--- name: transform description: 'Use this to author and change a dbt project or a semantic layer: bootstrap a project (`transform init`), write or refactor models from staging to marts, add tests and docs, and define semantic models, entities, dimensions, and metrics in MetricFlow or native Apache Ossie documents. Reach for it instead of editing model files by hand whenever a change spans more than one file or must stay consistent with the project: it validates the edit against the real schema, returns a reviewable diff with a plan id, and catches what otherwise fails at `dbt run`, such as wrong columns or broken refs. Bug-fix tickets count: "this model returns wrong numbers, fix it" is a transform task. Also for "build a staging model for this table", "define a revenue metric", "add a dimension to this entity". Warehouse builds are dev-target only, gated, and cost-surfaced first. If you have not verified the source tables'' columns or grain, use explore first. For a project that drifted from the warehouse, use maintain.' compatibility: 'Needs a local shell and uv. On first use, uv downloads the exmergo-dex-core engine from PyPI at the version scripts/run.py pins. Runs in Claude Code or another agent that loads Agent Skills and has a shell, not in claude.ai chat.' --- # Transform Author and refactor the dbt project, both the SQL (staging to marts, tests, docs) and the semantic layer on top. You write the file content; the engine validates it, computes the diffs, and stores a plan. Nothing reaches the project until `transform apply`, and any build runs against a dev target only. ## Procedure dex works in one loop: explore, transform, maintain. Every step runs one engine command, reads the single JSON envelope it prints, and decides the next step from that envelope. 1. **Explore before you write.** Before writing or fixing SQL against a table whose columns, types, grain, or join keys you have not verified in this session, run `explore map` (or `explore profile ` for a few named ones) and read its grain, keys, PII flags, and data-quality findings. Answer ad-hoc questions with `explore query`, never with a raw database client. 2. **Plan the change.** Author the file content and hand it to `transform plan` (or `semantic define|update|plan` for the semantic layer). Nothing is written yet. Read the diffs, the `warnings`, and, on a model that already exists, `data.row_attribution`; re-plan until they describe the change you meant. 3. **Apply it.** `transform apply ` writes the plan as a reviewable git diff. A human edit made since planning comes back as `needs_confirmation`: re-plan against the current files. 4. **Build and verify on dev.** Run `transform build --target dev --verify`. Read `data.verification.ran` first, then relay the findings and anything under `suppressed`. A green build says dbt ran, not that the rows are right. 5. **Maintain.** `maintain check` compares the warehouse and the project with the `.dex/snapshot.json` baseline, and `maintain verify` checks the project as it is now with no baseline. `maintain reconcile` proposes the fix as a plan, applied with `transform apply`. Take `maintain snapshot` after a known-good build. At every step: a `needs_confirmation` envelope waits on the user's decision (a spend, or a `dex config` diff), never on yours; only a human clears a PII flag; and you never edit the dbt project, `.dex/config.yml`, `.dex/cache.json`, or `.dex/plans/` by hand in place of the command that guards them. ## Running the engine ```bash uv run --no-project --script "${CLAUDE_SKILL_DIR}/scripts/run.py" [flags] ``` Installed as a plugin or skill, `run.py` runs the `exmergo-dex-core` engine from PyPI at the exact version its `DEX_CORE_VERSION` line pins, built from https://github.com/exmergo/dex/tree/main/packages/dex-core. - `uv` is a prerequisite that Claude Code does not install. If the shell reports `uv: command not found`, stop and tell the user to install it (`brew install uv` or `pipx install uv`, or the installer for their platform from the uv docs), then re-run. Tell them the command; never run an installer yourself. Never fall back to editing the dbt project by hand instead: the validation, the diffs, and the dev-target gating live in the engine, so any other path is unguarded. - The first command in a fresh environment installs the engine and can take tens of seconds. Offer `run.py --warm` once at setup to pay that up front; do not run it before ordinary commands. ## Transforming, step by step 1. **No dbt project yet?** Offer `transform init "" --connector ` before anything else. Ask the user for the name and **confirm the connector with them**: init never defaults one. Do not hand-write the skeleton. Read `${CLAUDE_SKILL_DIR}/references/init-and-dev-target.md` for per-connector setup, `--layered-schemas`, and the namespace warning. 2. **Find every use first** when a change has to land in more than one place: `transform references [more...]`, free on every connector. Read `data.completeness`; when it is `incomplete`, open each site under `data.indeterminate` and decide yourself rather than treating the resolved list as exhaustive. 3. **Author and plan.** Write the content into an edits file and run `transform plan "" --edits-file ` (`--scaffold ` drafts a staging model from the `.dex/` cache). The payload shape and each `kind`'s rules are in `${CLAUDE_SKILL_DIR}/references/edit-kinds.md`. For a rename or a removal, use `transform rename` / `transform remove` instead of assembling edits. For a derived column several models need, ask `transform place` where it belongs. For the semantic layer, use `semantic define|update|plan` (dbt) or `semantic ossie define|update|plan` (native Ossie); read `${CLAUDE_SKILL_DIR}/references/semantic-layer.md` first. 4. **Read the plan** (rules below), then `transform apply `. 5. **Build and verify:** `transform build --target dev --verify`. 6. **Measure the tests** right after you author or scaffold them, and before telling the user a model is covered: `transform test --mutate `. Per-command fields and flags are in `${CLAUDE_SKILL_DIR}/references/commands.md`. Shipped macros are in `${CLAUDE_SKILL_DIR}/references/macros.md`. Read them when a field, flag, or macro you need is not described here. ## Rules that change what you do ### Bootstrapping - Credentials are discovered, never asked for. When init or a build reports missing credentials, relay the fix it names (for example `gcloud auth application-default login` or `databricks auth login`); never ask for a key, token, or password. - Init warns when a namespace it would build into already holds objects. Relay it and ask whether the content is the user's (a previous dev build) or unrelated. If unrelated, discard the freshly scaffolded project (nothing was built), point the config at a different dev namespace, and re-run init. ### Reading a plan - `data.row_attribution` names every predicate, join, source, and grain change on an existing model, each measured against the prior model. A change you were not asked to make that carries a non-zero `delta` is the signal to look at: the model still compiles, and now returns different rows. `attributed: false` is unknown, not zero. On a billed connector, measuring needs `--attribute-rows` plus the cost handshake, so ask the user before spending. - A SELECT list that diverges from the model's `schema.yml` is warned in both directions. Fix whichever side is stale, and tell the user which one you decided it was. - A warning that a model **exposes a raw foreign key with no resolved counterpart** names sibling precedent and a parent. Prefer resolving it the way the siblings do. If the raw key is deliberate, say so plainly. Never switch the check off yourself: `conventions.resolved_keys: false` is a house-style decision to recommend to the user. - An entirely `unchanged` semantic plan changes nothing: check whether you meant to edit something. - Read every note on an Ossie plan: each names something that was not checked. ### Applying and refactoring - If `transform apply` returns `needs_confirmation` because a human edited a file, re-plan against the current state. Re-run with `--confirm` only when the user says so. - List plans with `transform plans`; never browse `.dex/plans/` by hand. - A delete is refused while a surviving file still `ref()`s it. Carry the edits that remove those references in the same plan. - `transform rename` needs a column named as `model.column`. It refuses rather than half-applying, and there is no override: fix what the refusal names and re-run. Compare `data.sites` with the `transform references` output; the two agreeing is your evidence nothing was dropped. - `transform remove` never rewrites a read. Author those edits yourself (only you know whether `{% if var('x') %}` is dropped or unguarded) and pass them with `--edits-file` in the same call. - `transform place`: read `data.reasoning` before applying (`--explain` asks for free). When `data.strategy` is `per_target`, relay the reason rather than applying duplicated copies on the user's behalf; often the fix it names is what they want. - Use a shipped macro (`transform macro `) rather than hand-rolling or inlining a copy of it, and do not hand-write `generate_schema_name`. When a plan warns that a called macro is missing, scaffold it. Do not "fix" the BigQuery quirks `unpivot_json_object` absorbs back in. ### The semantic layer - Prefer `--definitions-file` over `--edits-file` for dbt semantic models: send only the definitions that change, so every other byte of the shared file survives. Use `--edits-file` to create, move between, or empty files. - `semantic define` refuses a name that exists and `update` one that does not; use `semantic plan` for a change that mixes both. A removal is `"op": "delete"` on `update` or `plan`. If a surviving metric still reads what you remove, add that reader's own delete or update to the same payload. - A project with no MetricFlow time spine cannot parse semantic models. Author one (a day-grain date model plus a `time_spine:` config) in the same or a separate plan. - For native Ossie, edit only documents whose paths are listed in `semantic.ossie.files`, as whole documents. `maintain reconcile` never authors into Ossie; this command does. ### Seeds and PII - A seed puts values into git. Never build one out of warehouse rows you have not looked at: detection reads names and types, never values, so it cannot see personal data under a neutral column name. - A seed whose header looks like personal data is refused; the refusal names the `pii_overrides` entry a human can add to `.dex/config.yml`. Recommend it. If the user agrees, propose it with `dex config set pii_overrides ''` (the whole list, existing entries included: read them with `dex config get pii_overrides`) and let them confirm the diff; never confirm it yourself. - PII flags are stamped into model and column `config.meta` at any confidence. Only a human `pii_overrides` entry removes the stamp. ### Building - `transform build` runs against a dev target only. Production-looking targets are refused outright, and `--confirm` cannot override that. - Before the cost gate, a build refuses for free when `.dex/config.yml` and `profiles.yml` disagree, or when the dev database does not exist. Relay the fix it names: edit one file to match the other (the engine never rewrites `profiles.yml`), or give the user the `CREATE` or `GRANT` statement to run. dex will not create a database itself. - On a billed connector the first call returns `needs_confirmation` with an estimate (`per_table_bytes` names which node drives it). Surface it, get an explicit budget from the user, and re-issue with `--confirm --budget ` grounded in that number. Never invent a budget, and never retry with a raised one after an over-ceiling refusal without asking. Relay the calibration line, and point out that the ceiling binds on the estimate. - A `suggested_session_ceiling` is the project's one-time ask for a daily cap. Surface it, get the user's answer, and add `--session-ceiling ` or `--no-session-ceiling` to the same re-issue. Never answer it for them. - `--verify` is priced into the build's own estimate as a `(row counts)` line, so never add a second budget for it. An `ok` envelope with `data.offer` means the build is done and billed: relay the offer instead of re-running the build. - Verification findings never fail the build. Do not treat one as a failure or re-run to make it go away: relay the finding, its two counts, and the join it names. Relay a suppression too: it separates "checked and clean" from "not checked". - On ClickHouse, keep the `custom_settings` block in `profiles.yml`; it is how the confirmed budget becomes a server-side cap. ### Test mutation - Relay each survivor's `defect` and `suggested_test`: the user's next action is to write that test. Quote `score` as context, never as a grade, and never compare it between models. - Each survivor's `equivalence.status` decides which test to suggest. Relay `distinguishable` survivors first: an assertion over the dev data would catch them today. An `equivalent` one can only be caught by a unit test fixture that reaches the case, so say that rather than suggesting an assertion. On BigQuery or Snowflake the check needs `--check-equivalence` and joins the same single estimate, so ask the user before adding it. Relay a `not_checked` survivor's `reason` rather than guessing a label. - Check `baseline.excluded` (tests already failing) and `cap.elided` (more sites than the 20-mutant cap) before calling a result clean, and relay any `not_run` rather than reading a short list as complete. ## References - `${CLAUDE_SKILL_DIR}/references/edit-kinds.md`: the edits payload, every `kind`, its path family and validation, the three kinds of test, and deletes. - `${CLAUDE_SKILL_DIR}/references/commands.md`: `references`, `rename`, `remove`, `place`, `build`, `build --verify`, `test --mutate`, and `deps` in detail. - `${CLAUDE_SKILL_DIR}/references/init-and-dev-target.md`: per-connector init and how to prepare a dev target. - `${CLAUDE_SKILL_DIR}/references/semantic-layer.md`: authoring dbt semantic models and native Ossie documents. - `${CLAUDE_SKILL_DIR}/references/macros.md`: the shipped macros and the `unpivot_json_object` contract.