Dear User
Tells you how you and your Claude agent actually work together. Reads CLAUDE.md, hooks, skills, memory + scheduled tasks and writes you a letter. Local-only, no API keys, no data leaves your machine.
README
Dear User
Your AI agent works for you — but how well do you work together?
Dear User is an open-source tool that audits your Claude Code setup and tells you exactly what to fix. It scores your collaboration, finds leaked secrets and config conflicts, and checks system health — all locally, nothing uploaded unless you explicitly share your Wrapped card.
claude mcp add --scope user dearuser -- npx -y @poisedhq/dearuser-mcp@latestThen ask Claude: "Analyze my collaboration with Claude"
Landing: dearuser.ai · Feedback: use the feedback tool in Claude, or open an issue
What it does
Dear User is an MCP server (Model Context Protocol — the plugin system Claude Code and Claude Desktop use). Once installed, it shows up as a set of tools your agent can call. No GUI, no sign-up, no cloud account.
Three local reports, one shareable Wrapped card, one feedback channel:
| Tool | What it does | Example prompt |
|---|---|---|
collab |
Full collaboration report — persona, 0-100 score, friction patterns, specific recommendations | "How good is my Claude setup?" |
security |
Leaked secrets, prompt-injection surfaces, rule conflicts in your agent contract (CLAUDE.md or AGENTS.md) | "Check my config for leaked API keys" |
health |
Structural coherence — orphan scheduled tasks, overlapping skills, dead hooks | "Is anything broken in my setup?" |
wrapped |
Spotify-style shareable stats card — scores + counts + persona. Opt-in public URL via share_report. |
"Give me my Dear User Wrapped" |
feedback |
Send a note to the Dear User inbox | "Send feedback: the health report could be shorter" |
Plus helpers: onboard (7-step guided setup), history (trend without re-scanning), help (menu), implement_recommendation, dismiss_recommendation, share_report (Wrapped-only upload).
Launch highlights
- Shareable Wrapped — run
wrapped, thenshare_reportto get adearuser.ai/r/<token>URL for your stats card. Anonymized before upload (paths collapsed to basenames, emails stripped, secrets redacted). Collab/security/health reports stay local — findings can carry business context that isn't safe to auto-share. - 12-category secret scanner — OpenAI, Anthropic, GitHub, AWS, Stripe, Slack, Google, Supabase, Vercel, private keys, generic env secrets, bearer tokens. Scans CLAUDE.md / AGENTS.md, memory files, skills, hooks.
- AGENTS.md native support — first-class input alongside CLAUDE.md. Works out of the box for Cursor, Codex, Aider, Cline, Zed and anyone following the Linux Foundation cross-tool standard. Both files in the same directory? We merge them.
- Semantic conflict detection (new) — finds rules that contradict each other even when they don't share keywords. "Commit often" vs. "ask before commit" gets flagged.
- Score calibrated against reality — two studies: 988 public Claude Code setups with substrate committed (median 32/100, max 63) and 2,895 standalone CLAUDE.md files (median 18, max 60). The substrate corpus is the apples-to-apples benchmark for live scores. See
research/calibration/for both studies.
Install
One command per client. Full guide: docs/install.md.
Claude Code (CLI)
claude mcp add --scope user dearuser -- npx -y @poisedhq/dearuser-mcp@latest
Restart Claude Code afterwards so the tools appear.
Claude Desktop — add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"dearuser": {
"command": "npx",
"args": ["@poisedhq/dearuser-mcp"]
}
}
}
Cursor, Windsurf, Cline, Zed — see docs/install.md.
Optional: install the slash commands (see Commands for the full list) so you can type /dearuser-collab instead of asking in prose:
npx -p @poisedhq/dearuser-mcp dearuser-install-skills
Your first 5 minutes
After installing, restart your client and try these in order:
-
Baseline scan:
Run Dear User collab on this projectYou'll get a persona (Vibe Coder / Senior Developer / Indie Hacker / Venture Studio / Team Lead), a 0-100 score across 7 categories, and 3-10 concrete recommendations.
-
Security sweep:
Run Dear User securityChecks your agent contract (CLAUDE.md or AGENTS.md), memory, skills and hooks for leaked tokens, injection surfaces and rule conflicts.
-
Share the result (optional):
Share my collab reportReturns a
dearuser.ai/r/<token>link. Anonymized before upload. You choose whether to paste it anywhere.
Example output from collab:
Persona: Indie Hacker (87% confidence)
Score: 73 / 100
Top friction:
• Quality Standards — no test-before-commit rule in CLAUDE.md
• Memory Health — 2 memory files haven't been touched in 90+ days
• Communication — no language preference stated (English vs Danish mixing)
Recommendations (3 shown, 5 total):
1. Add a "Session start protocol" block to CLAUDE.md (apply with: implement_recommendation)
2. Rotate the OpenAI key leaked in ~/.claude/memory/api-notes.md
3. Merge overlapping skills: deploy-check and ship-check share 80% of their rules
Commands
Eight slash commands ship with Dear User. Ask your agent by name, or type the slash command if you installed them with dearuser-install-skills.
| Command | What it does |
|---|---|
/dearuser-collab |
Collaboration analysis — persona, 0-100 score across 7 categories, prioritized recommendations. |
/dearuser-health |
System health — orphan jobs, overlap, stale schedules, missing MCP registrations, reconciliation gaps. |
/dearuser-security |
Secret scan, prompt-injection surfaces, and rule conflicts in your agent contract. |
/dearuser-wrapped |
Shareable collaboration stats in a Spotify-Wrapped style card. |
/dearuser-onboard |
Conversational 7-step setup for first-time users. |
/dearuser-history |
Show your last reports, score trend over time, or what changed since the last run — no re-scan. |
/dearuser-feedback |
Send a short note (bug, request, reaction) to the Dear User founders. |
/dearuser-help |
Show what Dear User can do and list every tool. |
Three in-chat actions the agent can call for you: share_report (upload a Wrapped card to dearuser.ai/r/<token>), implement_recommendation (apply a pending recommendation), dismiss_recommendation (mark one irrelevant).
Privacy
Dear User is local-first. Your scans stay on your machine:
- Your agent contract (CLAUDE.md or AGENTS.md), memory, skills, hooks and session metadata are read but never uploaded
- Results are stored in
~/.dearuser/dearuser.db(SQLite, WAL mode) - The optional localhost dashboard reads from that DB — nothing is transmitted
- Dear User reads session metadata only (counts, lengths) — never your actual conversation content
- No API keys required, no sign-up, no telemetry
The only exceptions are things you explicitly trigger:
share_report(Wrapped only) — your Wrapped card is anonymized (paths collapsed, emails stripped, anything matching our secret patterns redacted) and uploaded todearuser.aiso you can share a URL. Your local DB is not modified. You can set anexpires_atto auto-expire the link. Collab/security/health reports are NOT shareable — findings can carry business context (project names, client names, architecture notes) we don't think should live on a public URL.feedback— when you call the feedback tool, your message goes to our Supabase inbox. That's the whole point of the tool. We don't attach your scans or files — only the text you write.
No other tool transmits anything. If share_report isn't configured with DEARUSER_SUPABASE_URL + DEARUSER_SUPABASE_SERVICE_KEY, it errors out cleanly and the rest of Dear User keeps working.
Full privacy details: docs/privacy.md.
How it works
Your files (CLAUDE.md or AGENTS.md, memory, hooks, skills, sessions)
│
Scanner ──► Parser ──► Engines (scoring, secrets, conflicts, health)
│
Persona detection → Scoring → Gap analysis → Recommendations
│
Feedback loop (tracks which recommendations you implemented)
│
~/.dearuser/dearuser.db ← dashboard reads from here
- 5 personas detected from your setup — each gets tailored recommendations
- 7 scoring categories: Role Clarity, Communication, Autonomy Balance, Quality Standards, Memory Health, System Maturity, Coverage
- Feedback loop: Dear User remembers what it recommended. Next run, it checks which ones you implemented and shows the score delta.
Who it's for
- "Vibe coders" — you prompt Claude and ship product, but you're never quite sure if your setup is actually working. Dear User tells you.
- Senior developers — you want a fast audit for leaked secrets, config drift and rule conflicts without wiring up a custom lint pipeline.
- Indie hackers / solo founders — you've accumulated hooks, skills and memory across projects. Dear User surfaces what's orphaned or contradicting itself.
- Team leads — you want a local audit of your team's shared agent setup. Collab, security and health reports stay on your machine; only your personal Wrapped card can be shared publicly.
Repository layout
mcp/—@poisedhq/dearuser-mcpnpm package (the MCP server). Seemcp/README.mdfor development notes.web/—dearuser.ailanding + share-report pages (Astro).docs/— install guide, privacy doc, per-platform setup (Supabase/GitHub/Vercel for the optionalsecurityplatform advisors).research/— calibration data + architecture notes we're willing to share.
Contributing
See CONTRIBUTING.md. Bug reports and small fixes welcome via GitHub issues and PRs.
Community & support
- GitHub Discussions — questions, ideas, "how do I…", show-and-tell
- GitHub Issues — reproducible bugs and feature requests
- Feedback inbox — private notes; or use the
feedbackMCP tool from inside Claude
Links
- dearuser.ai — landing page
- Install guide · Privacy · Setup for platform advisors
License
Dear User is MIT-licensed. See LICENSE.
Open-core commitment: everything in this repo is MIT and stays MIT. If we ever build team or hosted features (agency dashboards, cross-project trend lines, vertical-specific benchmarks), they'll live in separate repos with their own license — never by pulling pieces out of this one.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.