Imported from organvm-iv-taxis/a-i--skills (skills/data/prompt-atom-formalization/SKILL.md). Install upstream with npx skills add organvm-iv-taxis/a-i--skills --skill prompt-atom-formalization. Copyright stays with the author (MIT).

Prompt Atom Extraction & Formalization

Convert loose operator prose into atoms: minimal, classified, machine-readable units of intent that registries can store, pipelines can route, and future sessions can execute without re-interpreting the original wall of text.

Why this exists

Operator intent arrives packed — one dense paragraph can carry a standing law, two directives, a constraint, and an open question. Left as prose, that intent is executable only by whoever re-reads and re-derives it. Atomized, each unit gets an ID, a class, a lifecycle state, and provenance — it becomes governable. The doctrine: atoms are permanent; extraction is additive; nothing in the source is destroyed by being formalized.

The atom classes

The three states

• RAW — verbatim source span, untouched. Always preserved (quoted or referenced by span), never edited.
• CLEANED / FORMALIZED — the intent restated minimally in normalized language, classified, given frontmatter.
• ELEVATED — the atom generalized to its standing form: stripped of incident-specific detail, linked to related atoms, ready for constitutional or registry placement. Only laws, values, and constraints elevate; directives and questions resolve instead.

Every atom records which state it is in; an extraction pass may legitimately stop at CLEANED.

Workflow

1. Segment the source

• Split the text at intent boundaries, not sentence boundaries — an intent is one irreducible "do/never/prefer/decide" unit.
• Dense prompts pack abstractions: expect 3–10 atoms per operator paragraph. Under-segmentation (one atom per message) is the dominant failure.
• Assign each segment a provenance span: {file, line-range} or {session-id, message-index}.

2. Classify

• Apply the class table. Disambiguation tests:
  • Would it still bind next month? → law/value/constraint, not directive.
  • Does it command an action or bound an action? → directive vs constraint.
  • Can the agent resolve it alone? If no → question.
  • Are multiple mutually-exclusive futures named without choosing? → branch-vector.
• When torn between law and value: laws are violated, values are traded off. If you can imagine a sanctioned trade-off, it's a value.

3. Formalize into frontmatter

- id: ATM-NNNNNN            # mint from the registry's counter — never invent ranges
  class: constraint
  state: CLEANED
  text: "Never `chezmoi add` over existing source without `chezmoi diff` first."
  raw: "…also for god's sake diff before you chezmoi add anything again…"
  provenance: {session: 8bb8f846, message: 41}
  captured: 2026-06-07
  status: OPEN              # OPEN | DONE | ANSWERED | COLLAPSED | SUPERSEDED-BY:{id}
  links: [ATM-013811]       # related atoms; liberal linking
  tags: [chezmoi, destructive-ops]

Rules:

• Mint IDs from the registry's own counter surface — read it, claim the range, write back; never guess the next ID.
• raw is mandatory: the verbatim or span-referenced source. Formalization without provenance is paraphrase, not extraction.
• One intent per atom. If the text field needs "and", split it.

4. Elevate (when warranted)

For laws/values/constraints that recur across ≥2 independent sources:

• Strip incident detail ("in the limen repo" → gone, unless scope-bound).
• Link the supporting atoms as evidence.
• Mark state: ELEVATED and route to the appropriate standing surface (constitution tier, reliquary, registry) by pointer — the atom stays in the registry; the surface cites it.

5. Append and report

• Append atoms to the registry surface (append-only; existing atoms are never edited by an extraction pass — supersession is a new atom with SUPERSEDED-BY back-link).
• Emit the provenance map and counts: atoms by class, by state, plus the segments deliberately not atomized (conversational filler) so reviewers can audit the discard decisions.

Anti-patterns

• Atomizing the assistant's restatement instead of the operator's words. Extract from source turns only.
• Editing RAW. The verbatim layer is evidence; all normalization happens in CLEANED.
• Minting IDs by pattern-matching the last seen ID. Registry counters exist precisely because parallel sessions race; read-claim-write.
• Eliding the boring atoms. Constraints embedded in rants ("never do X again") are the highest-value extractions and the most commonly skipped.
• Elevating from a single occurrence. One strong statement is a CLEANED constraint; elevation requires recurrence.