Codex Chatgpt Bridge
Zhenyu98/codex-chatgpt-bridge
A skill your agent uses when Codex needs to coordinate ChatGPT, Chrome, Cloudflare tunnels, verified bridge Restart/Reboot recovery, or task routing between local code execution and ChatGPT…
Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
Install Memory Management
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install ThinkInAIXYZ/deepchat memory-management --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .claude/skills && cp -r skills-src/resources/skills/memory-management .claude/skills/memory-management && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .claude/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-managementType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install ThinkInAIXYZ/deepchat memory-management --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .agents/skills && cp -r skills-src/resources/skills/memory-management .agents/skills/memory-management && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .agents/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install ThinkInAIXYZ/deepchat memory-management --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/resources/skills/memory-management .cursor/skills/memory-management && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .cursor/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/ThinkInAIXYZ/deepchat.git --path resources/skills/memory-management--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install ThinkInAIXYZ/deepchat memory-management --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/resources/skills/memory-management .gemini/skills/memory-management && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .gemini/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install ThinkInAIXYZ/deepchat memory-managementInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .github/skills && cp -r skills-src/resources/skills/memory-management .github/skills/memory-management && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .github/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install ThinkInAIXYZ/deepchat memory-management --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/ThinkInAIXYZ/deepchat.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/resources/skills/memory-management .opencode/skills/memory-management && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "memory-management" agent skill from https://github.com/ThinkInAIXYZ/deepchat/tree/dev/resources/skills/memory-management into .opencode/skills/memory-management/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memory-management", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
memory-management- GitHub stars
- 6.4k
- Token cost
- ~849 tokens
- SKILL.md length
- 460 words
- Files
- 1
- Skills in repo
- 15
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
- Works in 6 steps: Did the user reveal a stable preference… → Did you learn a durable project fact? → Is there a task outcome, blocker, or… → …
- Tasks that involve Scheduled and recurring tasks
- SKILL.md covers Recall, Remember, Verbatim Scope and Procedures -> Skill, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Memory Management is an agent skill from ThinkInAIXYZ/deepchat. Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
Its SKILL.md is about 850 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Productivity & Automation, covering Scheduled and recurring tasks. It works with OpenAI. The repository describes itself as: 🐬DeepChat - A smart assistant that connects powerful AI to your personal world. The licence is Apache-2.0.
When your agent uses it
- Tasks that involve Scheduled and recurring tasks
Example prompts
- “/memory-management”
Workflow steps
6 steps, taken from the first numbered list in SKILL.md.
- Did the user reveal a stable preference or constraint?
- Did you learn a durable project fact?
- Is there a task outcome, blocker, or explicit deferral worth preserving?
- Did a reusable heuristic work?
- Did an anti-pattern or stale assumption become clear?
- Is this actually a reusable procedure for skill_manage or a recurring need for Scheduled Tasks rather than Memory?
What it can do on your machine
Read from SKILL.md and the folder at commit 4eb6062. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Memory Management loads about 849 tokens when it runs. Until then it costs about 32 tokens; SKILL.md has 460 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from ThinkInAIXYZ/deepchat at commit 4eb6062, republished under its Apache-2.0 licence (© ThinkInAIXYZ). 460 words, ~849 tokens.
Download SKILL.mdSave it as
.claude/skills/memory-management/SKILL.md (or your agent's skills folder).- name
- memory-management
- description
- Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
Memory Management
Use this skill when a task may produce durable learning or when the user asks you to recall, remember, continue earlier work, preserve an exact statement, capture a reusable procedure, or handle a recurring need.
Recall
Rely on automatic memory injection for ordinary context. Use memory_recall when the user refers to previous work with cues such as again, last time, before, continue, same project, remember, or asks what you already know.
Use tape_search and then tape_context when the user needs source evidence, exact wording, logs, command output, file snippets, or why a prior decision was made. Memory is a durable conclusion layer, not the raw transcript.
Remember
Use memory_remember only for durable conclusions that should change future behavior. Choose the most specific category:
user_preference: stable user preferences, constraints, communication style, environment choices.project_fact: durable project conventions, architecture entry points, commands, dependencies, paths, or operational constraints.task_outcome: completed, blocked, or deliberately deferred task results. Include status, outcome, and blocker in prose when relevant.heuristic: reusable troubleshooting strategy, workflow, decision rule, or engineering lesson.anti_pattern: repeated mistake, unsafe approach, brittle pattern, stale assumption, or thing to avoid.
Do not remember raw tool results, bash output, grep output, file contents, transient mechanics, one-off failures, secrets, credentials, hidden reasoning, or anything only useful for the current turn.
Verbatim Scope
Store exact wording only when the user explicitly asks you to remember a sentence or phrase verbatim. In that case, keep the requested text intact and make the surrounding content minimal.
Automatic extraction is different: it should normalize durable facts into concise memory content, deduplicate related entries, and avoid preserving raw transcript text.
Show full SKILL.md (190 more words)Show less
Procedures -> Skill
When the useful learning is a reusable multi-step procedure, prefer drafting a skill with skill_manage instead of stuffing the full procedure into Memory. Memory may keep a short pointer or heuristic, but the repeatable workflow belongs in a Skill.
Use skill_manage for draft skills only. Do not modify installed skills unless the user explicitly asks through the supported review flow.
Recurring -> Scheduled Task
When the user asks for a periodic, low-frequency, or future recurring action, suggest creating a Scheduled Task in settings. Memory does not wake the agent, schedule future work, or create automation side effects.
End-of-task Learning Check
Before finishing a non-trivial task, check whether there is one durable lesson to save:
- Did the user reveal a stable preference or constraint?
- Did you learn a durable project fact?
- Is there a task outcome, blocker, or explicit deferral worth preserving?
- Did a reusable heuristic work?
- Did an anti-pattern or stale assumption become clear?
- Is this actually a reusable procedure for
skill_manageor a recurring need for Scheduled Tasks rather than Memory?
Remember only the smallest durable conclusion. Leave raw process in Tape.
© ThinkInAIXYZ, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in resources/skills/memory-management of ThinkInAIXYZ/deepchat.
Open the folder on GitHubat commit 4eb6062
Compare with similar skills
Memory Management next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Memory Management this skillThinkInAIXYZ/deepchat | 6.4k | — | ~849 | Automated safety check: Pass | Apache-2.0 | |
| Codex Chatgpt BridgeZhenyu98/codex-chatgpt-bridge | 277 | — | ~4k | Automated safety check: Pass | MIT | |
| Daily Briefleiting-eric/DailyBrief | 364 | — | ~3k | Automated safety check: Notes | MIT | |
| Cronalytics8bit64k/cronalytics | 112 | — | ~4.7k | Automated safety check: Pass | MIT | |
| Scrapingbee CLIScrapingBee/scrapingbee-cli | 108 | — | ~3.2k | Automated safety check: Notes | MIT | |
| Chat Connectorsgarrytan/gbrain | 31k | — | ~2.8k | Automated safety check: Pass | MIT |
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Chat Connectors
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Connect a ChatGPT or Claude account and sync its conversation history into the brain automatically.
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Backend and infra for a project via Cohesivity (cohesivity.ai).
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Related
Works with
Categories
Questions about Memory Management
What does Memory Management do?
Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape. Memory Management is an agent skill from ThinkInAIXYZ/deepchat. Guide the agent to recall, remember, and route durable learning into Memory, Skills, Scheduled Tasks, or Tape.
When should I use Memory Management?
Memory Management fits situations like: tasks that involve Scheduled and recurring tasks.
How do I install Memory Management in Claude Code?
Run `npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a claude-code`. Or copy the skill folder (resources/skills/memory-management in ThinkInAIXYZ/deepchat) into .claude/skills/memory-management in your project. Claude Code loads it when a task matches its description.
How do I install Memory Management in Codex?
Run `npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a codex`. Or copy the skill folder (resources/skills/memory-management in ThinkInAIXYZ/deepchat) into .agents/skills/memory-management in your project. Codex loads it when a task matches its description.
Can I use Memory Management in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ThinkInAIXYZ/deepchat --skill memory-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory-management, .gemini/skills/memory-management, .github/skills/memory-management and .opencode/skills/memory-management in your project.
What does Memory Management need to run?
SKILL.md names no scripts, command-line tools or credentials: Memory Management is instructions for the agent only.
Does Memory Management access the network?
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Is Memory Management safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Memory Management use?
Memory Management is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Memory Management use?
About 849 tokens (SKILL.md is roughly 3.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to Memory Management?
Skills that share tags, products or a category with Memory Management: Codex Chatgpt Bridge (Zhenyu98/codex-chatgpt-bridge, 277 stars), Daily Brief (leiting-eric/DailyBrief, 364 stars), Cronalytics (8bit64k/cronalytics, 112 stars) and Scrapingbee CLI (ScrapingBee/scrapingbee-cli, 108 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Memory Management?
ThinkInAIXYZ (a GitHub organization) maintains it in ThinkInAIXYZ/deepchat, which has 6,359 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on October 9, 2026.
Source: ThinkInAIXYZ/deepchat on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.