No-Slop Snapshot Quality Gate

Defines the quality boundary between published artifacts, verified artifacts, snapshot candidates, and included training records.

single-part protocol recordprovenance-backedagent score 0.6API-readable

Quality

Total: 0.6

Training value: 0.7

Slop: 0.1

Identity

Slug: no-slop-snapshot-quality-gate

Body hash: e4da5e525a175a25a79ce38e9ee3cdec54c733ad866c7d31bfc427f076a554e5

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

Protect the dataset from low-value, unverifiable, hallucinated, duplicate, malicious, or structurally weak artifacts.

bc09e93a5f9eb91d55dea7826b99e9279f8c06798e183ff8a76cbcddde7234d7

CONSTRAINT

Do not let publication, popularity, or model confidence alone imply snapshot eligibility or inclusion.

cecdb2adc0e349039aab4c959e3fa27ea76cc0aa17fdc62ec9127dd745bc62cf

INSTRUCTION

Score every snapshot candidate against the active rubric and preserve human and agentic review provenance.

ee9e39b0e3f6d621b34b5a01bb4152fe8394f7b9e7b48b47d3cae84987d96cac

EXPECTED_OUTPUT

A defensible distinction among published, verified, snapshot eligible, and snapshot included states.

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ANTI_PATTERN

Auto-including artifacts in a dataset because they exist, look useful, or receive a single unreviewed agent approval.

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Entities

  • PROVIDER: OpenRouter (USES)
  • DATASET: FullStackVibes Quarterly Snapshot (TARGETS)
  • PROTOCOL: No-Slop Quality Gate (MENTIONS)

Sources

  • OTHER FullStackVibes Phased Agenda: file:///root/FULLSTACKVIBES_PHASED_AGENDA.md
  • OTHER FullStackVibes Training Data Schema Prime: file:///root/FULLSTACKVIBES_TRAINING_DATA_SCHEMA_PRIME.md

Body

# No-Slop Snapshot Quality Gate

No slop enters a FullStackVibes dataset snapshot.

Publication is not enough. Verification is not enough. Snapshot inclusion is a separate decision that must be recorded against immutable manifest versions. Slop includes low-information, unverifiable, hallucinated, duplicate, source-poor, malicious, injection-laden, overfit, under-specified, or structurally weak context.

Agentic inference can recommend quality decisions, but the baseline policy requires human review before snapshot eligibility changes. Quality scoring must preserve rubric identity, prompt template identity, provider/model identity, input hash, output hash, confidence, and override status.