EXTENSIONS

STL file validator — checks triangle count, degenerate faces, bounding box

Backblaze B2 data-plane transfers via the Native API v4 — the thirteen upload, download and large-file operations, guarded. Inventories the interrupted large uploads B2 bills for invisibly, proves a bucket is readable and writable end to end, and refuses to move more than 100 MB without an explicit override.

Validate one restic repository from a neutral host — snapshot freshness and backup-scope drift, structural check, read-data verification against bitrot, a dump canary, and a size-capped restore drill that proves the backup can actually be restored. Strictly read-only: it refuses every restic write command and never takes a repository lock, so it can never break the backup it validates.

Validates a caller-supplied parsed test result for internal consistency and a recognized multi-language test-runner command, then commit-pins the evidence to an immutable Git commit and branch, returning a single pass/fail verdict.

Rank a restic fleet by what has actually been proven restorable. A workflow-scope report that joins every @sntxrr/restic/repository step in a run — freshness, structural check, read-data verification, canary dump and restore drill — into one ranked findings list, where a rung that has never run is itself a finding. Read-only: it reads what the steps already wrote and never touches a repository.

Is this Jev question safe to build on? A pre-flight check for TypeSafe System One questions. Runs a fully crossed item x framing x repeat grid against the API and reports what you need settled before putting a model's number behind an `if`: repeatability (does an identical request give an identical answer), framing sensitivity (does rewording move the answer, and by how much more than plain noise), resolution (can the question tell your items apart, or does the scale saturate into unrankable ties), threshold stability (does a fixed cut-off flap on identical input), and answerability (is it confidently rating things that have nothing to rate). Works on all three primitives — score for rating, noul for gates, choice for routers. The headline is a decision flip rate: if you reran this, how often would the decision your code acts on come out differently? The report adds a nested variance decomposition that separates repeat noise from framing sensitivity from real differences between items, fitted by a Gibbs/slice sampler in TypeScript so it needs no Stan, R or Python, and it withholds the posterior when the convergence gate fails. It does not take your paraphrases on trust: it hashes every request body and refuses to count a perturbation that produced a byte-identical request.

Build and validate the Mere package-manager source tree through fixed, cancellable Zig commands, and package its fresh-branch delivery workflows. Does not download Mere releases, manage a Mere root, build recipes, publish artifacts, or provide credentials.

Tracks a Docker Compose project's structure (services, volumes, networks) and flexible key/value configuration as swamp-managed data. Data-only — pair it with @keeb/docker/compose for actual lifecycle execution. Every parameter, service field, and volume/network option is validated against the official compose-spec JSON Schema before it's written, so typos and malformed values are rejected at write time rather than surfacing later as a broken `docker compose` run. Ships with a bundled schema snapshot so it works fully offline out of the box; run the updateSchema method on an instance to refresh it from the canonical compose-spec repository when you need a newer field.

Let an AI fill in an analysis template without letting it touch the science. Governed parameter-fill: the AI fills ONLY the typed parameter slots of a frozen template, and `validate` is the deterministic gate that asserts the frozen structure was untouched and every fill satisfies its slot contract — bounded, validated, reproducible AI authoring, not free-form code generation. `author` builds Quarto (.qmd) or Jupyter (.ipynb) templates from structured cells (the writer owns the document layout and binds each param at its declared type) for R or Python; `init` wires an R project to record its work. The guarantee: what the AI can change is exactly the typed slots and nothing else — the template is the contract.