memory-seed 1.5.3

Portable local memory seed for file-reading AI coding agents

Memory Seed

Memory Seed is a portable local memory system for AI coding agents.

It provides a small set of plain Markdown control-plane files that can be planted into a new or existing project. During bootstrap, the seed generates project-specific operating memory so future agent sessions can recover the project's purpose, current state, conventions, risks, and recent decisions without depending on vendor-hosted memory.

Goals

• Keep project memory local, inspectable, and portable.
• Support file-reading AI coding agents through predictable Markdown files.
• Route tool-specific entry files into one shared .AGENTS/ memory core.
• Generate project-specific index.md, context.md, style.md, and session logs during bootstrap.
• Archive reusable control-plane versions while keeping generated project memory outside version archives.

Reusable Seed Files

AGENTS.md
CLAUDE.md
GEMINI.md
.AGENTS/
  agent-rules.md
  project-bootstrap.md

Generated Per-Project Files

.AGENTS/
  index.md
  context.md
  style.md
  sessions/

Current Version

The current reusable control-plane version is 1.4.

Archived reusable versions are stored under .AGENTS/archive/<version>/.

Python CLI

Memory Seed includes a small Python CLI.

From this repository, run:

python -m memory_seed.cli version
python -m memory_seed.cli doctor
python -m memory_seed.cli init --dry-run
python -m memory_seed.cli update --dry-run
python -m memory_seed.cli compact

The init command copies only the reusable seed files into the current folder:

AGENTS.md
CLAUDE.md
GEMINI.md
.AGENTS/agent-rules.md
.AGENTS/project-bootstrap.md

It does not copy generated project memory such as .AGENTS/context.md, .AGENTS/index.md, .AGENTS/style.md, .AGENTS/sessions/, or .AGENTS/archive/.

Use --dry-run to preview without changing files. Use --force only when you intentionally want to back up and replace existing seed files.

When --force creates backups, Memory Seed adds .AGENTS/backups/ to the target project's .gitignore to reduce the chance of committing replaced local memory files.

The update command refreshes only the reusable control-plane files in an existing project. It uses each file's memory-system-version YAML field to decide whether that file is current. It backs up replaced control-plane files under .AGENTS/backups/<timestamp>/, restores any missing reusable seed files, skips files already on the current control-plane version, and does not change generated project memory such as .AGENTS/context.md, .AGENTS/index.md, .AGENTS/style.md, or .AGENTS/sessions/.

The compact command summarises recent session activity so an agent can identify durable facts to promote into context.md, index.md, and style.md:

memory-seed compact              # last 7 days (default)
memory-seed compact --days 30    # last 30 days
memory-seed compact --all        # all sessions
memory-seed compact --output summary.md  # write to file

The output is a structured Markdown report with session headings and full entry text. The CLI summarises; the agent (or user) decides what to promote. No files are modified automatically.

For Code Projects

When Memory Seed is planted into a software, library, or API project, agents will use Semble for code search. Semble returns only the relevant code chunks, using ~98% fewer tokens than grep+read.

Install it once, globally:

claude mcp add semble -s user -- uvx --from "semble[mcp]" semble

During bootstrap, the agent adds a Code Search section to the project's AGENTS.md so all future agents — including sub-agents — can call semble search directly. No per-project setup is needed after that.

Public Memory Hygiene

Memory Seed files are plain Markdown and may be committed with a project. Treat .AGENTS files as publishable unless the project is explicitly private.

Do not put secrets, credentials, tokens, private keys, sensitive account details, client confidential information, or unnecessary personal data into generated memory files or session logs.

Publishing

This repository is configured for PyPI trusted publishing from GitHub Actions.

PyPI pending publisher settings should match:

PyPI Project Name: memory-seed
Owner: jnl-tshi
Repository name: memory-seed
Workflow name: publish.yml
Environment name: pypi

The publish workflow lives at .github/workflows/publish.yml. It runs tests, builds the package with uv build, and publishes through PyPI's trusted publisher flow.