IMPORT-NORMALIZE-PIPELINE.md markdown
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sha256:c2dbf04d56308f3bbf2d06e6d2eb022b8948b1e827195fe525a44e5e18d5f9c0 feat(auth): Phase B Connect cloud agent (RFC 8628) + Hermes… Human minor ⚠ breaking 11 days ago

Optional post-import normalization (agent JSON, LLM)

Today, import is implemented as format-specific parsers in lib/importers/. LLM usage in that path is limited to Whisper transcription for audio/video (lib/transcribe.mjs).

Problem

Agents or external tools may emit JSON or Markdown that does not match SPEC.md frontmatter (title, tags, optional intention fields in §2.3). MCP write currently accepts string key/value frontmatter only (lib/write.mjs); arrays must be represented in a way the writer can serialize correctly.

Add an explicit stage so deterministic importers stay testable:

  1. Normalize (rules) — Map known vendor keys to SPEC fields (no model).
  2. Normalize (LLM) — Optional: one shot “produce YAML frontmatter + body only” with a fixed schema and validation; reject on parse failure.
  3. Validate — Reject or quarantine notes missing required fields for your policy (e.g. inbox contract §2.2).

Implement as a separate subcommand or Hub action (e.g. knowtation import normalize <path> or “Normalize note” in UI), not hidden inside every importer.

Contract

  • Input: Path to a note or a JSON file + target vault path.
  • Output: Updated note or new note under inbox/ / staging, with machine-readable normalization_provenance (or equivalent) in frontmatter for audit.
File History 1 commit
sha256:93bcf8f9bd56d8c5b9339f4ec73b9ebd66571398d56262d38eedc2cfa9db9882 fix(test): align Band B landing assertion with desktop MCP … Human 11 days ago