dongarandClaude Opus 5 2b7651fb37
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Add ask_expert and eval capture (A14/A16) — step 7c
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>
2026-09-08 19:48:13 +00:00

Nisse

Two self-hosted AI agents sharing a common library, named for the Nordic farm spirit that keeps the place running overnight and expects to be treated well in return.

Package Role
nisse-core/ Shared library both agents sit on (Part A)
nisse-dev/ Dev Agent — plans and implements software projects (Part B)
nisse-ops/ Sysadmin Agent — operates infrastructure (Part C)

One repository, three packages. The library does not exist as code yet: it is extracted from nisse-dev once that agent works (build-order step 10), as a package split within this tree.

Architecture

The system-level specification lives at docs/Architecture-Build-Spec.md. It covers the shared library, both agents, the supporting services, the build order, and the remaining open decisions.

S
Description
LLM Agents for specialized tasks.
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