v1.84.1.0 fix: default Codex and Claude to frontier models (#2835)

* fix: default cross-model workflows to frontier models

* chore: bump version and changelog (v1.82.1.0)

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

* fix: repair frontier eval budgets and workflow instructions

Preserve frontier models and quality thresholds while fixing truncated judge output, ordered section expansion, consent checks, QA scoring, and ship audit gates. Add regression coverage and refresh generated docs.

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

* fix: resolve workflow gaps exposed by frontier evals

Clarify plan-review ordering and fallback modes, preserve deploy readiness gates, honor configured merge methods, correct benchmark and canary contracts, and restore vendored installs on setup failure. Cover recovery with real-shell regressions.

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

* fix: use agent capture budgets for deploy evals

Multi-turn deploy and benchmark sessions were incorrectly limited to the single-call judge timeout. Use the existing capture tier and leave outer-test cleanup headroom, with a free policy regression test. Keep all behavioral assertions and frontier models unchanged.

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

* fix: clarify retro workflow and evaluate compare instructions

Include compare mode in the frontier judge excerpt, define metric sources and snapshot ordering, and preserve the existing prompt-size budget.

Co-authored-by: OpenAI Codex <noreply@openai.com>

* fix: make documentation release review and publication consistent

Review before commit, clarify changelog safeguards and unavailable reviewer modes, and preserve raw PR bodies across separate shell calls. Keep title sync in one shell and add regression coverage.

Co-authored-by: OpenAI Codex <noreply@openai.com>

---------

Co-authored-by: OpenAI Codex <noreply@openai.com>

CONTRIBUTING.md

@@ -137,6 +137,20 @@ never touches a symlinked or non-gstack directory.
 
 ## Testing & evals
 
+Codex evals and the GPT benchmark adapter default to `gpt-6-astra`:
+explicit model > `GSTACK_CODEX_MODEL` > default. Claude capture and judge
+defaults are `claude-fable-5-1`, resolved through `lib/eval-model.ts`:
+
+- Claude session, PTY, and Agent SDK eval runners and the Claude benchmark adapter: explicit model > `EVALS_MODEL` > `GSTACK_EVAL_MODEL_CAPTURE` > `GSTACK_EVAL_MODEL` > default.
+- Shared judge calls (including benchmark quality scoring): explicit model > `GSTACK_EVAL_MODEL_JUDGE` > `GSTACK_EVAL_MODEL` > default. `EVALS_MODEL` applies to capture runners, not judges.
+
+Warmup stays on `claude-haiku-4-5`; distill stays on
+`claude-haiku-4-5-20251001`. Explicit test and historical benchmark model
+selections still win. Known frontier defaults are maintained in releases;
+there is no automatic model discovery. Paid-run costs shown below are
+historical estimates from before this default change, not measurements of
+the new defaults.
+
 ### Setup
 
 ```bash
@@ -289,7 +303,7 @@ Artifacts are never cleaned up — they accumulate in `~/.gstack-dev/` for post-
 
 ### Tier 3: LLM-as-judge (~$0.15/run)
 
-Uses Claude Sonnet to score generated SKILL.md docs on three dimensions.
+Uses `claude-fable-5-1` by default to score generated SKILL.md docs on three dimensions.
 Override the judge model per run with `GSTACK_EVAL_MODEL_JUDGE`:
 
 - **Clarity** — Can an AI agent understand the instructions without ambiguity?
@@ -302,7 +316,7 @@ Each dimension is scored 1-5. Threshold: every dimension must score **≥ 4**. T
 # Needs ANTHROPIC_API_KEY in .env — included in bun run test:evals
 ```
 
-- Uses `claude-sonnet-4-6` for scoring stability
+- Resolves the judge model through `lib/eval-model.ts`, using the override order above
 - Tests live in `test/skill-llm-eval.test.ts`
 - Calls the Anthropic API directly (not `claude -p`), so it works from anywhere including inside Claude Code