The planner's single-shot Claude call intermittently failed with "Reached
maximum number of turns (1)" — it needs slightly more headroom than the
clarifier to finish emitting its JSON. Phase A of the planner-reliability plan:
- plan_node now invokes with max_turns=4 (allowed_tools stays []; the extra
turns buy completion, not exploration).
- build_plan_prompt instructs the model to use no tools and return only JSON
(a tool_use would consume the single turn before the plan is emitted).
- plan_node auto-retries the model call exactly once on a TRANSIENT failure
(turn-cap exhaustion or an empty reply), and fails fast on DETERMINISTIC ones
(malformed JSON, missing/blank phases) — a retry would just reproduce those.
review_loop_llm.py is intentionally GPT-4.1 cross-family (no claude_invoke), so
it gets no turn-budget change. verifier_llm.py does use claude_invoke but is P3
build/verify scope — left for a follow-up.
Tests: max_turns passthrough; retry on turn-cap and on empty; no retry on
malformed JSON; the no-tools prompt line. 1387 passed.
Two root causes behind 'every task parks, and slowly':
1. SINGLE-SHOT INVOKER: subscription Claude calls ran as 40-turn, tool-enabled
agentic sessions (--max-turns 40, $2 budget) for what are pure reasoning->JSON
completions — minutes-long, and Claude wandered/returned unparseable output.
_DEFAULT_MAX_TURNS 40->1 + allowed_tools=[] -> fast deterministic single turn.
2. PLANNER FEEDBACK KEY MISMATCH: the review stage writes verdict/findings, but
_format_review_feedback read decision/notes/comment (never present) -> the
planner re-planned with EMPTY feedback, re-introduced the rejected flaw
('assumptions persist'), hit the review cap, parked. Now reads verdict/findings
(old keys kept as fallback) so GPT-4.1's objections reach the re-plan.
Plus: park notifications infer the phase the task was IN (review/plan/clarify)
instead of the terminal 'parked'.
Tests: planner real-verdict-keys regression + coordinator phase-inference. 1149 pass.
