46 lines
3 KiB
Markdown
46 lines
3 KiB
Markdown
# m2-market
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**Working title** for the M2 Marketplace — the platform for packaged work. Operators package
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repeatable outcomes as installable **Solutions**, sell them to other operators for **M2
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credits**; a **Solution Scout** proposes the right package in-session at the moment of need;
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Hermes composes build-vs-install proposals with cost evidence. *"The unit is not software.
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The unit is completed work."*
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## Status: spec discovery (kickstarted 2026-07-01)
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| Doc | Purpose |
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| [CONCEPT.md](CONCEPT.md) | Unified concept paper v0.2 (pitch v0.1 + fedlearn rails + cargstore + Scout) |
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| [context/SYSTEM-MAP.md](context/SYSTEM-MAP.md) | How m2-gpt, agent.memory.system, m2o/Coolify, Hermes/OpenClaw actually connect (verified) |
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| [specs/](specs/) | Spec-kit style discovery output lands here (spec → clarify → plan → tasks) |
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## The one-paragraph architecture
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Marketplace = **protocol + registry, not one app**. Forgejo (`git.machinemachine.ai`) is the
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system of record (listings = releases, review = PRs, veto = labels); **memory-api** indexes it
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semantically (`market:catalog` partition, same BGE-M3 hybrid search as agent memory);
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**cargstore** (revived → M2 Store) renders it in-desktop; **Hermes** speaks it in-session
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(backed by **m2-gpt**, whose tenant keys/budgets/metering seed the **m2-ledger** credit
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economy); the **fedlearn sync path** installs it (signed, idempotent, tenant-aware). The only
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genuinely new services: `m2-ledger` (append-only internal credits) and the `Solution Scout`
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(per-desktop watcher → semantic match → toast + deep link → few-clicks deploy).
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## Dependencies
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- **fedlearn MVP** (in execution): schemas, `m2/m2-core`, memory-api auth, curator+veto,
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`m2-core-sync`. The marketplace is its commercial tier — same rails, plus price/seller/license.
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- Existing: m2-gpt (tenancy+metering) · agent.memory.system (catalog+evidence) · m2o fleet
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(surface) · cargstore (storefront) · Forgejo (registry) · Coolify (deploys).
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## Open forks (need operator decision — CONCEPT.md §14)
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1. Ledger substrate: standalone m2-ledger , could become a crypto ledger that is managed in extended m2-gpt billing
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2. Pricing v1: fixed per install (rec.) vs metered vs both (when applicable, sometimes othe m2o take a job for a solution)
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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
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4. Scout host: standalone supervised watcher (rec.) vs Hermes plugin vs herdr plugin (explore solution)
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5. Seed Solutions: mm-pdf · agent-scaffold · competitor-scan (proposed)
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6. Platform cut % + starter grant (defaults 10% / 100 cr)
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## Next steps
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1. Resolve the 6 forks (or accept recommendations).
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2. Run spec discovery per subsystem → `specs/` (spec-kit or GSD; herdr herd like the fedlearn
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discovery: one angle-specialist per subsystem — ledger, catalog, store UI, Scout, packaging).
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3. Wait for fedlearn MVP convergence (schemas + sync path are hard inputs to `solution.schema`).
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