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The Kokonut Framework is the shared methodology behind Kokonut farms.

The Kokonut Framework gives farms a common baseline for:

• describing the farm and its context;
• planning development;
• applying regenerative principles;
• structuring value and impact questions;
• recording operational activity;
• producing reviewable evidence;
• learning across farms over time.

Its purpose is not to make every farm identical. Its purpose is to make farms interoperable enough that local operators, contributors, reviewers, capital participants, researchers, and software systems can work from compatible information.

The goal is interoperability, not uniformity: shared structure where coordination benefits from it, local adaptation where land, people, markets, and regulation differ.

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The Framework in one sentence

Describe the farm consistently → plan through shared phases → operate locally → record what happened → review the evidence → learn and improve.

That sequence is more durable than any particular tool, chain, dashboard, or governance mechanism. The Framework connects those steps. It does not collapse them into one authority.

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What the Framework standardizes — and what it does not

This boundary is central to the Framework. A shared schema can make records compatible. It does not make the farm a franchise. A shared development phase can organize work. It does not make every landscape move at the same speed. A shared evidence standard can make a claim easier to inspect. It does not make the claim automatically true.

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The current Framework building blocks

The Framework is easier to navigate through the components that are actually documented across this section.

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Four development phases organize the farm lifecycle

The Framework currently uses four development phases. Phase IV is not a finish line after which measurement stops. Evidence and learning should continue throughout farm operations.

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The Common Data Schema is the baseline — not the approval

The current Common Data Schema defines 13 required fields. Its purpose is to make a farm record structured enough for multiple actors and systems to work with it. That can support:

• farm intake;
• proposal preparation;
• data ingestion;
• comparison;
• MRV linking;
• reporting;
• analysis;
• agent workflows.

It should not be interpreted as:

“13 fields completed = farm approved, funded, verified, or investment-ready.”

Those are separate decisions. A complete record can still contain:

• weak assumptions;
• unresolved legal questions;
• poor economics;
• insufficient evidence;
• operating risks;
• missing reviewer approval.

Structure makes a farm easier to inspect. It does not substitute for judgment.

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Regenerative principles guide practice without becoming a recipe

The Framework documents five regenerative principles as the shared agricultural baseline. They help organize practice around areas such as:

• soil cover and soil protection;
• biodiversity and diversity;
• perennial and multi-layer systems;
• animal integration where appropriate;
• on-site or biologically oriented inputs and nutrient cycling.

Those principles should guide design and review. They should not be interpreted as evidence that a desired ecological outcome already occurred. For example: The last step requires more than documenting the intention.

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Value frameworks help ask better questions

The Framework does not reduce farm value to revenue alone.

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Pillars of Value

The six Pillars of Value ask:

1. WHAT value is being created?
2. WHO experiences the value?
3. HOW MUCH changes?
4. CONTRIBUTION — what changed because of this intervention?
5. RISK — what may not happen or may not persist?
6. PUBLIC GOODS — what value extends beyond the immediate transaction?

These are analytical questions. They do not automatically calculate or certify impact.

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8 Forms of Capital

The Framework also uses eight capital categories:

• Natural;
• Financial;
• Social;
• Human;
• Material;
• Intellectual;
• Cultural;
• Health.

The purpose is to make different forms of value visible without pretending they are interchangeable. A stronger financial result does not automatically compensate for ecological damage. A biodiversity intervention does not automatically prove social benefit.

The Framework can hold multiple forms of value in the same analysis without declaring one form sovereign over all the others.

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MRV supplies the evidence layer

The Framework and MRV are related but different. The Framework defines shared structures, methods, phases, and interpretation tools. MRV defines how operational observations become reviewable evidence. The current MRV sequence is:

observe → structure → review → publish → attest when useful → interpret

That means the Framework should not assume a fixed pipeline where every record must move through IPFS and EAS. Different evidence may use different storage and publication paths. EAS can add public provenance for significant records. It does not turn a weak source record into scientific truth.

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Kokonut Intelligence implements data infrastructure around the Framework

Kokonut Intelligence is not the Framework itself. It provides infrastructure that can operationalize Framework concepts through:

• canonical farm records;
• operational events;
• review states;
• analytics;
• forecasting;
• reports;
• scoring;
• EAS integration on Celo;
• agent-access workflows.

The distinction matters. A methodology can remain valid even if a software implementation changes. And a software score should not become a new methodology merely because it can be calculated.

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Governance uses the Framework — it does not own the Framework’s subject matter

The Framework can make a farm proposal easier to evaluate. That does not mean every Framework question belongs to the Moloch DAO. Different decisions have different authorities. A Moloch proposal may fund a Framework improvement. That vote does not make token holders the scientific, agronomic, or technical authority over the content of the method. Read the DAO Architecture →

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Who uses the Framework

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Adelphi is the first live reference implementation

Adelphi is where the Framework has its clearest real-world reference. It combines:

• locally operated land;
• farm-development phases;
• regenerative practice;
• crop and infrastructure systems;
• public-goods funding history;
• forecasts and actual records;
• MRV;
• Kokonut Hub publication;
• governance and contributor coordination.

That makes Adelphi useful for learning. It does not make Adelphi a universal template. Explore Adelphi →

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Terra Viva is the next replication test

The current documentation identifies Terra Viva as the next major test of Framework portability. Terra Viva is described as roughly 50,000 m² of adjacent land under agreement entering: Phase I — Planning & Preparation That status matters. Terra Viva is useful because it can help answer questions that Adelphi alone cannot:

• Which Framework fields transfer cleanly?
• Which methods need local adaptation?
• Which assumptions were specific to Adelphi?
• How should multi-farm comparison work?
• Which evidence can be normalized?
• Where does governance need to remain farm-specific?

It is not yet evidence of successful multi-farm replication.

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What the Framework can support — and what it cannot guarantee

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Current maturity of the Framework

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Framework principles for this documentation sprint

As the Framework pages are improved, they should preserve these rules.

1. Interoperability, not uniformity.
2. Local operators retain local operating authority.
3. Shared structure does not equal automatic approval.
4. Implemented practice does not equal measured outcome.
5. Forecast does not equal actual.
6. Attestation does not equal scientific certification.
7. Framework methodology and software implementation remain distinguishable.
8. Governance authority stays scoped to the decision being made.
9. Public-goods and economic arrangements should follow the approved farm-specific arrangement rather than an unsupported universal rule.
10. Replication claims should grow only as multi-farm evidence grows.

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Read the Framework in this order

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Navigate the Framework

The Framework succeeds when the next farm can start with more shared knowledge and better coordination than the first one—without losing the local judgment that makes a farm real.