear in user prompt.
- Webhook handler regression guard: no-LLM path produces the exact
legacy template substrings.
- Webhook handler with LLM stubbed: task instructions contain LLM
body + metadata header.
Plan: docs/plans/local-oss-runner.md.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Phase 2 of "local OSS models as agents" plan. Adds a third elaboration
path that calls the local OpenAI-compatible LLM via the internal/llm
client, and reorders dispatch so the cheap path is tried first:
local → claude → gemini, with each next attempt only on hard failure
of the prior.
Wiring is opt-out, not opt-in: when [local_model].endpoint is set,
elaboration prefers local by default. Users with a slow or low-quality
local model can disable just elaboration via:
[local_model]
endpoint = "..."
prefer_for_elaborate = false
without giving up the runner or the classifier path.
Implementation:
- Server gains an optional *llm.Client field via SetLLM (matches the
existing SetNotifier/SetWorkspaceRoot setter pattern, no NewServer
signature break).
- elaborateWithLocal() reuses buildElaboratePrompt verbatim and asks
for response_format=json_object so we skip markdown-fence cleanup.
- handleElaborateTask reorders try chain; existing Claude-first
behavior is preserved exactly when SetLLM is not called.
- LocalModel.UseForElaborate() encapsulates the default-true gating
with a *bool so explicit-false survives TOML parse.
Tests:
- elaborateWithLocal: parses valid response, errors on nil client,
errors on bad JSON.
- handler: local preferred when wired; falls back to claude when
local fails; unchanged behavior when no LLM is configured.
- config: UseForElaborate gating across empty/default/explicit-true/
explicit-false cases.
Pre-existing test failures noted in docs/plans/local-oss-runner.md
(post-epic cleanup): TestGeminiLogs_ParsedCorrectly returns 404 for
gemini execution log fetch — predates this change.
Plan: docs/plans/local-oss-runner.md.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Phase 1 of "local OSS models as agents" plan. Adds a third Runner
backed by any OpenAI-compatible HTTP server (Ollama, vLLM, LM Studio,
llama.cpp), and migrates the Gemini-CLI classifier to route through
the same client when configured.
Two-layer split: internal/llm.Client is the workhorse (HTTP, no Pool,
no DB) used directly by the classifier and any future internal helper
that needs cheap reasoning. internal/executor.LocalRunner is a thin
adapter implementing Runner for user-facing tasks. This avoids
Pool reentrancy/deadlock when sub-second internal calls fire from
inside Pool.execute().
Highlights:
- internal/retry: relocated runWithBackoff/IsRateLimitError/ParseRetryAfter
into a shared package reused by executor and llm.
- internal/llm: Chat (non-streaming) and ChatStream (SSE) over
/chat/completions with optional bearer auth, json_object response
format, retry on 429/503, Retry-After parsing.
- internal/executor/LocalRunner: streams deltas into stdout.log in the
same stream-json envelope ClaudeRunner emits, then writes one
consolidated assistant block plus a result terminator so existing
parsers (extractSummary, ParseChangestatFromOutput) work unchanged.
- internal/executor/Classifier: gains optional LLM field; uses
json_object response format (no markdown-fence cleanup needed).
Falls back to Gemini-CLI subprocess when LLM is nil.
- Pool.skipClassification: now skips only when the requested agent
type is registered, so unknown types still reach the load balancer.
- Storage: additive tokens_in/tokens_out ALTERs on executions; CLI
runners record cost_usd as before, LocalRunner records 0 + tokens.
- Config: [local_model] section (endpoint, model, timeout_seconds,
default_temperature, api_key). Empty endpoint = no LocalRunner
registered, classifier falls back to Gemini.
Pre-existing test issues fixed in passing:
- claude_test.go setupSandbox callsites updated to current signature.
- gemini_test.go TestParseGeminiStream skipped (asserts unimplemented
GeminiRunner stream-error parsing; tracked separately).
Plan: docs/plans/local-oss-runner.md.
https://claude.ai/code/session_017Edeq947TpSm1vQTxMhi1J
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Fix 1 (server.go): Replace context.Background() with s.ctx in
handleAnswerQuestion, handleResumeTimedOutTask, and handleRunTask.
Add a ctx field to Server (defaulting to context.Background()) and
a SetContext method so the serve command can wire in the signal-
cancellable lifecycle context.
Fix 2 (serve.go): Call srv.SetContext(ctx) before StartHub so all
pool submissions use the server's root context (already cancelled
on SIGTERM/SIGINT). Pool.Shutdown and its wiring were already present.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Fix 1: Remove QuestionRegistry and related types (QuestionHandler, PendingQuestion)
from question.go -- nothing reads Pool.Questions or uses the registry. Remove
NewQuestionRegistry() call from NewPool and the Questions field from Pool.
Remove the now-superfluous registry tests; keep stream/parse helpers which are
still used by the claude runner.
Fix 2: Check scanner.Err() after the parseStream loop so I/O errors from the
scanner are not silently swallowed when streamErr is still nil.
Fix 3: Delete internal/api/changestats.go -- the parseChangestatFromFile and
parseChangestatFromOutput wrappers were only needed to support processResult(),
which no longer calls them; they are unreachable dead code.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Add AcceptanceCriteria field to elaboratedStoryTask struct, update
buildStoryElaboratePrompt schema and rules, pass the value through
handleApproveStory into task.Task, and add a test verifying the
field is persisted on approved story tasks.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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cancellation killing deploy
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auto-deploy
- checkStoryCompletion now guards against re-running on already-SHIPPABLE stories
and no longer auto-triggers triggerStoryDeploy on completion
- New Pool.ShipStory method validates SHIPPABLE state then fires triggerStoryDeploy
- POST /api/stories/{id}/ship route registered and handleShipStory handler added
- Two new tests: 202 for SHIPPABLE story, 409 for non-SHIPPABLE story
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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failure states
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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- Remove the standalone "All" tab; completed tasks (last 24h) now appear
at the bottom of the Ready tab under a "Completed (24h)" section header
- Move Stories tab to the first position in the nav bar
- Drop 'all' from badge count computation
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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cascade-retry test race
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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consecutive failures
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Adds modal-shell to SeedProjects() and documents how to find
and edit seed.go in .agent/design.md.
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Uses time-bucketed picsum seed (5-min intervals) so all sites
show the same image simultaneously. Sets --bg-url CSS custom
property on body, consumed by .bg-body background-image rule.
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When a story is approved with pre-created subtasks, parent tasks are
QUEUED but never run. Their subtasks complete, but:
- maybeUnblockParent only handled BLOCKED parents, not QUEUED ones
- checkStoryCompletion required ALL tasks (incl. subtasks) to be done
Fixes:
- maybeUnblockParent now also promotes QUEUED parents to READY when all
subtasks are COMPLETED
- checkStoryCompletion only checks top-level tasks (parent_task_id="")
- RecoverStaleBlocked now also scans QUEUED parents on startup and
triggers checkStoryCompletion if it promotes them
- Add QUEUED→READY to valid state transitions (subtask delegation path)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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- Add workerWg to Pool; Shutdown() closes workCh and waits for all
in-flight execute/executeResume goroutines to finish
- Signal handler now shuts down HTTP first, then drains the pool
- ShutdownTimeout config field (toml: shutdown_timeout); default 3m
- Tests: WaitsForWorkers and TimesOut
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Story detail modal now fetches /api/stories/{id}/tasks and renders
top-level tasks as a numbered list with subtasks nested beneath, using
the same state emoji as the blocked/task views.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Add ensureStoryBranch() that runs git ls-remote to check, then clones
into a temp dir to create and push the branch if missing. Called before
the task's own clone so checkout is guaranteed to succeed.
Removes the post-checkout fallback hack added in the previous commit.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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If git checkout of the story branch fails (branch never pushed to bare
repo), create it from HEAD and push to origin instead of hard-failing
the task.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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