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REPL when skill_create needs user input

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Denton Social
2026-09-24 05:46:23 -05:00
parent e92b3e7228
commit 63922c1fad
15 changed files with 545 additions and 16 deletions
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AGENTS.md
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@@ -19,14 +19,20 @@ supplied options; an LLM is used only for generation and self-assessment.
```
cli.py argparse: run (REPL / --script), dream, skills, status, relabel,
dashboard
scheduler.py gate -> choice(tau) -> score -> queue; preempt + requeue
scheduler.py gate -> choice(tau) -> score -> queue; preempt + requeue;
a skill run paused for input (needs_input) keeps `current`
busy; `answer` routes straight to the pending run, bypassing
gate/score/navigation
queue.py urgency max-heap (desc weight, FIFO seq), age pulls toward 1.0
skills.py tree + registry (email.compose, response.reject, tracking.check),
navigation = SemIf choices per level (logged), create_category
and create_skill author + register stubs via the decision model
in generation mode; SkillBodyStore + materialize_skill persist
and hot-load runnable skill bodies from data/skills/
skill.py loop: observe -> predict -> act -> observe -> assess (LLM)
and hot-load runnable skill bodies from data/skills/;
ActionResult.needs_input pauses a run for human input
skill.py loop: observe -> predict -> act -> observe -> assess (LLM);
a run paused for input is resumed by re-invoking act with the
answer on request.user_input (predict is never re-run)
engine.py SemIfEngine -> semif_phase1.llamacpp_backend (lazy import)
codegen.py CodegenClient (OpenAI-compatible) writes runnable skill bodies
against SKILL.md; parse/validate (compile + predict/act)