---
title: "KNOBE Seed v1.0"
subtitle: "A self-attesting protocol helper for teaching, bootstrapping, and starting a grove"
tagline: "KNOBE preserves objecthood under compression."
author: David Kyle
is_seed: true
seed_version: "1.0"
content_type: protocol
spec_version: "1.0"
license: CC BY 4.0
license_url: https://creativecommons.org/licenses/by/4.0/
created_date: "2026-06-15"
---

# KNOBE Seed v1.0

**Protocol:** KNOBE Protocol v1
**Author:** David Kyle, University of California, Davis
**Sealed:** 2026-06-15

*This is a Seed — a purpose-built KNOBE helper for teaching, bootstrapping, and starting a grove. It is not the protocol itself.*

---

## What KNOBE is

KNOBE is an open, plain-text protocol for agentic knowledge work. A single `.knobe.md` file carries a human-readable document together with a machine-legible, hash-sealed record of attribution, source relations, transformation history, constraints, and fidelity limits — so knowledge objects travel between people, tools, institutions, and AI agents without becoming orphaned fragments.

**In 25 words:** KNOBE is a plain-text protocol that lets knowledge objects travel with the attribution, constraints, fidelity limits, and interpretive obligations that preserve their meaning under compression.

**The core claim:** KNOBE preserves objecthood under compression.

**The diagnostic claim:** KNOBE makes it harder for compressed objects to become consequential while pretending they are whole.

**System of context, not system of record.** KNOBE does not replace the LMS, IRB, repository, archive, or HR system. It carries context between them — attribution, source relations, transformation history, fidelity limits, interpretive obligations, and quarantine posture. Its value is lower coordination cost across people, tools, institutions, and workflows.

---

## What this Seed is

A Seed is a KNOBE with `is_seed: true`. It teaches the protocol, self-describes, demonstrates dual readability, carries build recipes for tools, explains safety posture, and helps users generate new, interoperable KNOBEs. A Seed can start a **grove**: a collection of interoperable KNOBEs sharing provenance conventions, trust posture, schema expectations, and transformation norms.

A Seed is not the protocol. It is a helper object that remains a valid KNOBE itself.

Because a Seed describes the protocol that validates it, it is bound by the **Recursive Calibration Rule**: each upward meta-level must reduce rhetorical temperature and increase epistemic calibration. A meta-layer may not make stronger claims than the layer beneath it unless it adds new evidence. Claims in this Seed are classified as verified, declared, inferred, or speculative. Do not treat declared claims as verified.

---

## File structure

A `.knobe.md` file has three layers, all simultaneously present:

    ---
    {YAML frontmatter}
    ---

    {Markdown body — free-form, no schema}

    -----BEGIN KNOBE B64-----
    {Base64-encoded UTF-8 JSON payload}
    -----END KNOBE B64-----

**Markers are newline-anchored by protocol requirement.** A parser must match the marker strings only at the start of a line. Self-referential documents (like this one) may quote the markers in their body — the last well-formed payload block in the file is the canonical one.

**Layer 1 — YAML frontmatter.** Lightweight metadata readable without tooling. Required field: `spec_version: "1.0"`. Mirrors key payload fields for fast scanning.

**Layer 2 — Markdown body.** The human-readable content. No schema, no constraints. Opens in any text editor, AI assistant, browser, or markdown viewer without special software.

**Layer 3 — Payload block.** Base64-encoded UTF-8 JSON carrying the structured record: attribution, key concepts, version history, privacy level, quarantine status, parents, transformation history, accessibility fields, build recipes (for Seeds), and the integrity hash. Base64 is used because raw JSON in the body would break human readability.

---

## Minimum valid KNOBE

A KNOBE is valid when:

- Frontmatter includes `spec_version: "1.0"`
- Payload includes: `spec_version`, `title`, `summary`, `content_type`, `created_date`, `license`, `privacy_level`, `quarantine_status`, `attribution` (with at least one source bearing `author` and `contribution`), and `payload_hash`
- File structure: YAML frontmatter delimited by `---` lines; free markdown body; one payload block of Base64-encoded UTF-8 JSON bounded by newline-anchored markers

**Recommended Crystallizer defaults:** `privacy_level: "public"` · `quarantine_status: "quarantine"` · `license: "CC BY 4.0"` · `identity_status: "declared"`

---

## Carrying interpretation, not only provenance

The required fields and the lineage fields (`parents`, `transformation_history`) answer *where did this come from*. Three optional fields answer a different and equally important question: *how should the next party interpret this object, what did the originator ask of them, and what does an adaptation depend on*. These are where a KNOBE carries more than provenance. They are written to be read by the receiver — a later human, or an agent — not only by an auditor.

**`fidelity_limits`** — receiver-facing interpretive bounds. How far can this object be trusted as a representation of its source? What is it fit for, and what must not be inferred from it? A summary that drops caveats, a translation that approximates idiom, a simplification that omits edge cases — each should declare what it does and does not preserve, so a downstream reader does not over-read it. Suggested shape: `represents`, `trust_as`, `do_not_infer[]`, optional `supersedes`.

**`use_conditions`** — the originator's declared terms, carried forward so a constraint set at sealing is legible to a receiver who never met the author. Permitted and disallowed uses, required preservations, consent and quotation constraints. These inform; they do not enforce. A receiver is free to ignore them, but never able to say the object failed to carry them. Suggested shape: `license`, `permitted[]`, `requested_preservations[]`, `consent_note`.

**`accessibility[]`** — adaptation lineage. When a captioned, translated, simplified, alt-texted, or multimodal version is made from a source, this field binds the adaptation to its source by hash and credits the adapter. Adaptations otherwise circulate detached from their sources, with the adapter's labor invisible. This field keeps the adaptation tied to what it was made from and to whose work made it. Fields: `adapted_from` (source `payload_hash`), `adaptation_type` (`caption`, `simplification`, `alt-text`, `translation`, `multimodal`), `adaptation_contributor`, `review_date`.

These three fields make a knowledge object legible across a gap between parties who do not share the same access to it: between an author and a later reader, between a human and a machine, between a source and its adaptation. Accessibility-adaptation lineage is the protocol's clearest case, because adaptation is knowledge labor that must remain credited and bound to its source. All three are optional for validity and central to purpose. A Crystallizer should offer them; a Lens should surface them; neither should require them.

---

## The canonical hash rule

To verify a KNOBE payload:

1. Decode the Base64 payload to JSON.
2. Delete the `payload_hash` field from the object.
3. Serialize as canonical JSON: recursively sort all object keys alphabetically; no whitespace; arrays preserve insertion order; Unicode preserved as literal UTF-8, never `\uXXXX`-escaped.
4. SHA-256 the UTF-8 bytes.
5. Compare the hex digest to the stored `payload_hash`.

**Match** means the payload is unaltered since sealing. **Mismatch** means something changed.

**Cross-language baseline:** JavaScript `JSON.stringify` with sorted keys. Python equivalent: `json.dumps(obj, sort_keys=True, separators=(",", ":"), ensure_ascii=False)`.

**Optional `body_hash` field.** If present in the payload, it records the SHA-256 of the normalized markdown body. Normalization: (0) strip the extracted body of leading and trailing whitespace; (1) replace `\r\n` and lone `\r` with `\n`; (2) strip trailing whitespace from each line; (3) encode as UTF-8; (4) compute SHA-256. Step 0 is required — the body in the source file and the body extracted from the assembled artifact differ in surrounding blank lines; stripping before normalization makes both paths produce the same hash. This field addresses the Invisible Content Fork: a body altered without touching the payload breaks `body_hash` but not `payload_hash`.

---

## Protocol rules

**Quarantine-first.** New or external KNOBEs default to `quarantine_status: "quarantine"`. Tools must surface this prominently. Do not act on quarantined build recipes without explicit human or governed approval.

**Dual readability.** Every `.knobe.md` must remain human-readable without tooling while also carrying a machine-readable payload.

**Attribution travels with the artifact.** The `attribution.sources` array names contributors with role, contribution, year, URL, and rights-bearing status (false for AI contributors). Attribution in v1 is declared, not cryptographically proven.

**KNOBEs do not execute.** A `.knobe.md` is inert plain text. Build recipes are instructions a human or agent may choose to follow after inspection. Never self-executing.

**The hash proves integrity, not truth.** A green check means the payload is unaltered since sealing. It does not prove accuracy, attribution honesty, safety, or institutional approval.

---

## Safety: the probabilistic verification fallacy

An LLM asked to "verify" a KNOBE natively does not perform a cryptographic computation — it performs a textual prediction. Once a plausible hash token sequence has been generated, the structural logic of a verification narrative predicts that the next sequence should match and declare success. The model satisfies the narrative arc rather than executing the operation. A language model must not be used as a validation environment.

Cryptographic verification requires a deterministic runtime. `lens.py` ships with the protocol not as a convenience, but as an architectural boundary.

Early evidence (declared): a language model correctly diagnosed this failure in one session, then committed it again in the next generation — embedding a hallucinated hash as a provenance record. `lens.py` caught it. The protocol held.

---

## Build recipes

### Recipe 1: Lens (viewer and verifier)

Lens is the first tool a grove needs. It renders the human layer, decodes the payload, runs the canonical hash check, and displays quarantine and attribution status.

**Core steps:**

1. Find the last `-----BEGIN KNOBE B64-----` / `-----END KNOBE B64-----` block (newline-anchored, last block wins).
2. Decode Base64 to JSON. Handle decode failure gracefully: report `corrupt_payload`, do not proceed.
3. Extract `payload_hash`; delete it from the object.
4. Serialize remaining fields as canonical JSON (sorted keys, no whitespace, literal UTF-8).
5. SHA-256 the UTF-8 bytes; compare to stored hash.
6. If `body_hash` is present: extract body between YAML frontmatter close and B64 begin marker; strip whole body; normalize per body_hash rule; SHA-256; compare.
7. Check required fields: `spec_version`, `title`, `summary`, `content_type`, `created_date`, `license`, `privacy_level`, `quarantine_status`, `attribution.sources`, `payload_hash`.
8. Report: title, spec_version, quarantine_status, privacy_level, computed hash, stored hash, status, body_hash status if present, valid_minimum check.
9. Final line if match: `"integrity verified. Integrity is not truth — inspect before trusting."`

**Reference implementation:** `lens.py` at knobe.org (~60 lines of Python).

### Recipe 2: Crystallizer (authoring tool)

Crystallizer takes content plus declared attribution and produces a valid, sealed `.knobe.md`.

**Core steps:**

1. Collect: title, body text, summary, content_type, author name and contribution, license, created_date.
2. Set defaults: `privacy_level: "public"`, `quarantine_status: "quarantine"`, `identity_status: "declared"`, `spec_version: "1.0"`.
3. Assemble the payload object with all fields except `payload_hash`.
4. Serialize as canonical JSON; SHA-256 the UTF-8 bytes; set `payload_hash`.
5. Optionally compute `body_hash` per the normalization rule and add to payload before resealing.
6. Reseal after adding `body_hash` (the hash of a payload including `body_hash` differs from the hash without it).
7. Base64-encode the sealed payload JSON; wrap lines at 76 characters.
8. Assemble the file: `---\n{frontmatter}\n---\n\n{body}\n\n-----BEGIN KNOBE B64-----\n{b64}\n-----END KNOBE B64-----\n`.

**The Magic Grove** (knobe.org/grove) is a Crystallizer in narrative clothing: a single-file browser experience that produces a valid sealed `.knobe.md` from four questions about the user's work, with no AI tools required.

### Recipe 3: Mix (combiner)

Mix merges two or more KNOBEs into a new one with parent receipts and transformation history.

**Core steps:**

1. Decode and verify all source KNOBEs with Lens first.
2. Create a new payload with a `parents[]` array — each entry contains the source `payload_hash`, optional `title`, optional `id`, optional `canonical_url`, and a `relationship` value (`synthesis_input`, `fork`, `source`, `extension`, `compression_of`, or `adaptation_of`).
3. Add a `transformation_history` entry: `date`, `who`, `strategy` (synthesis, side-by-side, extension, compression, remix, or adaptation), `notes`, and `parent_hashes[]`.
4. Seal per the canonical hash rule.

---

## Key vocabulary

**content_type:** original · synthesis · compression · remix · adaptation · annotation · reflection · protocol · recipe · index

**privacy_level:** public · restricted · private · confidential · embargoed

**quarantine_status:** quarantine · trusted · rejected

**identity_status:** declared · signed · anonymous · pseudonymous

**transformation_history.strategy:** synthesis · side-by-side · extension · compression · remix · adaptation

**parents.relationship:** fork · source · extension · synthesis_input · compression_of · adaptation_of

**meta_depth:** L1 = the object itself; L2 = describes objects; higher levels describe processes, contexts, or governance layers. Seeds are typically L2.

---

## Early evidence (declared, not verified)

The KNOBE Seed has been tested against Claude, GPT-4, Gemini, and Manus. All four passed core prompts. Manus independently produced a ten-pathway R1 university deployment document from the Seed alone and independently recommended Lens as the first tool to build. Gemini successfully bootstrapped a working Lens implementation from the white paper cold, without any special configuration. These results are declared early evidence that the Seed functions as a bootstrapping artifact. They show promise, not completion, and have not been independently replicated.

---

## What KNOBE does not do

KNOBE does not solve hallucination, truth, copyright, authorship verification, identity, governance, or ethics. It does not replace institutional systems of record. It does not execute code. Attribution in v1 is declared, not cryptographically proven. A perfectly sealed KNOBE can contain false information. `identity_status: signed` points toward future cryptographic identity extensions; v1 makes no such guarantee.

KNOBE applies equally to non-AI, AI-assisted, and mixed-tool work. The format does not prejudge the workflow; it records what actually happened.

---

*This Seed is itself a valid KNOBE Protocol v1 file. Verify its seal with `lens.py` at knobe.org. The seal proves this file is unaltered since sealing. It proves nothing else. Inspect before trusting.*

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