Work from another session, committed as found (tests green):
- `plan` reads an intake into a plan.yaml (a model decides needs,
stages, forms and budgets; a person reads the result before build).
- Plans gain `doors` (a first question before the forms, when a front
door would carry more than five needs), `groups` with labels that a
select may draw its options from (`options_from: groups`), `private`
fields kept off public pages, `multiple` selects, and `max_fields`
as what the intake said the person will tolerate.
- `card.rs`: an alternative as the visitor meets it, in text, so the
answering visitor and `rate` read the served card, not the heading.
- `rate` reads followup pages from the repo and reports "what happens
next" as not measured rather than zero when it cannot.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01L4jrCgLiKKHAEFuZUJjckH
Every prompt and reply is now kept under <out>/llm/. An empty reply is
a retry, not a fatal error; a spec that never parses stops the run
before the structure phase; --visitor-llm lets a different model play
the visitor. The file-block parser finds markers anywhere in a line,
accepts a short END and lets a new FILE close an open one, after a
reply glued two files together with `<<<END>></think>`. The reference
gains a language section: copy in the intake's language, identifiers
in ASCII.
runs/rehab-entreprenor-no-2026-09-21: nemotron-3.5-lightning:30b-a3b
did not produce a loadable site. Written up with the reason and the
way forward: structure from needs.yaml deterministically, words from
the model.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01L4jrCgLiKKHAEFuZUJjckH
`portal-trainer generate` turns a plain-words business intake into a
content repo in three phases, each held to portal's question_lint:
needs.yaml (then frozen, so the generator cannot weaken the spec to
pass), structure (revised against the lint's findings until green),
and wording (personas answered blind, misroutes fed back; a rewrite
that breaks structure is reverted). Model output is written to disk
only under aggregates.yaml, site.yaml and questions/**.yaml.
`portal-trainer answer` is the blind answerer alone.
The LLM is an external command, prompt on stdin, text on stdout:
engines/ollama.sh (local Ollama), engines/anthropic.sh (API key),
engines/mailbox.sh (hand each prompt to an agent or a person).
portal-portal/ is the onboarding site as a portal content repo: the
front door is the intake interview, records land in `onboardings`
(open -> drafted <-> revising -> live | declined), and it passes its
own needs spec.
runs/uhhm-2026-09-21/ollama: qwen3:8b and granite4.1:8b as blind
answerers on the same eight tasks.
Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01L4jrCgLiKKHAEFuZUJjckH
