By chicago-joe
Memory compression system for Claude Code - persist context across sessions
Generate a "Journey Into [Project]" narrative report analyzing a project's entire development history from claude-mem's timeline. Use when asked for a timeline report, project history analysis, development journey, or full project report.
Automated semantic versioning and release workflow for Claude Code plugins. Handles version increments across package.json, marketplace.json, plugin.json manifests, npm publishing (so `npx [email protected]` resolves), build verification, git tagging, GitHub releases, and changelog generation.
Generate a serial week-by-week narrative digest of a project's full claude-mem timeline. Splits the timeline into per-ISO-week files, then runs one consecutive subagent per week — each receiving the prior week's carry-forward block — to produce one chapter per ISO week of data. Use when asked for "weekly digests", "week-by-week story", "serial timeline", or "narrative chapters" of a project's history.
Turn one document into a kawaii NotebookLM slide-deck PDF. Use for "wowerpoint this", "make a deck about <file>", "turn this report into slides", or any request to render a single document as shareable narrative slides.
Search claude-mem's persistent cross-session memory database. Use when user asks "did we already solve this?", "how did we do X last time?", or needs work from previous sessions.
Matches all tools
Hooks run on every tool call, not just specific ones
Admin access level
Server config contains admin-level keywords
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Team memory for multi-session, multi-modal agentic coding agents.
This project extends claude-mem — a persistent memory plugin for AI coding tools — into a shared memory system for engineering teams. Two capabilities drive the work:
AI coding agents remember nothing across sessions and share nothing across teammates. Each developer rediscovers the same patterns, re-explains the same context, and loses the reasoning behind every change the moment the session ends.
claude-mem solves the single-developer case. manymems solves the team case.
Developer prompt
│
▼
UserPromptSubmit hook
│ stores prompt_text in user_prompts table
▼
PostToolUse hook ──► observation handler
│ │
│ ▼
│ Claude Agent SDK
│ (compresses tool events
│ into structured observations)
│ │
▼ ▼
SQLite ◄────────── storeObservation()
(local) files_modified: [paths] ← paths only, no line ranges
│
▼
Chroma (vectors)
│
▼
SessionStart hook
injects relevant past observations
into the next session's context
The team server (Postgres + BullMQ + better-auth, merged in PR #2383) adds multi-user identity, API-key auth, and a horizontally scalable worker. The substrate is sound; the gaps are provenance and team-layer features.
User types a prompt
│
▼ (UserPromptSubmit)
user_prompts row ──── prompt_id ────────────────────────┐
│
│ │
▼ (PostToolUse: Edit / Write) │
A1: extract line ranges │
│ new_string found in file after edit │
│ line_start, line_end computed deterministically │
▼ │
A2: build symbol anchor (tree-sitter) │
│ qualified_name: "AuthService.login" │
│ signature_hash: sha256(signature) ← staleness │
▼ │
A3: code_provenance row ◄─────────────── prompt_id ───────┘
│ file_path, line_start, line_end
│ symbol_qualified_name, signature_hash
│ old_content_hash, new_content_hash
│ commit_sha (backfilled by A4)
▼
A4: git post-commit hook
│ fills commit_sha on matching rows
▼
A5: get_code_provenance MCP tool
│ input: file, line
│ output: [{prompt_text, symbol, line_range,
│ commit_sha, stale}]
▼
"why was this written?" answered
Staleness: when a query arrives, manymems re-hashes the symbol's current signature. If it differs from the stored signature_hash, the record returns stale: true.
npx claudepluginhub chicago-joe/manymems --plugin claude-memMemory compression system for Claude Code - persist context across sessions
Standalone image generation plugin using Nano Banana MCP server. Generates and edits images, icons, diagrams, patterns, and visual assets via Gemini image models. No Gemini CLI dependency required.
Multi-model consensus engine integrating OpenAI Codex CLI, Gemini CLI, and Claude CLI for collaborative code review and problem-solving.
Ultra-compressed communication mode. Cuts ~75% of tokens while keeping full technical accuracy by speaking like a caveman.
Streamline people operations — recruiting, onboarding, performance reviews, compensation analysis, and policy guidance. Maintain compliance and keep your team running smoothly.
Write feature specs, plan roadmaps, and synthesize user research faster. Keep stakeholders updated and stay ahead of the competitive landscape.