# Openai Acset > OpenAI's ChatGPT export has a **tree-structured mapping** where messages form a DAG via `parent`/`children` relationships. The compositional ACSet anticipates this structure. - Skill: `plurigrid/openai-acset` (Agent Skill, multi-file: 4 files) - Install (CLI): `npx skillmds@latest add plurigrid/openai-acset` - Raw SKILL.md: https://api.skillmd.com/api/skills/plurigrid/openai-acset/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Coding & Dev Tools - Author: plurigrid (https://skillmd.com/u/plurigrid) - Updated: 2026-09-17 - Page: https://skillmd.com/skills/plurigrid/openai-acset --- # openai-acset > Compositional ACSet schema for OpenAI ChatGPT export traversal **Version**: 1.0.0 **Trit**: 0 (ERGODIC - schema discovery coordinator) **Color**: #10B981 ## Anticipated Schema via Traversal OpenAI's ChatGPT export has a **tree-structured mapping** where messages form a DAG via `parent`/`children` relationships. The compositional ACSet anticipates this structure. ## Discovered Schema (via traversal parsing) ``` ┌─────────────────────────────────────────────────────────────────────────────┐ │ SchOpenAIExport │ ├─────────────────────────────────────────────────────────────────────────────┤ │ │ │ Conversation ◄─────────── conv_of ─────────── Node │ │ │ │ │ │ │ ├── message ──► Message │ │ │ │ │ │ │ │ ├── parent ───────┐│ │ │ │ │ ▲ ││ │ │ │ └── children[]────┘│ │ │ │ │ │ │ │ Message ────────────┘ │ │ │ │ │ │ │ ├── author ──► Author │ │ │ ├── content ─► Content │ │ │ └── metadata ► Metadata │ │ │ │ │ Content (polymorphic) │ │ ├── TextContent {parts: [str]} │ │ ├── CodeContent {text: str, language: str} │ │ ├── ImageContent {asset_pointer: str} │ │ ├── ToolResult {content_type: "execution_output"} │ │ └── UserContext {user_profile: str, user_instructions: str} │ │ │ │ Metadata (extensible) │ │ ├── model_slug, request_id, turn_exchange_id │ │ ├── citations[], content_references[] │ │ ├── attachments[], search_queries[] │ │ └── aggregate_result (for tool outputs) │ │ │ └─────────────────────────────────────────────────────────────────────────────┘ ``` ## Julia ACSet Definition ```julia using ACSets, Catlab @present SchOpenAIExport(FreeSchema) begin # Objects (Obs) Conversation::Ob Node::Ob # mapping entry (id → node) Message::Ob Author::Ob Content::Ob Attachment::Ob Citation::Ob SearchQuery::Ob # Morphisms (Homs) - tree structure conv_of::Hom(Node, Conversation) message_of::Hom(Node, Message) # Node.message (nullable) parent_of::Hom(Node, Node) # Node.parent (nullable, DAG) child_of::Hom(Node, Node) # Node.children[] (inverse) # Message structure author_of::Hom(Message, Author) content_of::Hom(Message, Content) attachment_of::Hom(Attachment, Message) citation_of::Hom(Citation, Message) query_of::Hom(SearchQuery, Message) # Attributes ID::AttrType Text::AttrType Role::AttrType Time::AttrType Status::AttrType ContentType::AttrType ModelSlug::AttrType # Conversation attrs title::Attr(Conversation, Text) conv_id::Attr(Conversation, ID) create_time::Attr(Conversation, Time) update_time::Attr(Conversation, Time) current_node::Attr(Conversation, ID) gizmo_id::Attr(Conversation, ID) # GPT custom # Node attrs node_id::Attr(Node, ID) # Message attrs msg_id::Attr(Message, ID) msg_status::Attr(Message, Status) end_turn::Attr(Message, Status) weight::Attr(Message, Time) # Float recipient::Attr(Message, Text) # Author attrs role::Attr(Author, Role) # user|assistant|system|tool name::Attr(Author, Text) # tool name if role=tool # Content attrs (polymorphic via content_type) content_type::Attr(Content, ContentType) parts::Attr(Content, Text) # JSON array as string text::Attr(Content, Text) # for code/tool output # Metadata as attrs on Message model_slug::Attr(Message, ModelSlug) request_id::Attr(Message, ID) turn_exchange_id::Attr(Message, ID) end @acset_type OpenAIExport(SchOpenAIExport, index=[:conv_of, :parent_of, :author_of, :role]) ``` ## Python py-acset Implementation ```python SCHEMA_OPENAI = { "objects": [ "Conversation", "Node", "Message", "Author", "Content", "Attachment", "Citation", "SearchQuery" ], "morphisms": { # Tree structure "conv_of": ("Node", "Conversation"), "message_of": ("Node", "Message"), "parent_of": ("Node", "Node"), # Message composition "author_of": ("Message", "Author"), "content_of": ("Message", "Content"), "attachment_of": ("Attachment", "Message"), "citation_of": ("Citation", "Message"), "query_of": ("SearchQuery", "Message"), }, "attributes": { "Conversation": ["title", "conv_id", "create_time", "update_time", "current_node", "gizmo_id"], "Node": ["node_id"], "Message": ["msg_id", "status", "end_turn", "weight", "recipient", "model_slug", "request_id"], "Author": ["role", "name"], "Content": ["content_type", "parts", "text"], "Attachment": ["file_id", "file_name", "file_type"], "Citation": ["url", "title", "snippet"], "SearchQuery": ["query"], } } ``` ## Specter-Style Navigation Paths ```julia # Traverse from Conversation to all Messages all_messages(acset, conv_id) = begin nodes = incident(acset, conv_id, :conv_of) [acset[n, :message_of] for n in nodes if acset[n, :message_of] !== nothing] end # Thread reconstruction: walk parent chain function thread_path(acset, node_id) path = [node_id] while true parent = acset[node_id, :parent_of] parent === nothing && break pushfirst!(path, parent) node_id = parent end path end # All messages by role (user/assistant/tool) by_role(acset, r) = begin authors = findall(==(r), acset[:role]) [m for m in parts(acset, :Message) if acset[m, :author_of] ∈ authors] end # Tool invocations tool_calls(acset) = by_role(acset, "tool") # Search through content search_content(acset, pattern) = begin matches = [] for m in parts(acset, :Message) c = acset[m, :content_of] text = acset[c, :parts] * acset[c, :text] occursin(pattern, text) && push!(matches, m) end matches end ``` ## Compositional Decomposition The OpenAI export decomposes into **three compositional layers**: ### Layer 1: Conversation Graph (DAG) ``` Node ──parent_of──► Node │ └──children[]──► Node[] ``` ### Layer 2: Message Content (Product) ``` Message = Author × Content × Metadata ``` ### Layer 3: Polymorphic Content (Coproduct) ``` Content = TextContent + CodeContent + ImageContent + ToolResult + UserContext ``` ## Comparison: OpenAI vs Anthropic vs Amp | Dimension | OpenAI Export | Anthropic Claude | Amp Threads | |-----------|---------------|------------------|-------------| | **Structure** | Tree (DAG) | Linear | Linear | | **Parent ref** | `parent: uuid` | Implicit | Implicit | | **Branching** | `children: []` | None | None | | **Tools** | `author.role=tool` | `tool_use` block | Tool blocks | | **Attachments** | `metadata.attachments` | Inline | Inline | | **Models** | `model_slug` | `model` | Model ID | ## Package Dependencies Discovery From traversal, the export references: | Package | Evidence | Morphism | |---------|----------|----------| | **geb** | `model_slug: "gpt-4"` context | Content → Anoma | | **catlab** | Discussion content | Content → AlgebraicJulia | | **nats** | Search queries | SearchQuery → Messaging | | **emacs** | Tool outputs | Content → Editor | | **agda** | HoTT discussions | Content → TypeTheory | ## Usage ```bash # Extract with package filtering python3 -c " from openai_acset import build_openai_acset, filter_by_package acset = build_openai_acset('conversations.json') geb_convos = filter_by_package(acset, 'geb') print(f'GEB conversations: {len(geb_convos)}') " ``` ## Files | File | Purpose | |------|---------| | `openai_acset.py` | Full Python implementation | | `openai_schema.jl` | Julia ACSet schema | | `traverse_parser.py` | Schema discovery via traversal | Base directory: file:///Users/bob/.claude/skills/openai-acset --- ## End-of-Skill Interface ## GF(3) Triads ``` three-match (-1) ⊗ openai-acset (0) ⊗ gay-mcp (+1) = 0 ✓ [Export coloring] lispsyntax-acset (-1) ⊗ openai-acset (0) ⊗ specter-acset (+1) = 0 ✓ [Navigation] temporal-coalgebra (-1) ⊗ openai-acset (0) ⊗ duckdb-timetravel (+1) = 0 ✓ [Versioning] ``` ## Related Skills - `chatgpt-export-acset` - Simpler extraction - `acsets-algebraic-databases` - Core ACSet theory - `specter-acset` - Bidirectional navigation - `compositional-acset-comparison` - Schema comparison (DuckDB/LanceDB) - `lispsyntax-acset` - Sexp bridge --- ## Autopoietic Marginalia > **The interaction IS the skill improving itself.** Every use of this skill is an opportunity for worlding: - **MEMORY** (-1): Record what was learned - **REMEMBERING** (0): Connect patterns to other skills - **WORLDING** (+1): Evolve the skill based on use *Add Interaction Exemplars here as the skill is used.*