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 simulate` reads the model `question_lint --needs-sim`
exports. A visitor model picks an alternative and fills the form in a
manner that varies by run; the case is then walked along the handling
group's own desk buttons to a finished state, a different one each
run, so every state and button is exercised. At each button the
handler model is asked one thing: with only what the form collected,
could this role really do what the button claims? Its question goes
back to the visitor, who may not know.
Who wins is deliberately not simulated. The first version let the
handler decide: qwen3:8b sent every case to "won", and after one
sentence of prompt change, every case to "lost". Outcomes belong to
the live bucket; `success` in needs.yaml is what a report over real
records counts.
`compare` sets two score files side by side. engines/ollama.sh honours
SEED, FORMAT=json and TEMPERATURE so the same case replays the same
way against two versions of a site. generator/reference.md documents
`success` and `stages`.
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
