---
name: sync-ml-reports
description: >
  Copy skore reports between local, Hub, and MLflow with `skore
  sync`, and optionally switch the recorded upload destination.
  Trigger when the user asks to sync or migrate reports, switch
  skore mode, upload reports to Hub or MLflow, or pull Hub/MLflow
  reports onto disk. First G-SKORE-MODE pick stays
  evaluate-ml-pipeline.
metadata:
  modelTier: medium
---

# Sync ML Reports

Copy reports with the `skore` CLI. Switch the default destination
only when the user asked to. Do not evaluate, audit, or invent
`Project.sync` Python.

## Human-facing prose

Details: `setup-workspace` `references/human_facing_prose.md`.
Ask where reports live (disk, Hub, MLflow) in those words. Do not
name `G-SKORE-MODE`, skill ids, or the wrapper CLI in the
question. `skore sync` output may appear in the close as the
sync table.

## Procedure

1. Run `python -m skore_skills status`. Read `policy.skore_mode`
   and `skills`. Open `experiments/` and `audit/` for the
   `skore.Project(...)` init block: `name=`, Hub `workspace=`,
   MLflow `tracking_uri=`. Local store is always the workspace
   `reports/` directory (absolute path). Never omit
   `--from-workspace` / `--to-workspace` on a **local** endpoint.

2. If `policy.skore_mode` is unset: STOP. First pick is
   G-SKORE-MODE in `evaluate-ml-pipeline`. Do not ask local / hub
   / mlflow here. Load that skill only if
   `status.skills.evaluate-ml-pipeline` is true and the user
   asked to evaluate; else one-line skip. The close is only this
   stop: the destination is not chosen yet and is picked when a
   report is stored. Do not list local, Hub, or MLflow, a
   workspace name, or a tracking URI. Do not use the
   source-to-destination close below.

3. **AskUserQuestion** for any answer not already in the request.
   Ahead of each question, state in 2–4 lines what the answer
   authorizes — which reports move where, whether `skore_mode` and
   the Project init lines get rewritten — and the facts it rests
   on: the current mode, the discovered report count, the
   endpoint. A file link is an addition, never the context.

   - **Intent.** Switch default destination (sync, then persist
     `skore_mode` and rewrite every Project init) vs copy only
     (sync, leave policy and experiment files).
   - **Destination** — same three options as G-SKORE-MODE:
     `local` (disk, no account), `hub` (https://skore.probabl.ai),
     `mlflow` (tracking server). Hub: ask the workspace name; it
     MUST NOT contain `/`. MLflow: ask `tracking_uri`; confirm a
     bare `host:port` as `http://host:port`. Do not default the
     URI.
   - **Project name** if `name=` is missing or disagrees across
     files.
   - **Dry-run first** vs transfer now.

   If intent is **switch** and destination equals
   `policy.skore_mode`, stop in one line.

4. Destination extras: load `add-python-package` only if
   `status.skills.add-python-package` is true, for Skore at the
   **destination** mode (`env add-skore --mode <dest>`). If that
   skill is missing, name Skore for the destination and stop. Do
   not splice `pip install` / `skore[...]` here.

5. If Hub is source or destination: require `SKORE_HUB_API_KEY` in
   the environment. Missing → name it and stop. Do not open a
   browser login. Do not read `.skore` for the key.

6. Build `skore sync`. If `skore` is not on PATH, name
   `skore-cli` and stop. Do not call `skore.Project.sync` in
   Python.

   ```bash
   skore sync <project> --from=<source_mode> --to=<dest_mode>
   ```

   Source mode is `policy.skore_mode`. Add:

   | Endpoint | Flags |
   |---|---|
   | local | `--from-workspace` or `--to-workspace` = resolved `reports/` |
   | hub | `--from-workspace` or `--to-workspace` = Hub workspace name (required) |
   | mlflow | `--tracking-uri=...`; never `*-workspace` |

   `--to-project` only if the destination name differs.
   `--hub-url` only when `SKORE_HUB_URI` (or the user) names a
   non-default Hub. `--both` only if the user asked to copy
   missing reports both ways. Otherwise one-way.

   If the user picked dry-run first, run with `--dry-run`, show
   the plan, then ask to transfer. Live run omits `--dry-run`.

   Usage/auth/backend errors: name stdout/stderr and stop. Do not
   invent a Python fallback. Empty output `No reports to
   synchronize.` is success (nothing to copy; a **switch** may
   still continue).

7. **Switch intent only**, after a successful (or empty) sync:
   `python -m skore_skills policy set skore_mode <dest>`.
   Rewrite every Project init in `experiments/` and `audit/` to
   the destination form in
   `evaluate-ml-pipeline/references/g_skore_mode.md` (audit must
   match the paired experiment, byte-for-byte modulo formatting).
   If dest is **local**, `mkdir reports` (`exist_ok`); no README.
   If **hub** or **mlflow**, do not create `reports/`.
   If `journal/JOURNAL.md` exists, insert a `---` under History
   and one line `skore_mode: <old> → <dest> (sync-ml-reports)`.
   Missing journal → skip in one line; do not paste a JOURNAL
   body.

   **Copy-only:** do not `policy set`, rewrite init, mkdir, or
   edit JOURNAL.

## Stop conditions

- Do not steal first G-SKORE-MODE when `skore_mode` is unset.
- Do not silently change a recorded mode; switch requires the
  switch intent (or an explicit user request to switch).
- Do not `git commit`.
- Do not evaluate, `project.put`, or audit.
- Do not pass `*-workspace` on an MLflow endpoint.
- Do not omit `*-workspace` on a local or Hub endpoint.

## End of turn

### User-facing close

This close applies only after a sync. An unset `policy.skore_mode`
uses the step-2 stop instead.

Short story: source → destination, whether policy changed, and
the `skore sync` table or `No reports to synchronize.` Do not
dump experiment files.

Then `python -m skore_skills git end-turn --stage evaluate`
(the persist bucket for this work; this is not a CV run). If
JSON `action` is `invoke`, load `persist-ml-git` only if
`status.skills.persist-ml-git` is true and stop; that skill
returns to triage. If persist is missing, name the pending
`staged` paths and stop. Otherwise load `triage-ml-task` only if
`status.skills.triage-ml-task` is true; else stop. No `git
commit`.