context-generate

# ult-context-generate > **Status: piloting.** The What-L3/What-L2 dual-layer model, D10 blast-radius > analysis, D11 constraints layer, and the D12 handoff to a downstream generation > skill were validated end-to-end on a real ~40 KSLOC FastAPI codebase (an RBAC > guest-role feature, run through a full context-package generation and approval > cycle) before this migration. Now rolling out to a small set of pilot users on > substantially larger codebases (500 KSLOC+, often multi-repo), where the What-L1 > (external-spec) layer remains disabled and token-cost behavior at this scale is > still an open question. Report findings (works well / doesn't / surprises — > especially around graphify query budgets and token costs at scale) as an issue > in this repo so this can graduate out of pilot status or be reworked. > > **What-L1 fallback (Step 7.1, D13/D14) is also now piloting** — a small > `specs/external/` corpus is indexed by `scripts/md_index.py`, a > Python-stdlib-only CLI that builds a deterministic structural index > (headings, clause ids, section bounds, resolved cross-references — "the > graphify for markdown"; see `scripts/README.md`). Step 7.1 builds this index > once per run (`--stale-check`, the same build-once contract `graphify update` > uses), then queries it per both-layers-gap aspect with synonym-expanded keyword > matching to bridge terminology gaps between an aspect's wording and the external > spec's own terms. Validated end-to-end against a real downloaded ...