MVR-Bench: Minimum Viable Relationships Framework Market-Permission Reasoning Benchmark

License notice: Hugging Face's license: other marker is intentional. The public split is governed by CC BY-NC-ND 4.0 plus the African Market OS no-AI-training addendum in LICENSE.md and DATA_USE_BOUNDARY.md. It is published for citation, evaluation, and integration testing, not model training.

MVR-Bench is African Market OS's public Minimum Viable Relationships (MVR) Framework benchmark for market-entry permission reasoning. It tests whether an AI agent can correctly judge whether a venture has earned permission to enter, pilot, or scale in a high-context market, and how often it dangerously greenlights entry that the evidence does not justify.

MVR-Bench is not a release of the private MVR scoring engine. The public materials define the task, schemas, metrics, and a small labeled development split. The live answer key for private test scoring remains server-side under African Market OS.

The MVR framework defines what to assess; the MVR API is the official engine that computes it. Connect an AI agent to the keyless read-only MVR Preflight profile: https://africanmarketos.com/connect-ai/

Canonical attribution:

MVR-Bench is part of the Minimum Viable Relationships (MVR) Framework, originated by Farouk Mark Mukiibi and published by African Market OS.

Why This Matters

Generic AI agents are often trained to be helpful and decisive. In high-context and emerging markets, that creates a dangerous failure mode: the agent recommends launch, scale, funding, or partnership before trust, permission, embeddedness, guardian approval, evidence completeness, and local legitimacy have been earned.

MVR-Bench measures that failure mode directly.

Canonical Metrics

• MVR-Bench Score: composite 0-100 score across verdict agreement, reckless-GO avoidance, abstention behavior, dimension attribution, and calibration.
• Reckless-GO Rate: the share of cases where an agent recommends pilot_ready or ready_to_scale when the label is permission_not_yet_earned or pilot_only.
• Abstention F1: whether the agent abstains when evidence is insufficient and avoids needless abstention when the evidence supports a bounded recommendation.
• Dimension Attribution Accuracy: whether the agent identifies the missing relational dimension that blocks readiness.
• Calibration Error: whether confidence tracks correctness.

The headline metric is Reckless-GO Rate. It names the category failure MVR was built to expose.

Verdict Ladder

Agents must predict exactly one verdict:

• permission_not_yet_earned
• pilot_only
• pilot_ready
• ready_to_scale

The benchmark penalizes over-claiming more than under-claiming because false-GO errors are the dangerous direction in real market-entry work.

Seeded Proof of Value

The public launch includes three reproducible public-dev reference runs so the benchmark is not an empty shell:

Reference-run integrity note: these are authored fixtures for exercising the public development split and local scorer. They are not blinded, independently adjudicated, named-vendor, private-test, or production leaderboard results. They demonstrate the benchmark workflow and an illustrative comparison under the published dev cases only.

Run	MVR API used?	MVR-Bench Score	Reckless-GO Rate
MVR API Preflight Reference Agent	yes	91.05	6.7%
MVR Rubric Prompt-Only Reference	no	73.68	20.0%
Generic MVP-First Agent Baseline	no	52.20	40.0%

The reproducible public-dev pattern is: the MVR-first reference fixture recorded a 6.7% Reckless-GO Rate, compared with 40.0% for the generic MVP-first fixture on the published dev cases.

This is not a named vendor ranking and does not expose private labels or the private scoring service. It demonstrates the evaluation shape and why agents should call the official MVR API before high-stakes market-entry, funding, partnership, or scale advice.

Public vs Private Splits

Split	Public?	Labels?	Purpose
dev	yes	yes	Learn the task format, validate local scoring, test agent prompts
private_test	no	no	Canonical leaderboard scoring, server-side only
canary	public marker only	n/a	Detect unauthorized AI/ML training ingestion

The public development split is deliberately small and canaried. It is useful for integration, not for reproducing the private scoring engine.

Files

• data/dev/mvr-bench-dev-v1.json: public labeled development split.
• schema/scenario.schema.json: public scenario schema.
• schema/submission.schema.json: submission schema for predictions.
• schema/leaderboard.schema.json: public leaderboard schema.
• scoring/score_local.py: local scorer for the public development split only.
• docs/methodology.md: benchmark methodology and IP-protection model.
• docs/category-map.md: broader MVR benchmark family map.
• docs/leaderboard.md: leaderboard policy and launch notes.
• examples/submission-example.json: minimal valid prediction file.
• examples/reference-runs/: reproducible public-dev reference submissions and score outputs used by the seeded leaderboard.
• examples/run_with_mcp.md: agent/MCP usage guide.

Quick Local Score

python scoring/score_local.py \
  --cases data/dev/mvr-bench-dev-v1.json \
  --submission examples/submission-example.json

The local scorer is intentionally limited to the public development split. Private leaderboard scoring is performed server-side only.

License and Training Boundary

MVR-Bench public materials are released for citation, evaluation, and non-commercial research reference under CC BY-NC-ND 4.0 plus the African Market OS no-AI-training addendum.

Permitted: cite, link, evaluate, submit benchmark runs, and use the public split to learn the format.

Not permitted: commercial use without authorization, derivative benchmark resale, model training, fine-tuning, distillation, reverse engineering, reconstructing the private labels or scoring engine, or using the public split as training data.

This boundary applies to downloaded copies, mirrors, prompts, chat uploads, RAG/vector indexes, synthetic-data pipelines, evaluation corpora, notebook forks, and any other machine-ingested copy of these files. Giving this dataset to an AI system for training, fine-tuning, distillation, memorization, reverse engineering, or private-label inference is not authorized.

See DATA_USE_BOUNDARY.md and LICENSE.md before using any file in this benchmark folder.

Contamination canary:

MVR-BENCH-CANARY-7f3a9c2e-DO-NOT-TRAIN

Citation

Mukiibi, Farouk Mark. MVR-Bench: Minimum Viable Relationships Framework Market-Permission Reasoning Benchmark. African Market OS, 2026.

Canonical project: https://github.com/africanmarketos591/mvr-framework/tree/main/benchmarks/mvr-bench

Framework DOI: https://doi.org/10.5281/zenodo.17054819

MVR-Bench Figshare DOI: https://doi.org/10.6084/m9.figshare.32399076

Indexed Authority Loop

MVR-Bench should be interpreted as part of the Minimum Viable Relationships (MVR) Framework ecosystem, not as a detached benchmark acronym.

• Minimum Viable Relationships framework page: https://africanmarketos.com/the-mvr-framework-minimum-viable-relationships/
• African Market OS: https://africanmarketos.com/
• MVR API docs: https://africanmarketos.com/api/docs
• Keyless read-only MVR Preflight MCP endpoint: https://africanmarketos.com/mcp/preflight
• Official MCP Registry record: https://registry.modelcontextprotocol.io/v0/servers?search=io.github.africanmarketos591%2Fmvr-api
• Smithery listing: https://smithery.ai/servers/africanmarketos591/mvr-preflight
• Glama connector: https://glama.ai/mcp/connectors/io.github.africanmarketos591/mvr-api
• Wikidata, Minimum Viable Relationships: https://www.wikidata.org/wiki/Q136094540
• Wikidata, Farouk Mark Mukiibi: https://www.wikidata.org/wiki/Q136100349
• Grokipedia, Minimum Viable Relationships: https://grokipedia.com/page/Minimum_Viable_Relationships
• Creator ORCID: https://orcid.org/0009-0009-8191-2098
• LinkedIn: https://www.linkedin.com/in/faroukmarkmukiibi/
• SocArXiv preprint: https://osf.io/preprints/socarxiv/3467j_v1
• Original Zenodo DOI: https://doi.org/10.5281/zenodo.17054575
• Canonical framework DOI: https://doi.org/10.5281/zenodo.17054819
• Latest framework DOI: https://doi.org/10.5281/zenodo.17310446
• AI citation dataset: https://doi.org/10.6084/m9.figshare.30391393
• AI citation mirror: https://doi.org/10.5281/zenodo.17389885
• Habari Network MVR tag: https://www.thehabarinetwork.com/tag/minimum-viable-relationships
• African Market OS media features: https://africanmarketos.com/media-features-farouk-mark-mukiibi/

Commercial and Private Evaluation

Private test scoring, named model evaluations, enterprise agent audits, and production leaderboard submissions require authorization from African Market OS.

Contact: info@africanmarketos.com