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Agent skill

Lpm Memory

by gug007 in gug007/lpm

Shared project memory for AI coding agents: save or recall work-session logs in ~/.lpm/memory/<project/<session.md so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue…

MITAuto-check passedAgent Workflows

Install Lpm Memory

skills CLI
$ npx skills add gug007/lpm --skill lpm-memory -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install gug007/lpm lpm-memory --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/gug007/lpm.git skills-src && mkdir -p .claude/skills && cp -r skills-src/lpm-memory .claude/skills/lpm-memory && rm -rf skills-src

Use ~/.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/

Facts

Skill name
lpm-memory
GitHub stars
152
Token cost
~1.1k tokens
SKILL.md length
486 words
Files
2
Skills in repo
10
Repo updated
First seen
Licence
MIT

At a glance

Shared project memory for AI coding agents: save or recall work-session logs in ~/.lpm/memory/<project/<session.md so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue…

  • Works in 3 steps: $LPM_MEMORY_DIR, which lpm sets for… → ~/.lpm/memory/ where comes from lpm… → Without the lpm CLI, ~/.lpm/memory/…
  • The user asks to remember
  • SKILL.md covers Remember (save / hand off) and Recall (continue / join)
  • Calls git

What it does

Lpm Memory is an agent skill from gug007/lpm. Shared project memory for AI coding agents: save or recall work-session logs in ~/.lpm/memory/<project/<session.md so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue the work by session name. Invoke with a session id (e.g. /lpm-memory auth-refactor) to continue that session. Use when the user asks to remember or save the session or progress, hand off work, record what was done, or recall/continue/resume/join a named work session. This is per-project memory shared between agent CLIs…

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files (for example `agents/openai.yaml`).

It sits in Agent Workflows, covering Agent memory and Refactoring. It works with Git. The repository describes itself as: Start, stop, and duplicate dev projects with one click. The best workspace for running Claude Code, Codex, and other AI agents alongside your services. The licence is MIT.

When your agent uses it

  • The user asks to remember
  • Save the session
  • Record what was done
  • Recall/continue/resume/join a named work session

Example prompts

  • “/lpm-memory”

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. $LPM_MEMORY_DIR, which lpm sets for every terminal it opens — always use it when set.
  2. ~/.lpm/memory/ where comes from lpm project --json: its parentName, or its name when parentName` is empty.
  3. Without the lpm CLI, ~/.lpm/memory/ where is $LPM_PROJECT_NAME, else the main checkout's folder name (basename "$(dirname "$(cd "$(git…

What it can do on your machine

Read from SKILL.md and the folder at commit 986226a. 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

    Shell commands in SKILL.md call:

    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use git, which can reach the network depending on how they are called.

    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

Lpm Memory loads about 1.1k tokens when it runs. Until then it costs about 146 tokens; SKILL.md has 486 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~146
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

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 gug007/lpm at commit 986226a, republished under its MIT licence (© gug007). 486 words, ~1,069 tokens.

Download SKILL.mdSave it as .claude/skills/lpm-memory/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
lpm-memory
description
Shared project memory for AI coding agents: save or recall work-session logs in `~/.lpm/memory/<project>/<session>.md` so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue the work by session name. Invoke with a session id (e.g. `/lpm-memory auth-refactor`) to continue that session. Use when the user asks to remember or save the session or progress, hand off work, record what was done, or recall/continue/resume/join a named work session. This is per-project memory shared between agent CLIs — distinct from any CLI's own built-in memory.
version
1.6.0
argument-hint
[session-id]

Project memory lives in one folder per project, shared by every agent CLI. Resolve that folder in this order:

  1. $LPM_MEMORY_DIR, which lpm sets for every terminal it opens — always use it when set.
  2. ~/.lpm/memory/<project> where <project> comes from lpm project --json: its parentName, or its name when parentName is empty.
  3. Without the lpm CLI, ~/.lpm/memory/<project> where <project> is $LPM_PROJECT_NAME, else the main checkout's folder name (basename "$(dirname "$(cd "$(git rev-parse --git-common-dir)" && pwd)")", so a Git worktree resolves to the repository it belongs to), else the working directory's folder name.

A duplicate of a project shares the original's memory — same codebase, and the copy is disposable — so never derive a folder of its own from a copy's name or path. <session> is a kebab-case slug for one workstream (e.g. auth-refactor); each file is both the current handoff state and the work history.

Invocation:

  • /lpm-memory <session-id> — Recall that session and continue it. Unknown id: offer close matches, or create it.
  • No argument — Remember work already done in this conversation; at the very start of one, pick or create the session instead.
  • Either way, keep the memory current from then on without being asked: append a timeline entry and refresh ## Current state after each milestone and when the user wraps up.

Remember (save / hand off)

  1. Session slug: the user's name for it, else the one existing file that matches the work, else derive one and confirm it before writing.

  2. Create the folder if missing. Seed a new file with:

    markdown
    # <Work title>

## Goal
<one or two lines>

## Current state
<where things stand, next steps, blockers>

## Timeline

  3. Re-read the file right before writing — another agent may have saved meanwhile. If it changed since you last read it, keep their changes: append your timeline entry after theirs and fold both realities into ## Current state.

  4. Rewrite ## Current state to match reality now.

  5. Append a new entry at the end of ## Timeline. The timeline is strictly append-only: never edit or delete an existing entry — not even your own from earlier in the same conversation. Each entry covers only what happened since the previous save:

    markdown
    ### <YYYY-MM-DD HH:MM> — <agent>
- Done: what shipped or changed, in outcome terms
- Decided: choices made and why, including approaches tried and dropped
- Learned: surprises and gotchas the next agent must know
- Open: unresolved questions / blockers
- Next: unfinished work / immediate next step

    <agent> = your CLI name (claude, codex, ...), local time. Drop empty lines; keep it brief.

  6. Compaction — the one exception to append-only: when the timeline exceeds ten entries, condense the oldest into a single digest entry ### Archived through <YYYY-MM-DD> kept first in ## Timeline; keep the newest five entries verbatim. Condense only — preserve every decision and gotcha that still matters, never reinterpret, and fold into the existing digest on later compactions.

Show full SKILL.md (79 more words)Show less

Recall (continue / join)

  1. List the project memory folder's *.md; read the named session, or show the list (name, last modified, goal line) and ask which one.
  2. ## Current state is the source of truth; the newest timeline entries carry the freshest detail. Read those first — reach for older entries and the archive digest only when the work needs that history.
  3. State the next step you inferred, confirm direction, then continue — and Remember at the next stopping point.

© gug007, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file in lpm-memory of gug007/lpm.

  • SKILL.md
  • agents/openai.yaml

Open the folder on GitHubat commit 986226a

Compare with similar skills

Lpm 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.

Lpm Memory compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Lpm Memory this skillgug007/lpm152—~1.1kAutomated safety check: PassMIT
Neat-Freak Knowledge CloseoutKKKKhazix/khazix-skills21k—~1.9kAutomated safety check: PassMIT
Beads Task Memorygastownhall/beads28k—~1.2kAutomated safety check: PassMIT
Ownmemgrpcer/ownmem423—~593Automated safety check: PassApache-2.0
Docslatitude-dev/latitude-llm4.7k—~2.5kAutomated safety check: PassMIT
Update Docspeterkrueck/Claude-Code-Development-Kit1.4k—~2.7kAutomated safety check: PassMIT

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  • Neat-Freak Knowledge Closeout

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    21k GitHub stars~1.9k tokensUpdated 6 days ago
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Works with

Categories

Questions about Lpm Memory

What does Lpm Memory do?

Shared project memory for AI coding agents: save or recall work-session logs in ~/.lpm/memory/<project/<session.md so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue…. Lpm Memory is an agent skill from gug007/lpm.md so another agent CLI (Claude Code, Codex, Gemini) or a future session can continue the work by session name.

When should I use Lpm Memory?

Lpm Memory fits situations like: the user asks to remember; save the session; record what was done; recall/continue/resume/join a named work session.

How do I install Lpm Memory in Claude Code?

Run `npx skills add gug007/lpm --skill lpm-memory -a claude-code`. Or copy the skill folder (lpm-memory in gug007/lpm) into .claude/skills/lpm-memory in your project. Claude Code loads it when a task matches its description.

How do I install Lpm Memory in Codex?

Run `npx skills add gug007/lpm --skill lpm-memory -a codex`. Or copy the skill folder (lpm-memory in gug007/lpm) into .agents/skills/lpm-memory in your project. Codex loads it when a task matches its description.

Can I use Lpm 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 gug007/lpm --skill lpm-memory -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/lpm-memory, .gemini/skills/lpm-memory, .github/skills/lpm-memory and .opencode/skills/lpm-memory in your project.

What does Lpm Memory need to run?

Going by SKILL.md and its folder, Lpm Memory needs the command-line tools its instructions call (git).

Does Lpm Memory access the network?

SKILL.md contains no URLs. Its commands use git, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Lpm Memory 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 Lpm Memory use?

Lpm Memory is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Lpm Memory use?

About 1.1k tokens (SKILL.md is roughly 4.3k 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 Lpm Memory?

Skills that share tags, products or a category with Lpm Memory: Neat-Freak Knowledge Closeout (KKKKhazix/khazix-skills, 21k stars), Beads Task Memory (gastownhall/beads, 28k stars), Ownmem (grpcer/ownmem, 423 stars) and Docs (latitude-dev/latitude-llm, 4.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Lpm Memory?

gug007 (a GitHub user) maintains it in gug007/lpm, which has 152 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 8, 2026.

Source: gug007/lpm on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.