# m2-market

**Working title** for the M2 Marketplace — the platform for packaged work. Operators package
repeatable outcomes as installable **Solutions**, sell them to other operators for **M2
credits**; a **Solution Scout** proposes the right package in-session at the moment of need;
Hermes composes build-vs-install proposals with cost evidence. *"The unit is not software.
The unit is completed work."*

## Status: spec discovery (kickstarted 2026-07-01)

| Doc | Purpose |
|---|---|
| [CONCEPT.md](CONCEPT.md) | Unified concept paper v0.2 (pitch v0.1 + fedlearn rails + cargstore + Scout) |
| [context/SYSTEM-MAP.md](context/SYSTEM-MAP.md) | How m2-gpt, agent.memory.system, m2o/Coolify, Hermes/OpenClaw actually connect (verified) |
| [specs/](specs/) | Spec-kit style discovery output lands here (spec → clarify → plan → tasks) |

## The one-paragraph architecture

Marketplace = **protocol + registry, not one app**. Forgejo (`git.machinemachine.ai`) is the
system of record (listings = releases, review = PRs, veto = labels); **memory-api** indexes it
semantically (`market:catalog` partition, same BGE-M3 hybrid search as agent memory);
**cargstore** (revived → M2 Store) renders it in-desktop; **Hermes** speaks it in-session
(backed by **m2-gpt**, whose tenant keys/budgets/metering seed the **m2-ledger** credit
economy); the **fedlearn sync path** installs it (signed, idempotent, tenant-aware). The only
genuinely new services: `m2-ledger` (append-only internal credits) and the `Solution Scout`
(per-desktop watcher → semantic match → toast + deep link → few-clicks deploy).

## Dependencies
- **fedlearn MVP** (in execution): schemas, `m2/m2-core`, memory-api auth, curator+veto,
  `m2-core-sync`. The marketplace is its commercial tier — same rails, plus price/seller/license.
- Existing: m2-gpt (tenancy+metering) · agent.memory.system (catalog+evidence) · m2o fleet
  (surface) · cargstore (storefront) · Forgejo (registry) · Coolify (deploys).

## Open forks (need operator decision — CONCEPT.md §14)
1. Ledger substrate: standalone m2-ledger , could become a crypto ledger that is managed in extended m2-gpt billing 
2. Pricing v1: fixed per install (rec.) vs metered vs both (when applicable, sometimes othe m2o take a job for a solution)
3. Storefront: cargstore Electron revival (rec.) vs web-first vs both MVP electron app that connects to coolify or other parts with credentials from m2-gpt
4. Scout host: standalone supervised watcher (rec.) vs Hermes plugin vs herdr plugin (explore solution)
5. Seed Solutions: mm-pdf · agent-scaffold · competitor-scan (proposed)
6. Platform cut % + starter grant (defaults 10% / 100 cr)

## Next steps
1. Resolve the 6 forks (or accept recommendations).
2. Run spec discovery per subsystem → `specs/` (spec-kit or GSD; herdr herd like the fedlearn
   discovery: one angle-specialist per subsystem — ledger, catalog, store UI, Scout, packaging).
3. Wait for fedlearn MVP convergence (schemas + sync path are hard inputs to `solution.schema`).