Thriving 
TS Multi-instance WhatsApp platform — passive listener, conversational chatbot, and autonomous AI agent runtimes behind Baileys v7. Fleet console, 162 MCP tools, durable message delivery, and WhatsApp poll-based decision bridge.
// readme
A multi-instance WhatsApp platform that runs three fundamentally different runtimes — passive listener, conversational chatbot, and autonomous AI agent — behind one Baileys v7 connection per line. Ships with a fleet management console for provisioning, monitoring, and operating all instances from a single dashboard.
One process per instance. One SQLite database per instance. 168 MCP tools (165 always-registered + 3 conditionally-registered: knowledge_search when Pinecone config, credentials, and profiles are usable, emit_heal_result on non-sandboxed instances with at least one configured control-plane peer, and memory_write when a Pinecone key and index are configured). No backend build step — the runtime executes TypeScript directly via Node --experimental-strip-types; only the React console builds (to the repository-level dist/). Probably too many MCP tools.
Each WhatsApp number gets its own isolated process with its own runtime mode:
| Mode | What Happens | Use Case |
|---|---|---|
| passive | Stores messages. Does nothing else. Manual read/reply via MCP tools. | Personal number — just want the data accessible |
How much a project earns versus how much attention it actually gets. Above 50 means the work is outrunning its audience. Recomputed nightly from commit velocity, contributor effort, issue resolution, fork utility, release cadence, and project maturity — divided by a logarithmic reach factor.
score = signal / reach
signal = 0.25·commit_velocity // commits in last 90 days (cap 30)
+ 0.20·contributor_work // unique authors × velocity (cap 100)
+ 0.20·issue_resolution // closed ÷ total issues
+ 0.20·fork_ratio // forks ÷ stars (proxy for real usage)
+ 0.10·release_cadence // releases in 90 days (cap 3)
+ age_bonus // +0 to +0.30 after 6 months
+ homepage_bonus // +0.05 if homepage is set
reach = log₁₀(stars + watchers + 10)█ Is the project alive and maintained right now? A 0–100 pulse recomputed nightly from commit recency, rhythm, how fast issues close, and how quickly PRs get merged.
health = 0.35·recency // days since last commit (90d decay)
+ 0.25·cadence // commit rhythm consistency
+ 0.20·issue_health // closed ÷ total issues
+ 0.20·pr_health // merged ÷ total PRs█ The colour and label on every card come straight from the health score.
Healthy 80 – 100 active, responsive, regular releases
Stable 60 – 79 maintained, steady, no alarms
Quiet 40 – 59 slowing down — watch this one
At Risk 0 – 39 going dark · candidate for rescue█ Tags are independent behavioral signals computed nightly. A project can hold multiple at once. They drive the home page sections.
solo_builder one person holds > 80% of commits (last 180d)
needs_contributors has open "help wanted" or "good first issue" labels
hidden_gem < 100 stars · active in last 3 months · documented
legacy_hero repo > 5 years old · committed this year
fork_magnet forks/stars > 0.5 · used as template or dependency
release_machine 5+ releases in the last 90 days
under_pressure > 10 open issues · ≤ 2 contributors · health ≥ 60
community_watch watchers > stars · devs tracking before the public
community_hub GitHub Discussions enabled · > 20 discussions
funded maintainer has active funding channel█ Stars are an outcome, not effort. A project with 8 stars and daily commits is doing more interesting work than one coasting on 8k. We measure the building, then divide by the attention already received — so the genuinely undervalued rise to the top.
// stars = lagging indicator
// commits = leading indicator
// we rank by the leading one█