prompt-atom-formalization

Scan rough markdown, session exports, or pasted prose and isolate each core intent into a structured prompt atom — classified as law, value, directive, constraint, question, or branch-vector — then rewrite it into machine-readable YAML frontmatter per the RAW → CLEANED/FORMALIZED → ELEVATED doctrine. Triggers on "prompt atom extraction pass", "atomize this", "formalize these prompts", or converting loose operator text into registry-grade atoms.

Best use case

prompt-atom-formalization is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Scan rough markdown, session exports, or pasted prose and isolate each core intent into a structured prompt atom — classified as law, value, directive, constraint, question, or branch-vector — then rewrite it into machine-readable YAML frontmatter per the RAW → CLEANED/FORMALIZED → ELEVATED doctrine. Triggers on "prompt atom extraction pass", "atomize this", "formalize these prompts", or converting loose operator text into registry-grade atoms.

Teams using prompt-atom-formalization should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/prompt-atom-formalization/SKILL.md --create-dirs "https://raw.githubusercontent.com/organvm-iv-taxis/a-i--skills/main/distributions/claude/skills/prompt-atom-formalization/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/prompt-atom-formalization/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How prompt-atom-formalization Compares

Feature / Agentprompt-atom-formalizationStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Scan rough markdown, session exports, or pasted prose and isolate each core intent into a structured prompt atom — classified as law, value, directive, constraint, question, or branch-vector — then rewrite it into machine-readable YAML frontmatter per the RAW → CLEANED/FORMALIZED → ELEVATED doctrine. Triggers on "prompt atom extraction pass", "atomize this", "formalize these prompts", or converting loose operator text into registry-grade atoms.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

SKILL.md Source

# 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

| Class | Nature | Lifetime | Example |
|-------|--------|----------|---------|
| **law** | standing rule; governs all future behavior | permanent until amended | "nothing local-only — every artifact git-tracked AND pushed" |
| **value** | weighting/preference; shapes choices without mandating one | durable | "prefer user coinages over standard vocabulary" |
| **directive** | one concrete executable action | until DONE | "register the 5 bench agents in fleet.yaml" |
| **constraint** | boundary on how any action may be done | scoped or permanent | "never chezmoi add over existing source without diffing" |
| **question** | open decision owned by a human | until answered | "GCP_SA_KEY provisioning — enable CI deploys?" |
| **branch-vector** | a fork in possible futures; options held in superposition | until collapsed | "skills live in domus OR a-i--skills — decide before next install" |

## 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

```yaml
- 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.

Related Skills

skill-chain-prompts

5
from organvm-iv-taxis/a-i--skills

Orchestrate multi-skill workflows with prompt-based skill chaining. Define sequential or parallel skill invocations using YAML chain definitions, track progress through chains, and use pre-built chains for development, documentation, and career workflows. Use when coordinating multiple skills for complex tasks.

prompt-engineering-patterns

5
from organvm-iv-taxis/a-i--skills

Design effective prompts for LLM agents with structured input/output formats, chain-of-thought reasoning, few-shot examples, and system prompt architecture. Covers Claude-specific patterns and multi-turn conversation design. Triggers on prompt design, LLM interaction patterns, or system prompt architecture requests.

taxonomy-modeling-design

5
from organvm-iv-taxis/a-i--skills

Phase 2 of the pentaphase structural-overhaul protocol. Classifies entities, standardizes attributes, establishes relationships, and designs the access framework. Use when the user invokes phase 2 of an overhaul, asks to "design the taxonomy" or "model the structure", or has completed a landscape audit and is ready to redesign. Consumes phase-1-landscape-report.md; produces phase-2-taxonomy-model.md.

systemic-ingestion-normalization

5
from organvm-iv-taxis/a-i--skills

Phase 4 of the pentaphase structural-overhaul protocol. Purges redundancies, enriches and aligns legacy entities to the new schema, executes phased ingestion into the new environment, and audits integrity. Use when the user invokes phase 4 of an overhaul, asks to "migrate the data" or "ingest into the new system", or has a configured environment ready to accept legacy entities. Consumes phase-3-environment-spec.md; produces phase-4-ingestion-report.md.

system-environment-configuration

5
from organvm-iv-taxis/a-i--skills

Phase 3 of the pentaphase structural-overhaul protocol. Translates the taxonomy model into objective technical criteria, evaluates candidate mechanisms or frameworks, instantiates the chosen architecture, and programs validation rules. Use when the user invokes phase 3 of an overhaul, asks to "select a system" or "configure the environment", or has a taxonomy model and is ready to choose technology. Consumes phase-2-taxonomy-model.md; produces phase-3-environment-spec.md.

pentaphase-orchestrator

5
from organvm-iv-taxis/a-i--skills

Threads the full five-phase structural-overhaul protocol — landscape discovery, taxonomy design, environment configuration, systemic ingestion, governance evolution — for any substrate the user names. Use when the user requests a structural overhaul, system redesign, or end-to-end restructuring of a documentation system, asset registry, code monorepo, knowledge base, or operational workflow; or when they explicitly invoke the pentaphase methodology. Coordinates handoffs between phase-skills and seats validation gates between phases.

landscape-discovery-audit

5
from organvm-iv-taxis/a-i--skills

Phase 1 of the pentaphase structural-overhaul protocol. Inventories assets, maps current flow, identifies friction, and defines value metrics for any substrate. Use when the user invokes phase 1 of an overhaul, requests a baseline audit, asks to "discover the landscape" of a system, or wants to understand current state before redesigning. Produces phase-1-landscape-report.md.

governance-evolution-protocol

5
from organvm-iv-taxis/a-i--skills

Phase 5 of the pentaphase structural-overhaul protocol. Codifies operational protocols, onboards the ecosystem of participants, programs behavior monitoring, and establishes an iteration cadence so the substrate evolves rather than calcifies. Use when the user invokes phase 5 of an overhaul, asks to "establish governance" or "lock in the protocols", or has completed ingestion and is ready to declare the substrate operational. Consumes phase-4-ingestion-report.md; produces phase-5-governance-charter.md, which closes the protocol.

dimension-surfacing

5
from organvm-iv-taxis/a-i--skills

Surfaces the parallel domain dimensions implicit in a dense or minimal prompt. Use when a user prompt is small on the surface but plainly implies multiple independent domains needing different expertise; when explicitly invoked by the coliseum-orchestrator skill as Phase 1; or when the user asks "what dimensions does this prompt encode" or "what axes does this break into." Produces a named dimension set where each dimension is independently executable and not a paraphrase of another.

coliseum-dispatch

5
from organvm-iv-taxis/a-i--skills

Dispatches a composed set of assignment envelopes to domain-expert subagents in parallel, in a single message with multiple Agent tool calls. Enforces the no-pingpong gate via the pingpong-detector agent before any dispatch fires. Use when invoked by the coliseum-orchestrator as Phase 3; when envelopes are already composed and the next step is parallel execution; or when the user asks to "fan out" or "dispatch in parallel." Produces a dispatch log capturing what was sent, when, and where returns land.

assignment-composition

5
from organvm-iv-taxis/a-i--skills

Wraps each surfaced dimension as a self-contained 9-section autonomous-work-assignment envelope — scope, context, success criteria, allowed tools, return format, handoff — all the recipient subagent needs to execute without coming back. Use when invoked by coliseum-orchestrator as Phase 2; when dimensions are named and the next step is to make each independently dispatchable; or when the user asks "compose this as an assignment." The no-pingpong gate validates each envelope before dispatch.

workspace-autopsy-governance

5
from organvm-iv-taxis/a-i--skills

Conducts a full automated autopsy of the current workspace directory to map files, identifies structural issues, proposes a restructuring plan (the signal), and establishes unified governance using templates. Use this skill when a user asks to map, restructure, reorganize, or apply new governance to an existing messy repository.