evor-distill

name	evor-distill
description	Scan an existing ML workspace to produce a starting-point report; pre-fills the evor-setup interview
argument-hint	[workspace-path]
level	3
skills	["oh-my-evor:evor-mcp"]

evor-distill scans an existing ML repository and produces a StartingPointReport written to `/starting-point.json`. It classifies the workspace (greenfield / brownfield / evor-active / possibly-training), detects datasets, checkpoints, configs, and entry points, and scrapes any claimed metrics from READMEs or experiment logs. ALL scraped metrics and baseline candidates carry `verified: false` — EVOR will re-measure the baseline on the frozen split during setup and again on the first tick. The report pre-fills the evor-setup interview so the user confirms or edits pre-populated answers rather than typing from scratch.

<Use_When>

• User says "distill evor", "evor distill", "scan my ML repo", or invokes /evor-distill
• An existing ML codebase is present and the user wants to start an EVOR mission on it
• The session-start hook emits a brownfield nudge suggesting /oh-my-evor:evor-distill
• User wants to understand what EVOR detected before committing to the setup interview </Use_When>

<Do_Not_Use_When>

• A .evor/active-run.json already exists — the workspace is already an active EVOR mission; use /evor-run to resume
• The workspace is greenfield (no ML artifacts) — evor-setup works directly without distillation
• User wants contract/schema validation — use /evor-validate
• User wants environment health checks — use /evor-doctor </Do_Not_Use_When>

Step 1 — Resolve workspace and evor-root

Determine the workspace root and evor-root from arguments or defaults:

• <workspace>: use the argument if provided, else the current working directory.
• <evorRoot>: use $EVOR_ROOT if set, else <workspace>/.evor.

Step 2 — Run the scanner

Call evor_distill_scan({ path: "<workspace>", evor_root: "<evorRoot>" }).

This writes <evorRoot>/starting-point.json and returns a human summary. Bad or permission-denied paths are skipped; the scanner never throws on malformed input.

If the call returns {error: ...}, show the error and stop with:

evor-distill scan failed. Check that the workspace path is accessible and retry.

Step 3 — Read starting-point.json

Read <evorRoot>/starting-point.json and present a concise brief to the user:

=== evor-distill report ===

Workspace:    <root>
Class:        <workspace_class>
Framework:    <framework or "unknown">
Task guess:   <task_guess or "—">

Datasets (<count>):
  <list up to 3 notable entries: path  (kind, ~size)>

Models (<count>):
  <list up to 3 notable entries: path  (format, arch_guess if known)>

Configs (<count>):
  <list up to 3 notable entries: path — notable hyperparams if present>

Entry points: <entry_points joined by ", " or "none detected">

Scraped metrics:
  <for each: source_path — metric=value (split_hint if present)  [UNVERIFIED]>
  (none found)

Baseline candidate:
  Model:  <model_path or "none">
  Metric: <metric_name>=<claimed_value>  [UNVERIFIED — scraped from repo]
  Source: <source>
  — or —
  (none detected)

If warnings in the report is non-empty, print each entry prefixed with ⚠.

Step 4 — State the integrity framing

If a baseline_candidate is present (non-null), state clearly:

IMPORTANT: The baseline candidate value (<metric_name>=<claimed_value>) is UNVERIFIED.
It was scraped from the repository and has NOT been measured on a controlled split.
EVOR will re-measure it on the frozen split during /evor-setup (and on the first tick)
before it becomes the official baseline value tracked by the mission.
Never treat a scraped metric as a proven starting point.

If workspace_class is possibly-training, add this warning:

WARNING: A checkpoint or experiment log was modified within the last 10 minutes.
A training run may currently be active. EVOR will not touch any files.
Wait for the active run to finish, then re-run /evor-distill and /evor-setup.

Step 5 — Hand off to evor-setup

Print:

Starting-point report saved to: <evorRoot>/starting-point.json

Next step: run /oh-my-evor:evor-setup
evor-setup will read this report and pre-fill the interview (framework, dataset path,
model family hint, and baseline candidate) for you to confirm or edit.

<Tool_Usage>

• evor_distill_scan — deep-scan workspace; writes and returns a StartingPointReport to <evorRoot>/starting-point.json </Tool_Usage>