Completes step 7.
- expert.py: one stateless call for a question needing no repo access.
Structured output is contracted at the prompt level, since vendors
differ on JSON enforcement, so the reply is parsed and validated
locally with one retry — tolerating a fenced code block, because
models wrap JSON habitually, but not missing fields
- The per-task budget is counted from the canonical log rather than
memory, so it survives a restart and cannot hand a circling executor
a fresh allowance. Exhaustion raises rather than answering: a caller
out of consults should get on with the work or escalate
- Consults are recorded as delegation_started/completed with role
consultant. A16 asks for a "consult/delegation eval set", and
reusing the composite events gets consult evaluation for free rather
than inventing a parallel record
- evals.py pairs starts with completions into eval records, with
verdicts kept outside the canonical log: the log records what
happened, a verdict is a later judgement about it, and judgements
get revised. Schema v3 adds the outcomes table, so a v1 store now
traverses two migrations — a better exercise of the hook than one
- ask_expert is offered to the executor as a tool only when a desk is
configured, in addition to the observable escalation triggers and
never instead of them (A12). Consulting is not mutating, so a
completion claim backed only by consults is still challenged
Found live: passing an empty message list and putting the question in
the system prompt fails outright — the Messages API requires at least
one non-system message. The question now travels as a synthesised user
message that is never appended to the log, which keeps the consult
stateless while remaining a valid request.
Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
dongarandClaude Opus 5