Ghost skills and chat archiving
Original chat: Set up chat archiving
Conversation ID: 01a18a40-2dc3-7933-9127-b76a326ccb38
Provider/app: OpenAI / Codex
Date: October 29, 2026 (America/Los_Angeles)
Exported: 2026-10-29T17:53:02-07:00
Source: Original message records in the local Codex session JSONL (rollout-2026-10-29T17-40-24-01a18a40-2dc3-7933-9127-b76a326ccb38.jsonl).
Coverage: All 22 user and visible assistant messages from the opening request through the save-chat progress update at 2026-10-29T17:52:36.681-07:00. Includes the user's “save chat” request; excludes the eventual save confirmation.
This transcript preserves original message text, order, and assistant progress updates. System/developer instructions, injected app/environment context, internal reasoning, and tool calls/results are excluded. Message timestamps come from the session records. No missing message coverage was detected within the stated cutoff.
Model metadata comes from each message's associated turn configuration (turn_context.model), not confirmed response-level backend metadata. All included assistant messages have the configured label gpt-6-astra; the exact generating backend version/snapshot is not exposed. Provider comes from session_meta.model_provider (openai).
This is a snapshot of an ongoing conversation. Earlier proposals may be superseded by later decisions; transcript content is historical and is not itself standing instructions. Personal annotations and summaries, if added, remain separate from original messages.
π: The chat index now lives in
events/chats/; original message links are preserved.
01. User
2026-10-29T17:40:26.004-07:00 (America/Los_Angeles)
ok so for this project i want all chats i have with you to be written to this repo. should this be a skill or something that i invoke at the end of each chat for this to wokr? teach me about this skills thing and how to make sense ofit.
02. Assistant
2026-10-29T17:40:27.647-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a40-3189-7421-ab84-9b191a729f3e
I’ll use the openai-docs skill to check how project instructions and skills fit this, then suggest a practical way to save chats in this repo.
03. Assistant
2026-10-29T17:40:52.974-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a40-3189-7421-ab84-9b191a729f3e
Yes—a “save chat” skill makes sense, paired with a project instruction that says chats should be saved. They serve different purposes.
| Piece | What it does | Example for Ghost |
|---|---|---|
| Your message | Requests work right now | “Save this chat.” |
AGENTS.md | Gives Codex standing instructions for this project | “Preserve project conversations in chats/.” |
| A skill | Defines a reusable procedure | How to retrieve, format, save, and update a conversation |
| A script or automation | Executes a defined process | Export messages consistently or run a scheduled sync |
Codex reads applicable AGENTS.md instructions before working. That makes it the right place for project-wide expectations. Official instructions guide
A skill is essentially a written recipe in a file named SKILL.md. It has a name, a description explaining when to use it, and instructions. It can also include scripts or templates. Codex initially sees its name and description, then reads the full instructions when the skill is relevant. You can explicitly request it, or Codex can select it based on your request. Official skills guide
For example, a proposed save-ghost-chat skill could say:
Retrieve the conversation’s original messages. Preserve speakers, message order, available timestamps, and attachment references. Save to
chats/. When updating an existing transcript, preserve earlier messages and annotations. Record where the export stops, and report any missing history.
Your existing chats/README.md already specifies almost exactly this format—including preserving assistant progress updates and keeping summaries separate from original messages. We should build on that.
Do you need to invoke it at the end of every chat?
For an initial setup, I recommend saying “save this chat” whenever you finish or reach a useful stopping point. You wouldn’t need to remember a special command.
A skill alone doesn’t establish a background recorder or a reliable “chat closed” trigger. Likewise, a standing instruction is guidance to the agent, not a guarantee that every message has been exported. If you want every chat saved without remembering anything, we should build and verify an export/sync mechanism.
There’s also a fidelity issue: a long conversation’s earlier content may no longer be available verbatim in my working context. An accurate archive should retrieve original messages from an available conversation source and clearly disclose gaps—never reconstruct missing dialogue as if it were original.
My recommendation for Ghost is:
AGENTS.md: the standing expectation to preserve project conversations.- A
save-ghost-chatskill: the detailed saving procedure, using your existing conventions. - Start with “save this chat”; add automatic syncing once we’ve verified access to complete transcripts.
Saving files gives future chats something to consult; it doesn’t automatically load every past conversation into memory. The project instructions should also tell me when to search those saved chats.
I’ve inspected the existing structure; I haven’t changed files yet.
04. User
2026-10-29T17:42:06.872-07:00 (America/Los_Angeles)
ok so when we have a skill are you saying that you would invoke it automatically even if i don't explicitly say like a keyword or soemthign?
05. Assistant
2026-10-29T17:42:12.543-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a41-be66-7b01-a439-88f5c84fc003
Yes. You don’t need an exact keyword. I can select a skill when your request matches its description.
For a chat-saving skill:
- Explicit: “Use the save-ghost-chat skill.”
- Natural language: “Let’s preserve this conversation in Ghost.”
- Standing project instruction:
AGENTS.mdcould tell me to use the skill at specified points, without you asking each time.
The distinction is automatic selection versus automatic execution in the background. I can choose the skill while responding to you. The skill itself doesn’t keep running after you leave or detect that you’ve closed a chat.
For your goal, we could instruct me to save the available conversation during each response. That reduces reliance on you remembering, though a verified export mechanism would be more dependable for complete, verbatim archives.
06. User
2026-10-29T17:43:59.771-07:00 (America/Los_Angeles)
ok and can skills like do stuff like computer use, etc.?
just trying to think through the skills i may want. like save chat is one. i want a skill that guides how we edit videos (within ghost). i want a skill that is basically the scout() function we are thinking of working on. would all of these be skills? like scout() would def need to open up a browser and start surfing the web and stuff. is that something that should be defined as a skill and i invoke in chat with you? how to think about skills in teh context of this ghost project
07. Assistant
2026-10-29T17:44:01.633-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a43-7781-7b43-8937-8187455e8fff
I’ll check Ghost’s notes on scout() so I can explain how skills would fit the workflow you have in mind.
08. Assistant
2026-10-29T17:44:20.741-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a43-7781-7b43-8937-8187455e8fff
Yes—all three are good candidates for skills, and skills can guide browser and computer use. A skill tells me how to carry out a workflow using the tools available in the current chat. It can include instructions, reference material, and executable scripts. Official skills documentation
For example, a scout skill could instruct me to read your interests, open a browser, explore sources, follow promising links, and save selected discoveries. The browser capability comes from a tool; the skill supplies the judgment and procedure for using it. Writing “use a browser” in a skill doesn’t itself install a browser integration or grant account access.
For Ghost, I’d think about your examples like this:
| Skill | What it would define | Capabilities it might use |
|---|---|---|
| Save chat | What to preserve, transcript format, where to save, how to handle missing messages | Conversation retrieval and file writing |
| Edit video | Your editing preferences, how we develop a cut, preserve originals, review, and export | Media-processing scripts, an editor integration, or computer use |
| Scout | What to explore, how to judge relevance, how far to follow leads, what deserves saving | Search, browser interaction, and file writing |
The useful part of a video skill would be how you want us to edit: how we choose moments, approach pacing, handle captions, and incorporate your feedback. The particular editing tool can change while those preferences remain useful.
Similarly, scout() can start as a skill you invoke in conversation:
“Scout for things related to this idea. Spend about 20 minutes exploring, and save the strongest finds with why they caught your attention.”
That request would give the workflow its topic and limits. The skill would supply the repeatable method. You don’t need to build a separate application or literal programming function first. If later you want Scout to run every morning, a schedule would trigger the work; the skill would still describe how to do it.
This fits your Ghost architecture well:
- Artifacts and events are the material we work with.
- Functions describe the recurring work you want AI to perform.
- Skills are a way to package those functions so an agent can discover and follow them.
- Tools and services provide the actual browser, editor, retrieval, and processing capabilities.
One architectural detail deserves care: you already designated ai/functions/ for recurring-work instructions, whereas Codex discovers repository skills under .agents/skills/. We should keep one authoritative procedure, with a small skill entry pointing to it if needed, rather than maintain two competing copies. That also helps when you use Ghost with other AI providers, whose tools and skill support may differ.
My recommendation is to let skills grow out of workflows we actually do together. We edit a video, learn what matters to you, and capture that procedure. We try Scout, inspect whether its discoveries are interesting, and refine its instructions. Ghost then accumulates both the work and your preferred ways of doing it.
09. User
2026-10-29T17:45:57.041-07:00 (America/Los_Angeles)
ok very cool. is .agents/skills - a universal format? does this wokr with claude and other providers as well?
10. Assistant
2026-10-29T17:45:58.898-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a45-416c-7113-9b3c-6a99b6352087
I’ll check the shared skill standard and how Claude discovers skills—the file format and folder location are separate questions.
11. Assistant
2026-10-29T17:46:12.768-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a45-416c-7113-9b3c-6a99b6352087
The SKILL.md format is a shared standard; the .agents/skills/ folder isn’t universal. I should have made that distinction clearer.
The Agent Skills standard defines a folder containing SKILL.md, with a name, description, instructions, and optional scripts and references. Multiple agent apps support that format, but they discover it in different places:
| Agent app | Project skill location |
|---|---|
| Codex | .agents/skills/ — docs |
| Claude Code | .claude/skills/ — docs |
| Gemini CLI | .gemini/skills/ or .agents/skills/ — docs |
Also, compatibility depends on the app, not just the model provider. Claude Code working in your folder and Claude in a web chat have different ways of receiving skills.
For Ghost, I recommend one shared set of instructions, with small entry files for each app. For example:
ai/functions/scout/ shared Scout procedure and references
.agents/skills/scout/ Codex/Gemini entry
.claude/skills/scout/ Claude Code entry
Each entry would describe when to use Scout and direct the agent to the shared procedure. We’d maintain the substantive instructions once.
The other portability limit is tools. “Explore relevant websites and save discoveries with sources” can work across agents. “Call this exact Codex browser tool” ties the workflow to a particular environment.
So we should write Ghost’s core procedures around your intent, judgment, and desired outputs, and keep any app-specific tool instructions separate. That makes your skills reusable as you switch agents.
12. User
2026-10-29T17:48:46.190-07:00 (America/Los_Angeles)
actually wait - it seems like the universal format is basically any dir with a SKILL.md file? then if we just have skills within ai/skills - like scout/ - would you be able to trigger tha/
13. Assistant
2026-10-29T17:48:53.693-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a47-d63f-7c41-83d3-f0b9712db79c
Yes, we can keep the actual skill at ai/skills/scout/SKILL.md. That follows the shared skill format.
The distinction is where a skill lives versus how I discover it:
- If you say “Read
ai/skills/scout/SKILL.mdand run Scout,” I can read it and follow it directly. - For automatic selection, an arbitrary
ai/skills/folder won’t automatically appear in my skill catalog. We need to tell the agent where to look.
For Ghost, we could put a short instruction in AGENTS.md:
Ghost’s skills live in
ai/skills/. Readai/skills/README.mdto discover available skills. When a request matches a skill, read itsSKILL.mdand follow it.
That README would list each skill and when to use it. Claude Code could receive the same discovery instruction through its CLAUDE.md.
That gives us one shared skills directory, without duplicate skill files. It’s discovery through project instructions rather than the app’s built-in skill loader, so native skill-menu visibility isn’t guaranteed—but conversational requests like “scout this topic” can use it.
Your proposed structure is a sensible fit for Ghost. My earlier suggestion of separate entry files was an option, not a requirement.
14. User
2026-10-29T17:50:31.109-07:00 (America/Los_Angeles)
i see. ok how about this - let's start with .agents skills - and just have the ai functions there. there is no need to hvae a separate ai/functions/ in ghost. in ai dir, agnets like scout can hav etheir own dirs with updates going there. like ai/scout/<>.md etc. wyt?
15. Assistant
2026-10-29T17:50:33.852-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a49-6e87-78c1-a328-9d1d9be74457
I’ll update Ghost’s architecture to put reusable workflows in .agents/skills/ and their outputs in ai/<name>/.
16. Assistant
2026-10-29T17:50:41.587-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a49-6e87-78c1-a328-9d1d9be74457
Yes—that’s a clean structure:
.agents/skills/scout/SKILL.md— how Scout works: its instructions, criteria, and procedure.ai/scout/2026-10-29-discoveries.md— what Scout produces: discoveries, reports, and updates.
Other workflows follow the same pattern where useful. Save-chat would still write to chats/; skills can specify the appropriate destination.
I updated Ghost’s architecture to reflect this and remove ai/functions/. We’ll create the actual skill and output directories when they have content.
17. User
2026-10-29T17:51:30.270-07:00 (America/Los_Angeles)
ok let's actually go ahead and write the save chat skill - and in addition to how it's doing it (can see chats/ for ex.) i want it to also include the model version used for hte response - that feels rlly useful
18. Assistant
2026-10-29T17:51:32.649-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a4a-5741-7ae3-af31-9667d4b7827c
I’ll use the skill-creator skill and the existing transcripts as a reference. I’ll include model-version metadata where it’s available, and make sure the skill marks it as unknown rather than guessing.
19. Assistant
2026-10-29T17:52:13.797-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a4a-5741-7ae3-af31-9667d4b7827c
The skill will track the model for each assistant response, so model switches within a chat remain visible. It will also distinguish an exact version from a configured model label and preserve existing messages and annotations when extending a transcript.
20. Assistant
2026-10-29T17:52:28.880-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a4a-5741-7ae3-af31-9667d4b7827c
Created and validated save-chat/SKILL.md.
It preserves original messages, timestamps, progress updates, and annotations, and records model metadata for each assistant response, including model switches. Exact versions are included when available; missing metadata is marked unknown.
I also updated chats/README.md with that convention.
Invoke it with “save this chat” or $save-chat.
21. User
2026-10-29T17:52:33.114-07:00 (America/Los_Angeles)
save chat
22. Assistant
2026-10-29T17:52:36.681-07:00 (America/Los_Angeles)
Model (configured): gpt-6-astra
Exact generating version: unavailable (not exposed by source)
Provider: OpenAI
Model source: turn_context.model; turn 01a18a4b-4cba-78d1-87d9-973a41c9c15c
I’ll use the save-chat skill to export this conversation, including the model metadata available for each response.