Files
gstack/test/fixtures/eng-seeded-packet-ae.json
Garry TanandOpenAI Codex 9f81911136 v1.86.0.0 feat: route outside reviews by harness (#2850)
* feat: add a restricted and supervised Claude Code runner

Preserve configured authentication and models while enforcing tool access, strict completion JSON, bounded output and process cleanup. Cover argv, failure handling, session metadata and Windows process containment.

* feat: route outside reviews by harness and migrate wrapper installs

Use Claude Code from Codex and Codex from other supported hosts, with shared invocation rendering, positive gate validation and per-phase provenance. Rename /claude to /claude-code, repair managed shared and copied installations safely, and generate native Kiro skills. Add installed-workflow, failure-injection and live cross-harness regression coverage.

* test: recognize CEO mode labels without terminal spacing

The paid workflow rendered SCOPEEXPANSION at option 4, but its driver required a literal space. Match the leading mode title without cursor-spacing artifacts and ignore adjacent preview text. Preserve missing-target failures and downstream posture assertions.

* test: isolate plan-count fixtures before starting review workflows

Seed the complete test plan in a private git repository before launching Claude, so a bare slash command cannot review the live workspace while a delayed fixture message remains queued. Preserve count thresholds, parsers and budgets. Add initial-context and installed-discovery tests, and retain startup/terminal diagnostics on failed evaluations.

* test: stabilize review fixtures and Claude eval startup

Preserve source boundaries in workflow judge inputs, isolate CEO mode plans, and wait for interactive trust input readiness. Keep startup failure evidence and retain existing models, budgets, and assertions.

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* test: classify collapsed review modes and isolate seeded findings

Keep review questions out of the setup count when terminal cursor positioning removes spaces. State existing webhook safeguards so the five-finding control measures its seeded defects without accidental extra security and concurrency gaps. Preserve question bands and the paired control.

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* test: isolate browser daemon state across free shards

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* test: stabilize native review counting and interactive navigation

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* chore: prepare v1.82.0.0 release

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* fix: eliminate browser and process-cleanup test flakes

Pin every CI surface to Bun 1.4.0 to avoid extra-stdio finalizers closing
reused live sockets. Add an isolated GC/listener regression that fails on
Bun 1.3.13, and prevent coordinated rollback to an affected CI runtime.

Check renderer cleanup against the render's own staging directory so
concurrent renders cannot invalidate the assertion. Make the no-pgrep
process-tree walk tolerate disappearing /proc entries, and synchronize
its test fixture through child readiness and pipe EOF instead of sleeps.

Validation: 9,157 passed, 31 skipped, zero failures across 556 files with
retries disabled. Build, all-host generation freshness, and skill checks
passed. All three races have failing-before/passing-after regressions.

* fix: count completed native review questions in evals

* fix: drive review navigation from confirmed native choices

* fix: require complete section-loading eval reports

* test: isolate telemetry HTTP transport from local assertions

* fix: keep review input on the active native question

* test: let tunnel revocation daemon choose an available port

* test: allocate available ports for pairing and watchdog fixtures

* fix: stabilize planning eval navigation and phase reporting

* test: isolate installed runtime paths in planning evals

* test: stabilize review evidence and concurrent refresh fixtures

* fix: resolve design findings before editing the plan

* fix: honor and persist disabled outside plan reviews

* fix: preserve planning decisions and terminal evidence

Load installed host reviews at autoplan phase entry and wait for completed
reviewers and saved artifacts. Reuse approved remedies while preserving
individual finding decisions.

Drive interactive evals from the current terminal viewport, bind native
questions across scrolling, and require complete native report evidence.
Cover captured stale menus, permission lifecycles, setup classification,
and disabled-review tool availability with deterministic regressions.

Advance release metadata and the upgrade migration to the unclaimed
1.83.0.0 slot.

* fix: drive native review questions and preserve current plans

Use the native single-choice keyboard protocol and current terminal viewport,
with per-question navigation inside packets and completed-call coverage.
Keep permissions, multi-select menus, and Submit controls distinct.

Send Autoplan reviewers the amended implementation plan, keep its review record
separate, and supply retained application contracts in the chain fixture.
Clarify individual DevEx decisions and complete CEO fix options; use one active
plan destination for the section-loading report.

* fix: preserve complete plan-review decisions

* fix: recognize native plan dialogs and reviewer controls

* fix: preserve review decisions and phase completion

* fix: recognize completed reviews without losing findings

* fix: preserve review continuity and native eval completion

* test: fix native review completion and eval retry isolation

* test: handle native review menus and complete eval fixtures

* test: fix native review setup, completion, and isolation failures

* test: limit native skill discovery to runtime assets

* fix: bind Autoplan reviews to full ordered phase inputs

* test: fix planning eval routing, counting, and timeout handling

* chore: advance queued release to v1.84.0.0

* fix: preserve complete review inputs and planning decisions

* fix: reconcile review approvals and preserve phase obligations

* fix: preserve review obligations and unblock eval permissions

Carry recorded Autoplan requirements into blind phase inputs, require Eng
review approvals before exit, and exercise combined asynchronous flows in
CEO reviews. Correct native finding and handoff classification and unblock
repeated report edits using scoped request identities.

* fix: retain plan requirements and complete native review dialogs

* fix: complete native review prompts and retain plan references

* fix: preserve review inputs and classify native eval evidence

* fix: check competing completion orders in CEO reviews

* fix: recognize review decisions and require phase methodology

Require the current phase methodology before Autoplan snapshots. Correct
substantive decision, closed handoff, and cache-finding classification, and
honor the recommended implementation approach in native review dialogs.

Add captured-transcript regressions without changing review thresholds,
provider models, retries, or deadlines.

* test: bind native review decisions and close completed handoffs

* fix: complete review dialogs and verify methodology delivery

* fix: preserve review evidence and unblock native eval prompts

* fix: handle native review question completions

* fix: recognize native review narration and controls

* fix: count native review decisions and isolate eval fixtures

* test: verify seeded review coverage and current artifact permissions

* test: isolate model and brain-aware skill renders

* fix: repair native workflow evaluation and clarify review steps

* fix: stabilize workflow eval evidence and review guidance

* test: repair native workflow observation and fixture isolation

* fix: recognize completed workflow evidence and owned skill reads

* test: repair seeded workflow delivery and completion evidence

* test: recognize current review evidence across native forms

* test: handle native review variants and permission redraws

* fix: honor review preferences and recognize native eval evidence

* test: recognize completed review decisions and queued permissions

* test: match current review contracts and partial-line edits

* test: recognize completed workflow evidence and bounded human waits

* fix: preserve review entry gates and native eval interactions

* fix: recognize native workflow evidence and preserve review gates

* test: recognize current review evidence and preconfigure workflow fixtures

* test: recognize completed review findings and scoped artifact permissions

* fix: stabilize native workflow review and permission evidence

* fix: recognize current review evidence and scoped edit confirmations

Clarify Design and engineering review entry instructions and Design scoring.
Recognize required legacy coverage and public Autoplan completion recaps.
Bind the pending Edit confirmation to its exact file, ordered digest, and
one-request approval when a preceding command display remains visible.
Keep reviews within their existing size limits and preserve scope gates
when extracting workflow fixtures from either supported preamble header.

Keep failure outcomes, review thresholds, provider choices, and eval budgets.

* fix: recover review workflow progress and eval evidence

* fix: recognize valid review evidence and scope selection

* test: fix review evidence parsing and repeated artifact prompts

* test: recognize valid review decisions and pending native cards

* fix(plan-eng-review): keep final navigation consistent with approved tasks

* test: recognize valid review evidence and bind legacy diff requests

* fix: stabilize review eval evidence and harness repair guidance

* docs: update project documentation for v1.85.0.0

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* test: fix Windows CI fixtures and credential scan

Rebase captured JSON values and filesystem evidence using the appropriate
path convention. Compile native fake CLIs on Windows and synchronize pipe
holder readiness, with cleanup retained when assertions fail.

Assemble synthetic credential fixtures at runtime so the added-line scan
keeps enforcing the same gate without flagging its own rejection controls.

Discover generated skills directly for the empty-find regression check,
avoiding a recursive scan through saved evaluation artifacts and dependencies.

* fix: preserve source renders on Windows

Compare canonical generator paths using native separators so an output
sidecar pointing at the source cannot overwrite its skill or metadata.
Keep the regression fixture isolated from the real checkout and expose
freshness diagnostics before asserting subprocess status.

Detach Windows drain-test pipe holders from the fake provider's automatic
child cleanup while preserving the enclosing runner job and its assertions.

* fix: clarify outside review fallback and CEO decisions

Render one applicable own-harness fallback path and retain native review,
disabled policy, and missing-coverage semantics. Align report field names
and mode labels, and make the existing per-cut scope approval explicit.

Regenerate skill outputs and keep the workflow judge's model, thresholds,
and retry policy unchanged.

* chore: move release to free version slot (v1.86.0.0)

PR #2852 now claims v1.85.0.0. Align the release metadata and
rename migration so upgrades from that version still receive it.

Co-Authored-By: OpenAI Codex <noreply@openai.com>

* fix: include engineering review prerequisites and restore branch context

* fix: recognize coverage diagrams and clarify design review instructions

* fix: preserve file identities and join Windows test processes

---------

Co-authored-by: OpenAI Codex <noreply@openai.com>
2026-09-14 14:32:45 -07:00

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{
"provenance": {
"kind": "exact completed public native packet and required-test paragraph",
"sourceHead": "e8470a7e447f7850f75214383bb1a41d3f1debd8",
"session": "97b9510d-c630-4cbb-9f8c-d1bb31a9e4ec",
"reportSha256": "959c68c2ea28986ccb1f7ce8526ba622ad6f733144dc062cb3bc795a20092ce1",
"historicalOutcome": "plan_ready609366ms; natural test failure for missing complexity and mandatory regression"
},
"packet": {
"sessionId": "97b9510d-c630-4cbb-9f8c-d1bb31a9e4ec",
"toolUseId": "toolu_01Fdi1cEcgf6vKR8da6kmRLV",
"questions": [
{
"question": "D3 \u2014 Issue 0: 12 files and 5 new types for an auth refactor \u2014 reduce scope or proceed as-is?\nProject/branch/task: gstack-plan-count-I2kvlg on main, PLAN.md Multi-tenant Auth Refactor (PLAN.md:34-36 \"touches 12 files and introduces 4 new classes\", plus AuthBroker at PLAN.md:19).\nELI10: The plan adds five new moving parts to do auth: AuthBroker, SessionMint, TokenStore, AuthCache, RequestPolicy. Two of them look like wrappers around things that already exist. AuthCache is described (PLAN.md:11-13) as a facade over the existing adapter \"with one backing cache\" that keeps every rule unchanged, so it is a pass-through. TokenStore stores tokens next to a cache that already stores tokens keyed by tenant. RequestPolicy has no stated behavior. Every extra class is a place for a 3am bug to hide and a file the next engineer has to read.\nStakes if we pick wrong: Too many parts and the auth path becomes hard to reason about and test; too few and we may cram unrelated responsibilities into one class.\nRecommendation: 0A because AuthBroker and SessionMint can take the existing adapter by constructor injection, TokenStore's job is already the adapter's, and RequestPolicy can start as a plain typed config object. That matches the 'engineered enough' and smallest-clean-diff preferences. Estimated ~7-8 files, 2 new classes.\nNote: options differ in kind, not coverage \u2014 no completeness score.\n0A) Reduce: keep AuthBroker + SessionMint, inject the existing adapter, drop AuthCache facade and TokenStore, make RequestPolicy a typed object (recommended) (human: ~1 day saved / CC: ~10 min saved)\n \u2705 Two new classes instead of five; the auth hot path stays readable in one sitting\n \u2705 Removes the pass-through facade that would otherwise need its own test suite\n \u274c If TokenStore was meant to hold non-cache state (refresh tokens, mint receipts), that need must be re-stated\n0B) Middle: drop only the AuthCache facade, keep TokenStore and RequestPolicy as classes (human: ~2 days / CC: ~20 min)\n \u2705 Keeps a dedicated place for token persistence separate from the validity cache\n \u2705 Still removes the pure pass-through wrapper\n \u274c Three new classes for one feature is still a lot of surface for 12 files\n0C) Proceed as-is: 5 new types, 12 files (human: ~3 days / CC: ~30 min)\n \u2705 Each concern gets its own named home, which some teams prefer for auth\n \u2705 No rework of the plan before implementation starts\n \u274c Facade with no new behavior and overlapping stores add coupling and test burden without user-visible gain\nNet: fewer classes with injected dependencies versus more named boundaries that mostly wrap existing code.",
"header": "Scope",
"multiSelect": false,
"options": [
{
"label": "0A Reduce to 2 new classes (recommended)",
"description": "Inject existing adapter into AuthBroker/SessionMint; drop AuthCache facade and TokenStore; RequestPolicy becomes a typed object."
},
{
"label": "0B Drop only AuthCache facade",
"description": "Keep TokenStore and RequestPolicy as classes; remove the pass-through wrapper."
},
{
"label": "0C Proceed as-is",
"description": "Keep all 5 new types and 12 files; review continues against the plan unchanged."
}
]
},
{
"question": "D4 \u2014 Enable cross-project learnings search on this machine?\nProject/branch/task: gstack setup for gstack-plan-count-I2kvlg; one-time config, not a plan finding.\nELI10: gstack can search learnings from your other projects on this machine to find patterns that might apply here. This stays local (no data leaves your machine). Recommended for solo developers. Skip if you work on multiple client codebases where cross-contamination would be a concern.\nStakes if we pick wrong: Enabled on a multi-client machine, a learning from one client's codebase could surface in another's review; disabled, this project only learns from itself.\nRecommendation: A because it is local-only, reversible with one config command, and compounding learnings is the point of the tool.\nNote: options differ in kind, not coverage \u2014 no completeness score.\nA) Enable cross-project learnings (recommended)\n \u2705 Reviews get smarter from patterns seen in your other local projects\n \u2705 Local-only lookup, nothing leaves the machine, one command to reverse\n \u274c On a shared or multi-client machine, unrelated project patterns may surface\nB) Keep learnings project-scoped only\n \u2705 Zero chance of cross-client pattern leakage in review output\n \u2705 Simpler mental model: this repo only learns from itself\n \u274c Slower compounding; every project restarts its learning from zero\nNet: faster compounding versus strict per-project isolation.",
"header": "Learnings",
"multiSelect": false,
"options": [
{
"label": "Enable cross-project (recommended)",
"description": "Set cross_project_learnings true; local-only search across your projects."
},
{
"label": "Project-scoped only",
"description": "Set cross_project_learnings false; this repo learns only from itself."
}
]
}
],
"answered": true,
"failed": false,
"answers": {
"D3 \u2014 Issue 0: 12 files and 5 new types for an auth refactor \u2014 reduce scope or proceed as-is?\nProject/branch/task: gstack-plan-count-I2kvlg on main, PLAN.md Multi-tenant Auth Refactor (PLAN.md:34-36 \"touches 12 files and introduces 4 new classes\", plus AuthBroker at PLAN.md:19).\nELI10: The plan adds five new moving parts to do auth: AuthBroker, SessionMint, TokenStore, AuthCache, RequestPolicy. Two of them look like wrappers around things that already exist. AuthCache is described (PLAN.md:11-13) as a facade over the existing adapter \"with one backing cache\" that keeps every rule unchanged, so it is a pass-through. TokenStore stores tokens next to a cache that already stores tokens keyed by tenant. RequestPolicy has no stated behavior. Every extra class is a place for a 3am bug to hide and a file the next engineer has to read.\nStakes if we pick wrong: Too many parts and the auth path becomes hard to reason about and test; too few and we may cram unrelated responsibilities into one class.\nRecommendation: 0A because AuthBroker and SessionMint can take the existing adapter by constructor injection, TokenStore's job is already the adapter's, and RequestPolicy can start as a plain typed config object. That matches the 'engineered enough' and smallest-clean-diff preferences. Estimated ~7-8 files, 2 new classes.\nNote: options differ in kind, not coverage \u2014 no completeness score.\n0A) Reduce: keep AuthBroker + SessionMint, inject the existing adapter, drop AuthCache facade and TokenStore, make RequestPolicy a typed object (recommended) (human: ~1 day saved / CC: ~10 min saved)\n \u2705 Two new classes instead of five; the auth hot path stays readable in one sitting\n \u2705 Removes the pass-through facade that would otherwise need its own test suite\n \u274c If TokenStore was meant to hold non-cache state (refresh tokens, mint receipts), that need must be re-stated\n0B) Middle: drop only the AuthCache facade, keep TokenStore and RequestPolicy as classes (human: ~2 days / CC: ~20 min)\n \u2705 Keeps a dedicated place for token persistence separate from the validity cache\n \u2705 Still removes the pure pass-through wrapper\n \u274c Three new classes for one feature is still a lot of surface for 12 files\n0C) Proceed as-is: 5 new types, 12 files (human: ~3 days / CC: ~30 min)\n \u2705 Each concern gets its own named home, which some teams prefer for auth\n \u2705 No rework of the plan before implementation starts\n \u274c Facade with no new behavior and overlapping stores add coupling and test burden without user-visible gain\nNet: fewer classes with injected dependencies versus more named boundaries that mostly wrap existing code.": "0A Reduce to 2 new classes (recommended)",
"D4 \u2014 Enable cross-project learnings search on this machine?\nProject/branch/task: gstack setup for gstack-plan-count-I2kvlg; one-time config, not a plan finding.\nELI10: gstack can search learnings from your other projects on this machine to find patterns that might apply here. This stays local (no data leaves your machine). Recommended for solo developers. Skip if you work on multiple client codebases where cross-contamination would be a concern.\nStakes if we pick wrong: Enabled on a multi-client machine, a learning from one client's codebase could surface in another's review; disabled, this project only learns from itself.\nRecommendation: A because it is local-only, reversible with one config command, and compounding learnings is the point of the tool.\nNote: options differ in kind, not coverage \u2014 no completeness score.\nA) Enable cross-project learnings (recommended)\n \u2705 Reviews get smarter from patterns seen in your other local projects\n \u2705 Local-only lookup, nothing leaves the machine, one command to reverse\n \u274c On a shared or multi-client machine, unrelated project patterns may surface\nB) Keep learnings project-scoped only\n \u2705 Zero chance of cross-client pattern leakage in review output\n \u2705 Simpler mental model: this repo only learns from itself\n \u274c Slower compounding; every project restarts its learning from zero\nNet: faster compounding versus strict per-project isolation.": "Enable cross-project (recommended)"
},
"unansweredQuestionIndices": [],
"answeredAt": "2026-09-09T21:37:45.546Z"
},
"requiredTest": "- `legacyAuthFlow` regression test. Before the rewrite, capture the current\n input/output and side-effect behavior of `legacyAuthFlow()` for valid,\n expired, revoked, and wrong-tenant tokens. The rewritten path must pass the\n same assertions. What broke without it: the plan rewrote existing behavior\n with no test covering the changed path.",
"retryPacket": {
"sessionId": "afed76c6-b7b0-41a8-9a5d-90088b2471fe",
"toolUseId": "toolu_016RCPa88bGkVXejhUDAta4S",
"questions": [
{
"header": "Arch 1",
"question": "D4 \u2014 Issue 1 [P1] (confidence 9/10) PLAN.md:19-20,10: two services write the same cache entries with no serialization. Who owns writes?\nProject/branch/task: gstack-plan-count on main, PLAN.md Multi-tenant Auth Refactor, Architecture review.\nELI10: The plan says both AuthBroker and SessionMint mutate the shared cache (\"Both services mutate it\", PLAN.md:20) and that the cache rules \"do not serialize mutations\" (PLAN.md:10). D2 removed the module-level export, but two writers to one adapter is still a race condition: two code paths touching the same entry at once, so the last one to finish wins. Concretely, SessionMint writes a fresh session for tenant A while AuthBroker, mid-validation, overwrites the same key with a stale or revoked result. The tenant sees a session that is either dead or wrongly alive.\nStakes if we pick wrong: Intermittent auth failures or, worse, a revoked token briefly honored, and neither is reproducible in a unit test.\nRecommendation: 1A because separate key namespaces give each service exactly one writer, need no locking code, and are enforced by a type on the key builder. This maps to your explicit-over-clever preference.\nCompleteness: A=9/10, B=8/10, C=3/10\nNet: eliminate the race by design (A), fence it at runtime (B), or accept last-write-wins (C). <gstack-qid:plan-eng-review-arch-shared-writer>",
"options": [
{
"label": "1A Single writer per key namespace (recommended)",
"description": "\u2705 AuthBroker owns `validation:` keys, SessionMint owns `session:` keys; no entry has two writers, so no race to serialize. (human: ~3h / CC: ~15 min)\n\u2705 Enforced at compile time by a typed key builder; a wrong-namespace write fails the build, not production.\n\u274c Cross-namespace invalidation (revocation must clear both) needs an explicit fan-out in the adapter hook."
},
{
"label": "1B Per-key async mutex in one shared writer path",
"description": "\u2705 Both services keep writing anywhere; a per-key queue serializes mutations at runtime. (human: ~1 day / CC: ~25 min)\n\u2705 Handles future writers without re-partitioning keys.\n\u274c Adds a lock primitive and a lock-lifetime bug class (leaked or held-across-await locks) to an auth path."
},
{
"label": "1C Accept last-write-wins, document it",
"description": "\u2705 Zero code; the adapter already behaves this way today.\n\u2705 Fastest path to shipping the two services.\n\u274c A revoked token can be resurrected by a slower concurrent write; silent and untestable."
}
],
"multiSelect": false
}
],
"answered": true,
"failed": false,
"answers": {
"D4 \u2014 Issue 1 [P1] (confidence 9/10) PLAN.md:19-20,10: two services write the same cache entries with no serialization. Who owns writes?\nProject/branch/task: gstack-plan-count on main, PLAN.md Multi-tenant Auth Refactor, Architecture review.\nELI10: The plan says both AuthBroker and SessionMint mutate the shared cache (\"Both services mutate it\", PLAN.md:20) and that the cache rules \"do not serialize mutations\" (PLAN.md:10). D2 removed the module-level export, but two writers to one adapter is still a race condition: two code paths touching the same entry at once, so the last one to finish wins. Concretely, SessionMint writes a fresh session for tenant A while AuthBroker, mid-validation, overwrites the same key with a stale or revoked result. The tenant sees a session that is either dead or wrongly alive.\nStakes if we pick wrong: Intermittent auth failures or, worse, a revoked token briefly honored, and neither is reproducible in a unit test.\nRecommendation: 1A because separate key namespaces give each service exactly one writer, need no locking code, and are enforced by a type on the key builder. This maps to your explicit-over-clever preference.\nCompleteness: A=9/10, B=8/10, C=3/10\nNet: eliminate the race by design (A), fence it at runtime (B), or accept last-write-wins (C). <gstack-qid:plan-eng-review-arch-shared-writer>": "1A Single writer per key namespace (recommended)"
},
"unansweredQuestionIndices": [],
"answeredAt": "2026-09-09T21:49:10.064Z"
},
"retryRequiredTask": "- [ ] **T1 (P1, human: ~4h / CC: ~20min)** \u2014 legacyAuthFlow \u2014 Write characterization suite before any rewrite",
"retryProvenance": {
"sessionId": "afed76c6-b7b0-41a8-9a5d-90088b2471fe",
"reportSha256": "0a8018a1fd6652514ef2373640ea290e32a295ed39335972b9aeeb6540b6d697",
"historicalOutcome": "natural second-attempt assertion failure after plan_ready; replay never grants completion credit"
}
}