skill-memory-bank
Universal long-term project memory for AI coding agents — Claude Code, Cursor, Windsurf, Cline + 4 more. TDD rules, code graph, spec-driven dev, cross-session recall.
Install / Use
npx skills add fockus/skill-memory-bankInstalls into whichever agent you are using.
Other
Other agent config
Quality Score
Category
AI & Machine LearningSupported Platforms
Our assessment of skill-memory-bank
skill-memory-bank scores 78/100 on our quality scale, 804th of 965 AI & Machine Learning skills we index.
Its Other is 44 KB long, well organised into 57 sections with 24 code examples: long enough that it reads more like full documentation than a focused instruction file, which agents can find harder to follow.
It has 33 GitHub stars, so there is little community track record yet; judge it on its content.
Maintenance, license and trust
- The repository was last updated 18 days ago, so skill-memory-bank is actively maintained.
- Our last check on 2026-10-21 found the source still online.
- It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
- Its trust signals score 97/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.
Safety scan
No issues foundOur scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful.
AI review by kimi-k2.7-code on 2026-09-24. Automated pattern scan on 2026-09-24. It catches known dangerous patterns, not every risk — read a skill before letting an agent act on it.
skill-memory-bank compared with similar skills
All 4 of these similar skills score higher than skill-memory-bank; compare them before choosing.
| Skill | Score | Stars | Updated | Format |
|---|---|---|---|---|
| skill-memory-bank (this skill)by fockus | 78 | 33 | 18d ago | Other |
| claude-memby thedotmack | 100 | 113.5k | today | CLAUDE.md |
| Understand-Anythingby Egonex-AI | 100 | 90.9k | 10d ago | CLAUDE.md |
| headroomby headroomlabs-ai | 100 | 78.9k | today | CLAUDE.md |
| CowAgentby zhayujie | 100 | 47.8k | today | CLAUDE.md |
Frequently asked questions
- How do I install skill-memory-bank?
- Run
npx skills add fockus/skill-memory-bank. The install tabs above show the steps for each supported agent. - Which AI agents does skill-memory-bank work with?
- It is written for Claude Code, Cursor, Windsurf, Cline and OpenAI Codex, as a Other file. Other agents that read the same format can often use it too.
- Is skill-memory-bank safe to use?
- Our scan of the whole file found no instruction hijacking, hidden characters, credential access, data exfiltration or destructive commands. An AI review of the same text found nothing harmful. It is MIT-licensed and scores 97/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
- Is skill-memory-bank still maintained?
- The repository was last updated 18 days ago, so skill-memory-bank is actively maintained.
Skill content
View source on GitHubmemory-bank-skill
Persistent project memory + dev toolkit for AI coding agents.
Your AI remembers the project between sessions, follows the same engineering rules, and picks up exactly where you left off.
Claude Code · Cursor · Windsurf · Cline · Kilo · OpenCode · Codex · Pi Code
Install · Quick start · What you get · Code graph · Commands · Cross-agent · FAQ · Docs · Website
<a href="https://fockus.github.io/skill-memory-bank/"><img src="https://raw.githubusercontent.com/fockus/skill-memory-bank/main/site/og-image.png" alt="memory-bank-skill — persistent memory for AI coding agents" width="720"></a>
</div>New in v5.0 — the
/mb workpipeline is now composable: the default flow is a leanimplement → verify → done, with review and judge as opt-in stages (--review,--judge,--workflow full). CHANGELOG · v4 → v5 migration
pipx install memory-bank-skill && memory-bank install
# then, inside your agent:
/mb init # once per project
/mb start # every session — full context restored
| Slash commands | /mb sub-commands | Subagents | AI clients | Automated tests |
|:--------------:|:------------------:|:---------:|:----------:|:---------------:|
| 25 | 25+ | 29 | 8 | 1,900+ |
The problem it solves
Every new AI coding session is amnesia: you re-explain the project, re-state the plan, re-list what's done — and context compaction erases whatever the agent finally learned. memory-bank-skill makes project memory a first-class citizen: a .memory-bank/ directory next to your code that the agent reads at session start and updates as it works.
.memory-bank/
├── status.md ← where we are, what's next
├── checklist.md ← current tasks (✅ / ⬜)
├── roadmap.md ← priorities, direction
├── research.md ← hypotheses log (H-NNN) + current experiment
├── backlog.md ← parking lot for ideas + ADRs
├── progress.md ← work log (append-only)
├── lessons.md ← mistakes not to repeat
├── notes/ ← knowledge (5-15 line snippets)
├── plans/ ← detailed plans per feature/fix
├── reports/ ← analysis, post-mortems
├── experiments/ ← EXP-NNN experiment artifacts
└── codebase/ ← stack / architecture / conventions map (`/mb map`)
This directory lives alongside your code (commit it, share it with your team, or .gitignore it — your call).
Install
Pick one:
Option 0: skills.sh CLI (fastest one-shot install)
npx skills add fockus/skill-memory-bank
Copies the skill bundle (SKILL.md + scripts + commands + agents) into your local skills directory. Use this for a quick single-host try-out (Claude Code, Cursor, or any host that reads ~/.claude/skills/ or ~/.cursor/skills/). For cross-agent setup (Codex / Windsurf / OpenCode hooks, managed blocks in AGENTS.md, memory-bank CLI, hooks, slash commands globally installed), use Option 1 or 2 below.
Option 1: pipx (recommended, cross-platform)
pipx install memory-bank-skill # stable
# or, for the latest release candidate:
pipx install --pip-args='--pre' memory-bank-skill
# pipx only installs the CLI. Run this once to wire agents, rules, commands, and Pi prompts:
memory-bank install # global install for Claude Code + Cursor + Codex + OpenCode + Pi
# optional: pick installed rule language explicitly
memory-bank install --language ru
Requires: Python 3.11+, pipx, jq, git, bash (3.2+; macOS ships one, Windows needs Git Bash/WSL — see docs/install.md).
Option 2: Homebrew (macOS / Linuxbrew)
brew tap fockus/tap
brew install memory-bank
memory-bank install
Option 3: git clone (developers)
git clone https://github.com/fockus/skill-memory-bank.git ~/.claude/skills/skill-memory-bank
cd ~/.claude/skills/skill-memory-bank
./install.sh
Add cross-agent support (Cursor, Windsurf, OpenCode, etc.)
Three ways — pick whichever matches your workflow:
A. Interactive menu (from any terminal — recommended if you're unsure which clients you want):
cd your-project/
memory-bank install # multi-select prompt for all 8 clients
# in TTY mode it will also ask which language to use for installed rules
B. CLI flags (scripts / CI / one-liner):
cd your-project/
memory-bank install --clients claude-code,cursor,windsurf
memory-bank install --clients claude-code,cursor --language en
C. From inside an agent with command surface (Claude Code / OpenCode):
/mb install # interactive picker
/mb install cursor,windsurf # direct
/mb install all # every client
Claude Code/OpenCode can front this through /mb install, then run memory-bank install --clients <selected> for the current project. In Codex use the CLI directly; Codex gets global skill discovery plus ~/.codex/AGENTS.md hints, not a native /mb command surface.
Supported client names: claude-code, cursor, windsurf, cline, kilo, opencode, pi, codex.
Supported rule languages: en (default), ru (full translation), es/zh (scaffolds — community PRs welcome, see docs/i18n.md). You can also set MB_LANGUAGE=en|ru|es|zh.
Full per-client details: docs/cross-agent-setup.md.
5-minute quick start
-
Install (see above).
-
Open your project in your AI agent (Claude Code, Cursor, etc.) and run:
/mb initThis creates
.memory-bank/with all the files above, detects your stack, and generates aCLAUDE.md(or equivalent) pointing the agent at the memory bank. -
Every session starts with:
/mb startThe agent loads
status.md,checklist.md,roadmap.md,research.md— it knows exactly what you were working on and what comes next. -
As you work: the agent updates
checklist.md(⬜ → ✅) whenever tasks finish. -
Every session ends with:
/mb doneThis appends a session entry to
progress.md, updatesstatus.mdif needed, writes a knowledge note if something interesting was learned.
That's it. Rinse and repeat.
The core workflow: build a feature
init / start / done are the session bookends. The actual feature work happens through a plan or spec → work → verify → done loop. Two entry points:
Plan-based — for a well-understood change:
/mb plan feature "user avatar upload" # scaffolds a staged plan with SMART DoD + TDD notes
/mb work # executes the plan stage by stage (TDD → verify per stage)
/mb verify # audits the diff against every DoD item — REQUIRED before done
/mb done # closes the session, appends progress, writes a note
Spec-driven (SDD) — for a larger or fuzzier feature, add an interview + spec first. The full chain is brief → discuss → sdd → work:
/mb brief billing-overhaul --input PRD.md # raw request + documents → validated one-pager in briefs/
/mb discuss billing-overhaul # 5-phase interview → EARS-validated context/billing-overhaul.md
/mb sdd billing-overhaul # generates specs/billing-overhaul/{requirements,design,tasks}.md
/mb work billing-overhaul # executes the tasks.md items (<!-- mb-task:N -->) in order
/mb verify
/mb done
Use one kebab-case slug for the whole feature (billing-overhaul, not "billing overhaul") — /mb discuss uses the topic verbatim as the filename, so keeping it already-slugged makes every later command resolve to the same context/ and specs/ paths.
/mb work runs implement (TDD) → verify → done by default — review is off, so it stays fast and cheap. /mb verify is mandatory before /mb done whenever the work followed a plan: it re-reads the plan and checks every DoD item against the real code, so you never close a stage that only looks finished.
Storage modes
Memory Bank supports three ways to store your bank — pick the one that fits your workflow:
Local mode (default)
/mb init # same as /mb init --storage=local
The bank lives in the repo at .memory-bank/. Commit it to share with your team, or add it to .gitignore for solo use. This is the default and recommended mode for team projects.
Global mode (opt-in personal storage)
/mb init --storage=global --agent=claude-code # for Claude Code
/mb init --storage=global --agent=cursor # for Cursor
/mb init --storage=global --agent=codex # for Codex
The bank lives outside the repo under ~/.<agent>/memory-bank/projects/<id>/.memory-bank. It is personal storage and must not be committed to the project repo. Use this when you want persistent memory across sessions but don't want to touch the repository.
Rules-only mode (no init required)
You can intentionally skip /mb init entirely. In this state:
- The agent prints
[MEMORY BANK: ABSENT]— Memory Bank lifecycle commands (/mb start,/mb done, etc.) stay inactive. - All engineering rules still apply: TDD, SOLID, Clean Architecture, DRY/KISS/YAGNI, Testing Trophy, protected files, no placeholders. The installed global rules (
~/.claude/CLAUDE.md,~/.codex/AGENTS.md, etc.) are always-on. - Run
/mb initat any point to activate Memory Bank without losing any code.
Existing local bank users can stay on local mode — there is no forced migration.
Rule profiles & stack presets
Personalize the configurable rules layer without weakening the immutable safety baseline (TDD, no placeholders, protected files, destructive-confirm, fail-fast, DRY/KISS/YAGNI, verification before completion — these cannot be disabled by any profile).
# User-global profile (works even without a project Memory Bank):
mb-profile.sh init --scope=user --role=backend --stack=go --architecture=microservices --delivery=contract-first
# Project profile (stored in .memory-bank/ or global bank):
mb-profile.sh init --scope=project --role=frontend --stack=typescript --architecture=fsd --delivery=sdd
Supported role presets: backend, frontend, mobile. Supported stack presets: go,
Truncated for display — read the full file on GitHub.
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Languages
Trust signals
From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.
