Alex Newman 37d24944af feat(skills): wowerpoint share-link upload step (#2445)
* feat(skills): wowerpoint share-link upload step

After the kawaii NotebookLM PDF lands on disk, the subagent now also POSTs
it to the WOWerpoint Server (if configured) and reports back a share URL.
The PDF is still the backup; the share URL is the primary deliverable.

Gated on three env vars (WOWERPOINT_API_BASE, WOWERPOINT_VIEWER_BASE,
WOWERPOINT_UPLOAD_TOKEN) — if any are missing the skill skips the upload
silently and behaves exactly as before.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(skills): address CodeRabbit + Greptile findings on wowerpoint

- Drop the ~/.wowerpoint.env reference: the subagent inherits the parent's
  environment and never sources a dotenv file, so storing vars there would
  silently disable the upload step. Documented only the shell-export path.
- Switch jq parsing to `.id // empty` so a missing key yields an empty
  string instead of the literal "null", letting the [-z "$DECK_ID"] guard
  fire correctly on error responses.
- Capture the full JSON response so a non-empty .error field is surfaced as
  a warning rather than emitting an invalid …/d/null share URL.
- Add TITLE to the subagent template's Inputs block so the parent agent
  knows it must supply a title slot the curl command depends on.
- Make step 6 itself guard on the env vars instead of relying on prose, so
  the snippet works in isolation if a future agent skips the surrounding
  instructions.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(skills): gate the top-level upload snippet on env vars too

CodeRabbit pointed out the prose snippet at the top of the Share-link
section uploaded unconditionally, while the subagent step 6 version had the
env-var guard. Anyone copying the standalone snippet would have skipped
"silently" by failing the curl request. Wrapping both in the same guard
keeps the two snippets in sync.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* fix(skills): cap wowerpoint upload curls at 30 s

Greptile flagged that a bare curl on an unreachable WOWERPOINT_API_BASE can
sit on the OS TCP timeout (75–130 s) before returning, stalling the
background subagent and delaying the completion notification. Adding
--connect-timeout 10 --max-time 30 to both upload snippets bounds the
hang and lets the share-link step fail fast.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs(skills): wowerpoint slug example reflects 3-word IDs

Server now mints adjective-noun-creature slugs (e.g. quirky-compass-hawk)
instead of base64url. The curl/jq snippets are unchanged — they already
parse .id as opaque — but the prose was stale.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

* docs(skills): wowerpoint slug example reflects title-aware IDs

Server now slugifies the title and appends a creature suffix
(tokenrouter-quest-hawk) instead of three random words. Falls back to a
3-word slug when the title is empty or non-ASCII. The curl/jq snippets
are unchanged — they parse .id as opaque — but the prose was stale.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-12 20:38:37 -07:00
2026-05-11 00:28:52 -07:00
2026-05-11 18:41:25 -07:00
2026-05-04 20:29:31 -07:00
2026-05-11 18:41:25 -07:00
2026-04-04 14:58:05 -07:00


Claude-Mem

🇨🇳 中文🇹🇼 繁體中文🇯🇵 日本語🇵🇹 Português🇧🇷 Português🇰🇷 한국어🇪🇸 Español🇩🇪 Deutsch🇫🇷 Français🇮🇱 עברית🇸🇦 العربية🇷🇺 Русский🇵🇱 Polski🇨🇿 Čeština🇳🇱 Nederlands🇹🇷 Türkçe🇺🇦 Українська🇻🇳 Tiếng Việt🇵🇭 Tagalog🇮🇩 Indonesia🇹🇭 ไทย🇮🇳 हिन्दी🇧🇩 বাংলা🇵🇰 اردو🇷🇴 Română🇸🇪 Svenska🇮🇹 Italiano🇬🇷 Ελληνικά🇭🇺 Magyar🇫🇮 Suomi🇩🇰 Dansk🇳🇴 Norsk

Persistent memory compression system built for Claude Code.

License Version Node Mentioned in Awesome Claude Code

thedotmack/claude-mem | Trendshift


Claude-Mem Preview Star History Chart

Quick StartHow It WorksSearch ToolsDocumentationConfigurationTroubleshootingLicense

Claude-Mem seamlessly preserves context across sessions by automatically capturing tool usage observations, generating semantic summaries, and making them available to future sessions. This enables Claude to maintain continuity of knowledge about projects even after sessions end or reconnect.


Quick Start

Install with a single command:

npx claude-mem install

Or install for Gemini CLI (auto-detects ~/.gemini):

npx claude-mem install --ide gemini-cli

Or install for OpenCode:

npx claude-mem install --ide opencode

Or install from the plugin marketplace inside Claude Code:

/plugin marketplace add thedotmack/claude-mem

/plugin install claude-mem

Restart Claude Code or Gemini CLI. Context from previous sessions will automatically appear in new sessions.

Note: Claude-Mem is also published on npm, but npm install -g claude-mem installs the SDK/library only — it does not register the plugin hooks or set up the worker service. Always install via npx claude-mem install or the /plugin commands above.

🦞 OpenClaw Gateway

Install claude-mem as a persistent memory plugin on OpenClaw gateways with a single command:

curl -fsSL https://install.cmem.ai/openclaw.sh | bash

The installer handles dependencies, plugin setup, AI provider configuration, worker startup, and optional real-time observation feeds to Telegram, Discord, Slack, and more. See the OpenClaw Integration Guide for details.

Key Features:

  • 🧠 Persistent Memory - Context survives across sessions
  • 📊 Progressive Disclosure - Layered memory retrieval with token cost visibility
  • 🔍 Skill-Based Search - Query your project history with mem-search skill
  • 🖥️ Web Viewer UI - Real-time memory stream at http://localhost:37777
  • 💻 Claude Desktop Skill - Search memory from Claude Desktop conversations
  • 🔒 Privacy Control - Use <private> tags to exclude sensitive content from storage
  • ⚙️ Context Configuration - Fine-grained control over what context gets injected
  • 🤖 Automatic Operation - No manual intervention required
  • 🔗 Citations - Reference past observations with IDs (access via http://localhost:37777/api/observation/{id} or view all in the web viewer at http://localhost:37777)
  • 🧪 Beta Channel - Try experimental features like Endless Mode via version switching

Documentation

📚 View Full Documentation - Browse on official website

Getting Started

Best Practices

Architecture

Configuration & Development


How It Works

Core Components:

  1. 5 Lifecycle Hooks - SessionStart, UserPromptSubmit, PostToolUse, Stop, SessionEnd (6 hook scripts)
  2. Smart Install - Cached dependency checker (pre-hook script, not a lifecycle hook)
  3. Worker Service - HTTP API on port 37777 with web viewer UI and 10 search endpoints, managed by Bun
  4. SQLite Database - Stores sessions, observations, summaries
  5. mem-search Skill - Natural language queries with progressive disclosure
  6. Chroma Vector Database - Hybrid semantic + keyword search for intelligent context retrieval

See Architecture Overview for details.


MCP Search Tools

Claude-Mem provides intelligent memory search through 4 MCP tools following a token-efficient 3-layer workflow pattern:

The 3-Layer Workflow:

  1. search - Get compact index with IDs (~50-100 tokens/result)
  2. timeline - Get chronological context around interesting results
  3. get_observations - Fetch full details ONLY for filtered IDs (~500-1,000 tokens/result)

How It Works:

  • Claude uses MCP tools to search your memory
  • Start with search to get an index of results
  • Use timeline to see what was happening around specific observations
  • Use get_observations to fetch full details for relevant IDs
  • ~10x token savings by filtering before fetching details

Available MCP Tools:

  1. search - Search memory index with full-text queries, filters by type/date/project
  2. timeline - Get chronological context around a specific observation or query
  3. get_observations - Fetch full observation details by IDs (always batch multiple IDs)

Example Usage:

// Step 1: Search for index
search(query="authentication bug", type="bugfix", limit=10)

// Step 2: Review index, identify relevant IDs (e.g., #123, #456)

// Step 3: Fetch full details
get_observations(ids=[123, 456])

See Search Tools Guide for detailed examples.


Beta Features

Claude-Mem offers a beta channel with experimental features like Endless Mode (biomimetic memory architecture for extended sessions). Switch between stable and beta versions from the web viewer UI at http://localhost:37777 → Settings.

See Beta Features Documentation for details on Endless Mode and how to try it.


System Requirements

  • Node.js: 18.0.0 or higher
  • Claude Code: Latest version with plugin support
  • Bun: JavaScript runtime and process manager (auto-installed if missing)
  • uv: Python package manager for vector search (auto-installed if missing)
  • SQLite 3: For persistent storage (bundled)

Windows Setup Notes

If you see an error like:

npm : The term 'npm' is not recognized as the name of a cmdlet

Make sure Node.js and npm are installed and added to your PATH. Download the latest Node.js installer from https://nodejs.org and restart your terminal after installation.


Configuration

Settings are managed in ~/.claude-mem/settings.json (auto-created with defaults on first run). Configure AI model, worker port, data directory, log level, and context injection settings.

See the Configuration Guide for all available settings and examples.

Mode & Language Configuration

Claude-Mem supports multiple workflow modes and languages via the CLAUDE_MEM_MODE setting.

This option controls both:

  • The workflow behavior (e.g. code, chill, investigation)
  • The language used in generated observations

How to Configure

Edit your settings file at ~/.claude-mem/settings.json:

{
  "CLAUDE_MEM_MODE": "code--zh"
}

Modes are defined in plugin/modes/. To see all available modes locally:

ls ~/.claude/plugins/marketplaces/thedotmack/plugin/modes/

Available Modes

Mode Description
code Default English mode
code--zh Simplified Chinese mode
code--ja Japanese mode

Language-specific modes follow the pattern code--[lang] where [lang] is the ISO 639-1 language code (e.g., zh for Chinese, ja for Japanese, es for Spanish).

Note: code--zh (Simplified Chinese) is already built-in — no additional installation or plugin update is required.

After Changing Mode

Restart Claude Code to apply the new mode configuration.

Development

See the Development Guide for build instructions, testing, and contribution workflow.


Troubleshooting

If experiencing issues, describe the problem to Claude and the troubleshoot skill will automatically diagnose and provide fixes.

See the Troubleshooting Guide for common issues and solutions.


Bug Reports

Create comprehensive bug reports with the automated generator:

cd ~/.claude/plugins/marketplaces/thedotmack
npm run bug-report

Contributing

Contributions are welcome! Please:

  1. Fork the repository
  2. Create a feature branch
  3. Make your changes with tests
  4. Update documentation
  5. Submit a Pull Request

See Development Guide for contribution workflow.


License

Claude-Mem is licensed under the Apache License 2.0.

We chose Apache-2.0 because durable agentic memory should be easy to embed in developer tools, local agents, MCP servers, enterprise systems, robotics stacks, and production agent harnesses.

See the LICENSE file for full details. See docs/license.md and docs/ip-boundary.md for licensing scope and the open/commercial boundary.

Note on Ragtime: The ragtime/ directory is licensed under the Apache License 2.0. See ragtime/LICENSE for details.


Support


Built with Claude Agent SDK | Works with Claude Code | Made with TypeScript


What About $CMEM?

$CMEM is a solana token created by a 3rd party without Claude-Mem's prior consent, but officially embraced by the creator of Claude-Mem (Alex Newman, @thedotmack). The token acts as a community catalyst for growth and a vehicle for bringing real-time agent data to the developers and knowledge workers that need it most. $CMEM: 2TsmuYUrsctE57VLckZBYEEzdokUF8j8e1GavekWBAGS

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