Codex Session Manager logo

Codex Session Manager

Community
sugarforever
codex-session-manager

Manage local Codex session transcripts, including listing candidate sessions, exporting full or selected sessions to organized Markdown, inspecting archived sessions, and summarizing tool-call history. Use when the user asks to scan, parse, archive, inspect, recover, summarize, manage, or convert Codex sessions, `~/.codex/sessions` data, `~/.codex/archived_sessions` data, `.jsonl` transcripts, tool-call history, or hard-to-read Codex conversation logs.

Overview

Publishersugarforever
Repository01coder-agent-skills
Skill namecodex-session-manager
Stars
139
Forks
37
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by sugarforever on GitHub. Read the source before you install it.

Installation

Install the Codex Session Manager AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/sugarforever/01coder-agent-skills/tree/main/skills/codex-session-manager
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/sugarforever/01coder-agent-skills.git /tmp/01coder-agent-skills
mkdir -p .claude/skills
cp -r /tmp/01coder-agent-skills/skills/codex-session-manager .claude/skills/codex-session-manager
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Codex Session Manager in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Codex Session Manager on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Codex Session Manager is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Codex Session Manager

Overview

Codex stores session transcripts as JSONL files under ~/.codex/sessions/YYYY/MM/DD/*.jsonl. Archived sessions may also exist under ~/.codex/archived_sessions/*.jsonl. Use the bundled manager to list candidates or export sessions into Markdown transcripts with a digest, timeline, message text, and linked tool-call details.

Default output folder: ~/.codex/session-markdown. Tell the user before exporting there, and mention any custom output folder they requested.

Quick Start

Let the user's wording choose the mode when it is clear; otherwise ask them to choose before exporting:

  • Full mode: export all matching sessions. Use this for archive, backup, broad search, or "convert all sessions" requests.
  • Specific mode: list candidate sessions first, ask the user to pick one, then export only that session.

Run from any directory:

bash
python3 /path/to/codex-session-manager/scripts/manage_codex_sessions.py

Useful options:

  • --mode full: export all matching sessions. This is the default.
  • --mode specific --list-candidates: print a numbered candidate table and do not export.
  • --mode specific --pick N: export the Nth candidate from the same filtered candidate list.
  • --include-archived: also scan ~/.codex/archived_sessions.
  • --project <text>: only export date/project keys containing this text.
  • --session <text>: only export sessions whose id or filename contains this text.
  • --since YYYY-MM-DD: only export sessions modified on or after this date.
  • --limit N: export the N most recently modified matching sessions.
  • --include-tool-details-inline: embed full tool payloads in the main session Markdown instead of sidecar files.

Specific Mode Candidate Flow

Use this flow when the user wants one Codex session, is unsure which session they need, or asks to inspect recent sessions before converting.

  1. Run a candidate list command. Use --limit 20 by default unless the user asks for a different count.
bash
python3 /path/to/codex-session-manager/scripts/manage_codex_sessions.py \
  --mode specific \
  --list-candidates \
  --limit 20
  1. If the user gave a date, session id fragment, or archive hint, pass it through the same filters:
bash
python3 /path/to/codex-session-manager/scripts/manage_codex_sessions.py \
  --mode specific \
  --list-candidates \
  --since 2026-06-01 \
  --include-archived \
  --limit 20
  1. Present the numbered candidate rows to the user. The candidate table includes modified time, date/project key, short session id, cwd, and first user prompt excerpt.
  2. After the user chooses a number, rerun with the exact same filters and --pick N.

If the user already gives an exact session id or unique fragment, use --mode specific --session <id-or-fragment> --list-candidates first when there is any ambiguity. Export with --pick 1 only when the candidate list has exactly one match.

Output Layout

The exporter writes:

text
~/.codex/session-markdown/
├── index.md
└── <date-or-archive-key>/
    ├── index.md
    ├── <session-id>.md
    └── tool-details/
        └── <session-id>.tools.md

Each session Markdown includes:

  • Digest: source path, key, session id, cwd, timestamps, event/message/tool counts, and first user prompt excerpt.
  • Linked tool details file when tool calls or results exist.
  • Timeline: session metadata, user/assistant/developer messages, reasoning summaries, tool calls, and tool outputs.
  • Short tool summaries inline, with full JSON payloads in the sidecar file by default.

Workflow

  1. Confirm the source folder. Default to ~/.codex/sessions; add --include-archived when the user asks about archived sessions.
  2. Ask the user to choose full mode or specific mode if they did not already make the choice.
  3. Confirm or announce the output folder. Default to ~/.codex/session-markdown.
  4. For full mode, run the manager script with any needed filters.
  5. For specific mode, list candidates, get the user's chosen number, then export with --pick.
  6. Report the number of sessions exported, output index path, and any parse warnings.

Notes

  • Treat transcript data as private. It can contain prompts, file contents, command output, secrets accidentally pasted into chat, and tool results.
  • Do not delete or modify original .jsonl files.
  • Prefer sidecar tool details for large sessions. Inline tool payloads can make Markdown hard to search and load.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Codex Session Manager AI skill do?

Manage local Codex session transcripts, including listing candidate sessions, exporting full or selected sessions to organized Markdown, inspecting archived sessions, and summarizing tool-call history. Use when the user asks to scan, parse, archive, inspect, recover, summarize, manage, or convert Codex sessions, `~/.codex/sessions` data, `~/.codex/archived_sessions` data, `.jsonl` transcripts, tool-call history, or hard-to-read Codex conversation logs.

Why use Codex Session Manager on TypingMind?

Because you install it once and use it with any model. Codex Session Manager is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Codex Session Manager in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/sugarforever/01coder-agent-skills/tree/main/skills/codex-session-manager. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Codex Session Manager?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Codex Session Manager?

As many as you like. As long as a model supports skills, you can use Codex Session Manager with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Codex Session Manager AI skill free?

Yes. It is published on GitHub by sugarforever under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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