| ---
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| pretty_name: MVR-Bench
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| license: other
|
| language:
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| - en
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| task_categories:
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| - text-classification
|
| tags:
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| - evaluation
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| - benchmark
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| - agent-evaluation
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| - abstention
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| - responsible-ai
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| - market-entry
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| - african-markets
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| - emerging-markets
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| - relational-readiness
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| - evidence-completeness
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| - market-permission
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| - minimum-viable-relationships
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| - african-market-os
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| - africanmarketos
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| - mcp
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| - mcp-server
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| size_categories:
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| - n<1K
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| configs:
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| - config_name: dev
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| data_files:
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| - split: dev
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| path: data/dev/mvr-bench-dev-v1.json
|
| ---
|
|
|
| # MVR-Bench: Minimum Viable Relationships Framework Market-Permission Reasoning Benchmark
|
|
|
| > **License notice:** MVR-Bench v1 was released under CC BY-NC-ND 4.0. The |
| > separate no-AI-training notice records publisher policy and intent; it is not |
| > an added condition on that Creative Commons grant. See `LICENSE.md` and |
| > `DATA_USE_BOUNDARY.md`. Private labels and the protected runtime are not published. |
|
|
| 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:
|
|
|
| ```text
|
| 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
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|
|
| Agents must predict exactly one verdict:
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|
|
| - `permission_not_yet_earned`
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| - `pilot_only`
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| - `pilot_ready`
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| - `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 Scorer Demonstration |
|
|
| The public launch includes three reproducible, human-authored public-dev fixtures 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 Preflight Authored Fixture | no | 91.05 | 6.7% | |
| | MVR Rubric Prompt-Only Reference | no | 73.68 | 20.0% |
|
| | Generic MVP-First Agent Baseline | no | 52.20 | 40.0% |
|
|
|
| In these authored fixtures, the MVR-preflight pattern scores 6.7% Reckless-GO and the generic MVP-first pattern scores 40.0%. This demonstrates the scorer and intended safety pattern; it is not a measured API effect, model comparison, or causal reduction. |
|
|
| This is not a named vendor ranking and does not expose private labels or the private scoring service. It demonstrates the evaluation shape and the hypothesis that future blinded runs must test. |
|
|
| ## 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
|
|
|
| ```bash
|
| 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 v1 public materials were released under CC BY-NC-ND 4.0. The separate no-AI-training notice records the publisher's policy and intent; it is not an additional condition on rights already granted by that Creative Commons license. Existing CC grants and applicable legal exceptions are not narrowed. Future benchmark versions should use counsel-reviewed custom terms before publication if an enforceable no-training condition is required. |
|
|
| 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:
|
|
|
| ```text
|
| 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
|
|
|
| ## 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
|
| |
