feat(transcript): noise tagging + llm review-relevance grading

[plind-junior]

makes the review console's session transcript skimmable — a long agent session
buries the few exchanges a reviewer needs to judge whether the session's
proposals are trustworthy. two presentation-only layers over the normalized
transcript; the raw session file stays the evidence of record.

what changed

• deterministic noise tagging (transcript.py): classify_noise tags
  injected scaffolding (system reminders, hook payloads, command output, meta)
  by prefix, and a message whose blocks are all noise rolls up to a single
  collapsed stub. no llm.
• llm review-relevance grading (transcript_grading.py, new): the
  deployment's compile.llm_cmd grades the surviving dialog messages key /
  low (ungraded = normal) so a reviewer skims to what matters. every reply is
  mechanically validated — out-of-range indices, unknown grades, non-dialog
  targets are dropped; an unusable reply degrades to an error note on the
  transcript, never an exception. results cache in state.db keyed by the raw
  file's content hash (index_db.get/put_transcript_grades).
• surface: vouch session transcript --grade (--regrade bypasses the
  cache) and the grade/regrade params on kb.session_transcript across mcp
  • jsonl. the review console renders the noise stubs and key/low badges + notes
    (TranscriptView.tsx, MessageBlock.tsx, transcript.ts).
• capture.load_config gains a VOUCH_CAPTURE_DISABLE guard so the grading llm
  subprocess does not capture itself back into the kb.

verification

full gate green: pytest (whole suite), mypy, ruff; webapp vitest (153 tests) and
tsc && vite build. new tests: test_transcript_grading.py,
test_session_transcript.py (+84), TranscriptView.test.tsx (+158). cli flags
confirmed wired. a live llm-grading drive needs a configured compile.llm_cmd
(not exercised here); the grading pipeline itself is covered by unit tests.

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• Commit unit tests in branch feat/transcript-noise-grading

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