Planning with Files
OthmanAdi/planning-with-files
Keeps a task plan, findings and progress log in markdown files on disk so long agent tasks survive context resets, with Gemini hooks and helper scripts.
Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward.
Install Memori Long-Term Memory
$ npx skills add MemoriLabs/Memori --skill memori -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MemoriLabs/Memori memori --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/MemoriLabs/Memori.git skills-src && mkdir -p .claude/skills && cp -r skills-src/integrations/claude-code .claude/skills/memori && 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 "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .claude/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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/MemoriLabs/Memori/tree/main/integrations/claude-codeType 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 MemoriLabs/Memori --skill memori -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MemoriLabs/Memori memori --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MemoriLabs/Memori.git skills-src && mkdir -p .agents/skills && cp -r skills-src/integrations/claude-code .agents/skills/memori && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .agents/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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 MemoriLabs/Memori --skill memori -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MemoriLabs/Memori memori --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MemoriLabs/Memori.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/integrations/claude-code .cursor/skills/memori && 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 "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .cursor/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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/MemoriLabs/Memori.git --path integrations/claude-code--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 MemoriLabs/Memori --skill memori -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MemoriLabs/Memori memori --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MemoriLabs/Memori.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/integrations/claude-code .gemini/skills/memori && 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 "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .gemini/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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 MemoriLabs/Memori memoriInstalls 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 MemoriLabs/Memori --skill memori -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MemoriLabs/Memori.git skills-src && mkdir -p .github/skills && cp -r skills-src/integrations/claude-code .github/skills/memori && 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 "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .github/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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 MemoriLabs/Memori --skill memori -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MemoriLabs/Memori memori --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MemoriLabs/Memori.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/integrations/claude-code .opencode/skills/memori && 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 "memori" agent skill from https://github.com/MemoriLabs/Memori/tree/main/integrations/claude-code into .opencode/skills/memori/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "memori", 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
memori- GitHub stars
- 17k
- Token cost
- ~2k tokens
- SKILL.md length
- 749 words
- Files
- 4
- Skills in repo
- 3
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward.
- Works in 7 steps: Run recall before drafting any… → Always run recall before any external… → Use recall.summary only for broad… → …
- Keeping long-term memory across Claude Code sessions in the same project
- SKILL.md covers Setup, Commands, Procedure and Recall, plus 2 more sections
- Runs TypeScript scripts from its folder; calls bun; needs MEMORI_API_KEY
What it does
The skill is a thin command-line wrapper, run with bun, around Memori Cloud. It is meant to work in the background: the agent is told to recall relevant memory before drafting any substantive reply and before external lookups, without waiting for you to mention memory, and to finish non-trivial turns with an advanced-augmentation step that stores what happened. Trivial acknowledgements, turns where past context cannot help and turns where you opt out are skipped.
Other commands include recall.summary for broad session summaries, compaction to restore context after it is lost, feedback on memory quality, quota for limits, and signup, which is used only when you ask for it. Setup needs a MEMORI_API_KEY and a MEMORI_ENTITY_ID in .claude/settings.local.json or a colocated .env file. The project ID defaults to the workspace folder name and the session ID to the Claude Code session, while recall reads stay project-scoped across sessions.
When your agent uses it
- Keeping long-term memory across Claude Code sessions in the same project
- Recalling past decisions, preferences and project history before answering
- Restoring session context after it was lost to compaction or a cleared chat
Example prompts
- “What did we decide last week about the database migration approach?”
- “Recall what you know about my preferences for test naming before you write these tests.”
- “Give me a summary of everything stored for this project so far.”
- “How much of my Memori quota is left?”
Requirements
- A Memori Cloud API key (MEMORI_API_KEY)
- A stable MEMORI_ENTITY_ID
- bun, to run index.ts
- Pre-approved tools (allowed-tools): Bash
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Run recall before drafting any substantive response. This is the default
- Always run recall before any external information lookup (WebSearch,
- Use recall.summary only for broad summary cases: session orientation,
- Use compaction only after context compaction or lost working context.
- Answer or complete the user's actual request. Memory should improve
- After drafting the final response for a non-trivial turn, run
- Use feedback, quota, and signup only when the user request or a
What it can do on your machine
Read from SKILL.md and the folder at commit 574b1ea. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
Bash
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (TypeScript), which the agent can run.
Shell commands in SKILL.md call:
bun
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 these keys or tokens, usually read from environment variables:
MEMORI_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Memori Long-Term Memory loads about 2k tokens when it runs. Until then it costs about 247 tokens; SKILL.md has 749 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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NoteMentions a .env fileSKILL.md:78
A colocated `.env` file next to `index.ts` is loaded as a fallback when - NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Bash
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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 749 words (~1,973 tokens).
“Thin CLI wrapper around Memori Cloud for Claude Code subprocesses. Memori is an ambient memory enhancement, not an explicit destination tool. Do not wait for the user to ask to "use Memori" before applying the memory lifecycle below. Claude Code's…”
- name
- memori
- allowed-tools
- Bash
- argument-hint
- <command> [--flags ...]
Files
SKILL.md and 3 other files in integrations/claude-code of MemoriLabs/Memori.
- SKILL.md
- .env.example
- README.md
- index.ts
Open the folder on GitHubat commit 574b1ea
Compare with similar skills
Memori Long-Term Memory 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 |
|---|---|---|---|---|---|---|
| Memori Long-Term Memory this skillMemoriLabs/Memori | 17k | — | ~2k | Automated safety check: Notes | Custom licence | |
| Planning with FilesOthmanAdi/planning-with-files | 27k | — | ~2.9k | Automated safety check: Pass | MIT | |
| User Thoughts Memorysickn33/agentic-awesome-skills | 47k | 1 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Planning With FilesOthmanAdi/planning-with-files | 27k | — | ~3k | Automated safety check: Pass | MIT | |
| Harness Engineering10xChengTu/harness-engineering | 102 | 1 repos | ~1k | Automated safety check: Pass | None | |
| Planning with Files for KiroOthmanAdi/planning-with-files | 27k | — | ~2.1k | Automated safety check: Pass | MIT |
Similar skills
User Thoughts Memory
sickn33/agentic-awesome-skills
Saves a user's project decisions, rules and preferences into a project-local mdbase so later sessions and other agents can recover the intent.
Planning With Files
OthmanAdi/planning-with-files
Keeps a task plan, findings and progress log as Markdown files in the project so long multi-step agent work survives context resets.
Harness Engineering
10xChengTu/harness-engineering
Set up and improve harness engineering (AGENTS.md, docs/, lint rules, eval systems, project-level prompt engineering) for AI-agent-friendly codebases.
Planning with Files for Kiro
OthmanAdi/planning-with-files
Keeps task_plan.md, findings.md and progress.md on disk as the agent's working memory for multi-step work, wired into Kiro steering, with no hooks.
CPR Compress
EliaAlberti/cpr-compress-preserve-resume
Saves the current session as a searchable log with a curated summary and the raw transcript, so a later session can resume from it.
More from MemoriLabs/Memori
Memori Long-Term Memory
MemoriLabs/Memori
Adds structured long-term memory to OpenClaw agents, built automatically from sessions, with tools the agent calls to recall facts, summaries and decisions.
Memori MCP Memory Usage
MemoriLabs/Memori
Teaches an MCP-connected agent when and how to call Memori's recall, summary, compaction, augmentation, feedback and quota tools to keep context across sessions.
Related
Categories
Questions about Memori Long-Term Memory
What does Memori Long-Term Memory do?
Connects Claude Code to Memori Cloud for long-term memory, recalling stored context before substantive replies and saving new context afterward. The skill is a thin command-line wrapper, run with bun, around Memori Cloud. It is meant to work in the background: the agent is told to recall relevant memory before drafting any substantive reply and before external lookups, without waiting for you to mention memory, and to finish non-trivial turns with an advanced-augmentation step that stores what happened.
When should I use Memori Long-Term Memory?
Memori Long-Term Memory fits situations like: keeping long-term memory across Claude Code sessions in the same project; recalling past decisions, preferences and project history before answering; restoring session context after it was lost to compaction or a cleared chat.
How do I install Memori Long-Term Memory in Claude Code?
Run `npx skills add MemoriLabs/Memori --skill memori -a claude-code`. Or copy the skill folder (integrations/claude-code in MemoriLabs/Memori) into .claude/skills/memori in your project. Claude Code loads it when a task matches its description.
How do I install Memori Long-Term Memory in Codex?
Run `npx skills add MemoriLabs/Memori --skill memori -a codex`. Or copy the skill folder (integrations/claude-code in MemoriLabs/Memori) into .agents/skills/memori in your project. Codex loads it when a task matches its description.
Can I use Memori Long-Term Memory 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 MemoriLabs/Memori --skill memori -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memori, .gemini/skills/memori, .github/skills/memori and .opencode/skills/memori in your project.
What does Memori Long-Term Memory need to run?
Going by SKILL.md and its folder, Memori Long-Term Memory needs TypeScript for the scripts in its folder, the command-line tools its instructions call (bun) and credentials named MEMORI_API_KEY. Our summary lists: A Memori Cloud API key (MEMORI_API_KEY); A stable MEMORI_ENTITY_ID; bun, to run index.ts. Its frontmatter pre-approves these tools: Bash.
Does Memori Long-Term Memory 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 Memori Long-Term Memory safe to install?
Our automated static check of SKILL.md found notes only (mentions a .env file; pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Memori Long-Term Memory use?
Memori Long-Term Memory has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Memori Long-Term Memory use?
About 2k tokens (SKILL.md is roughly 7.9k 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 Memori Long-Term Memory?
Skills that share tags, products or a category with Memori Long-Term Memory: Planning with Files (OthmanAdi/planning-with-files, 27k stars), User Thoughts Memory (sickn33/agentic-awesome-skills, 47k stars), Planning With Files (OthmanAdi/planning-with-files, 27k stars) and Harness Engineering (10xChengTu/harness-engineering, 102 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Memori Long-Term Memory?
MemoriLabs (a GitHub organization) maintains it in MemoriLabs/Memori, which has 17,149 GitHub stars. The repository holds 3 skills in this directory. The repository was last updated on October 3, 2026.
Source: MemoriLabs/Memori on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.