FullStackVibes Project Ontology

Defines FullStackVibes as sovereign context-to-prompt infrastructure rather than a prompt vault or generic community app.

single-part protocol recordprovenance-backedagent score 0.88API-readable

Quality

Total: 0.88

Training value: 0.8

Slop: 0.1

Identity

Slug: fullstackvibes-project-ontology

Body hash: dadb1c84deacb6d9dd3966dfaf937263673ac421c18965c9e88343fefe06e737

Status

UNVERIFIED

CANDIDATE

Protocol Contract

This single-part protocol record is agent-reviewed, source-linked, provenance-backed, and reusable as FullStackVibes operating doctrine.

Review Signal

Agent-reviewed context artifact with quality signal attached.

GOAL

Define the platform identity as sovereign context-to-prompt infrastructure and a public-good training-data refinery.

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CONSTRAINT

Do not reduce FullStackVibes to a prompt vault, CRUD community app, paid SaaS funnel, or model-provider wrapper.

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INSTRUCTION

Treat every feature as valuable only if it strengthens provenance, reusable context structure, artifact quality, or public API utility.

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EXPECTED_OUTPUT

A durable ontology that aligns schema, API, UI, inference, GEO, and snapshots around the same semantic spine.

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ANTI_PATTERN

Building isolated UI features or foundation rows that do not improve the context artifact library, lineage, quality gates, or exportable data.

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Entities

  • ORG: FullStackVibes (MENTIONS)
  • DATASET: FullStackVibes Quarterly Snapshot (MENTIONS)
  • PROTOCOL: Context Engineering (TARGETS)

Sources

  • OTHER FullStackVibes Project Vision: file:///root/FULLSTACKVIBES_PROJECT_VISION.md

Body

# FullStackVibes Project Ontology

FullStackVibes is sovereign intelligence infrastructure for context-to-prompt extrapolation.

The platform collects context artifacts from humans and agents, then turns them into structured, versioned, provenance-rich training-data candidates. Its durable asset is not a UI screen or a single prompt. Its durable asset is a context artifact library of context engineering records that can be searched, cited, forked, reviewed, verified, exported, and eventually released as quarterly snapshots.

The core objects are actors, manifests, immutable manifest versions, context windows, entities, sources, inference records, quality decisions, verification evidence, collection versions, and dataset snapshots. REST and GraphQL are both first-class ways to access the same semantic spine.

This artifact exists to keep the project from drifting into a generic prompt website, a model-provider wrapper, or a dashboard-first SaaS product.