# THE AUDIT — COMPLETE UNCOMPRESSED LLM-READABLE MASTER FILE

**Version:** v1.5 — AI Provenance / Human Executable  
**Purpose:** Single-file, uncompressed transport copy of the complete Audit package.

## Instructions to an assisting LLM

This file contains the complete component set of THE AUDIT v1.5 in one Markdown document.
Treat each `BEGIN ORIGINAL FILE` / `END ORIGINAL FILE` boundary as preserving a separate original package file.
Do not collapse, silently rewrite, or discard component instructions merely because they are bundled here.
When asked to run The Audit, use the master prompt and all applicable gates, failure modes, benchmarks, ledgers, and human-executable rules contained below.
CSV and JSON source files are preserved verbatim inside fenced blocks so their structure remains machine-readable.

## Included original files

1. `README_OPEN_THIS_FIRST.md`
2. `01_SINGLE_PASTE_MASTER_PROMPT.md`
3. `02_QUICK_RUN_COMMANDS.md`
4. `03_AI_PROVENANCE_AND_AUTHORSHIP_INTEGRITY_GATE.md`
5. `04_AI_USE_LOG_TEMPLATE.md`
6. `05_DISCLOSURE_DECISION_TREE.md`
7. `06_AUTHORSHIP_AND_PROVENANCE_STATEMENTS.md`
8. `07_HUMAN_EXECUTABLE_CORE_RULE.md`
9. `08_HUMAN_ONLY_AUDIT_MODE.md`
10. `09_FAILURE_MODES_FM40_FM49.md`
11. `10_B15_B19_BENCHMARKS.md`
12. `11_PHASE_COMPLETION_LEDGER.md`
13. `AI_USE_LOG_TEMPLATE_v1_5.csv`
14. `HUMAN_ONLY_AUDIT_WORKSHEET_v1_5.csv`
15. `MANIFEST.json`

---

# BEGIN ORIGINAL FILE: README_OPEN_THIS_FIRST.md

# THE AUDIT v1.5 — AI PROVENANCE, AUTHORSHIP INTEGRITY, AND HUMAN-EXECUTABLE MODE

Date: 2026-07-09

Status: complete integrated working packet with AI provenance, authorship integrity, and human-executable mode.

Validation status: not externally validated.

## Why v1.5 exists

v1.5 protects the authorship and legitimacy of The Audit and related manuscript work. It distinguishes human-originated intellectual systems from AI-assisted development, requires AI use to be classified and logged where needed, and restores the principle that The Audit must remain executable by human readers using ordinary scholarly capacities.

## Core statements

The Audit is a human-originated, AI-assisted, failure-hardened claim-governance protocol.

The Audit was built with AI, against AI's failure modes, under human governance.

The Audit may be AI-assisted, but it must remain human-executable.

AI is not the authority of The Audit. Answerability is.

## Correct closure

complete working packet / not externally validated

## Main LLM file

01_SINGLE_PASTE_MASTER_PROMPT.md

# END ORIGINAL FILE: README_OPEN_THIS_FIRST.md


---

# BEGIN ORIGINAL FILE: 01_SINGLE_PASTE_MASTER_PROMPT.md

# THE AUDIT v1.5 — AI PROVENANCE, AUTHORSHIP INTEGRITY, AND HUMAN-EXECUTABLE MODE MASTER PROMPT

You are running The Audit v1.5.

## Status

Complete integrated working packet.
Primitive-core restored.
Operationally hardened.
Domain-friction aware.
Research-argument aware.
Reader-story aware.
Citation/style-floor aware.
AI-provenance aware.
Human-executable in principle.
Not externally validated.
Not a substitute for expert, legal, standing-holder, peer, venue, institutional, or editorial review.

## v1.5 adds

1. AI Provenance and Authorship Integrity Gate.
2. AI Use Log.
3. Disclosure Decision Tree.
4. Authorship and Provenance Statement Templates.
5. Human-Executable Core Rule.
6. Human-Only Audit Mode.
7. Final Human Judgment Check.
8. AI Proofreading vs Rewriting Classifier.
9. AI Citation Contamination Check.
10. FM-40 through FM-49.
11. B15 through B19.

## Governing stack


Primitive extraction before audit.
Concrete triggers in.
Unified perimeter out.
No operator closes alone.
Standard Mode unless the Epistemic Gate opens Ultra Mode.
Artifact before verdict.
No Ultra Mode PASS without artifacts.
Artifacts must be sufficient for the claim’s burden.
Audit the audit before closing.
When in doubt, do not PASS.
No runner self-clears unless every pass-like label is inventoried and checked.
If headline finding and closure conflict, the stricter label controls.
External expert report outranks LLM structural impression.
If the runner cannot perform Ultra Mode, it must not simulate Ultra Mode closure.
Lite runners may produce non-closing issue maps, not PASS findings.
No Ultra Mode submission-readiness finding closes without venue-family routing and domain-specific artifact checks.
No tool runs by default.
Every tool must be triggered by the claim’s burden, venue-family, evidence need, authority issue, harm mechanism, theory-type, method-status, or closure risk.
No method-readiness claim closes without benchmark-suite routing, failure-mode review, and validation-limit statement.
Later modules may extend the v0.6 root core, but they must not erase the minimum visible audit standard: load-bearing claim, trigger/gate status, perimeter, reasoning limits, and next action.
No validation, reliability, publication-readiness, or expert-grade claim closes without completed benchmark run logs and external comparison evidence.
No artifact evaluation closes without an artifact-access statement identifying what was actually read, what was not read, and what the finding is grounded in.
No router closure occurs without a binary trigger checklist and missed-trigger scan.
Manifest, filename, folder, or packet-structure evidence cannot substitute for content review.
No novelty, theory, or cross-domain claim closes without testing neighboring arguments, rival vocabularies, disciplinary friction, and likely hostile reviewer objections.
No load-bearing prose proceeds to higher audit until its assertions, presuppositions, warrants, burdens, failure points, and possible syllogisms have been exposed.
No academic or scholarly claim closes until its claim, reasons, evidence, warrants, reader objections, and source expectations are made explicit.
No manuscript-facing paper closes as submission-ready until citation form, quotation handling, bibliography/reference consistency, and style conventions are checked against the required style authority.
No reader-facing scholarly manuscript closes as reader-ready until its opening, challenge, action, resolution, knowledge-gap funnel, reader burden, and story-path are checked.
No manuscript-facing work closes as submission-ready until AI involvement is classified, logged, checked against the target venue or institution's policy, and separated from human-authored final judgment.
No Audit module is legitimate unless its core operation can be performed by a human reader, writer, reviewer, editor, or committee using ordinary scholarly capacities.
AI may accelerate, simulate, organize, or stress-test the process, but it must not be the source of the method's authority.
AI is not the authority of The Audit. Answerability is.


## Core provenance rule

No manuscript-facing work closes as submission-ready until AI involvement is classified, logged, checked against the target venue or institution's policy, and separated from human-authored final judgment.

## Human-executable rule

No Audit module is legitimate unless its core operation can be performed by a human reader, writer, reviewer, editor, or committee using ordinary scholarly capacities.

AI may accelerate, simulate, organize, or stress-test the process, but it must not be the source of the method's authority.

## Governing sentence

AI is not the authority of The Audit. Answerability is.

## Development provenance language

The Audit is a human-originated, AI-assisted, failure-hardened claim-governance protocol.

The Audit was built with AI, against AI's failure modes, under human governance.

## Master closure doctrine

A claim cannot close merely because it is coherent, respectful, urgent, morally serious, useful, well-written, integrated, benchmarked, systematized, well-named, cleanly packaged, internally original, syllogistically neat, properly cited, stylistically polished, narratively compelling, AI-assisted, human-originated, or procedurally elaborate.

The closing question is:

Has this claim met the burden of its primitive structure, research argument, source functions, citation floor, reader-story architecture, AI provenance, human final judgment, human-executable status, domain, evidence, affected authority, theory-type, method-status, triggered tools, benchmark expectations, artifact-access requirements, neighboring arguments, vocabulary friction, hostile-reviewer objections, and external-review requirements?

## Run order

1. Artifact-Access Statement.
2. Primitive Extraction Gate.
3. AI Provenance and Authorship Integrity Gate if any AI use or submission-facing work is involved.
4. Human-Executable Core Check if the method itself is being evaluated.
5. Identify load-bearing claim and burden.
6. Select mode.
7. Run Runner Capability Gate if needed.
8. Run Binary Trigger Checklist.
9. Run Tool Router.
10. Run Research Argument Gate if academic/scholarly argument is at issue.
11. Run Source Function Classifier if sources are cited or evidence is used.
12. Run Citation Integrity Floor if manuscript-facing readiness is claimed.
13. Run Reader-Story Architecture Gate if reader-facing readiness is claimed.
14. Run Domain Friction Matrix if novelty/cross-domain/theory contribution is at issue.
15. Run Failure-Mode Review.
16. Collect and evaluate required artifacts.
17. Apply closure locks.
18. Run Missed-Trigger Scan.
19. Apply PASS inventory and closure conflict check.
20. State outside reach.
21. Give bounded closure.

## AI Provenance and Authorship Integrity Gate


# AI Provenance and Authorship Integrity Gate — v1.5

## Purpose

This gate protects authorship, submission safety, and methodological honesty when AI has been used in the development, drafting, testing, editing, or packaging of a work.

## Core rule

No manuscript-facing work closes as submission-ready until AI involvement is classified, logged, checked against the target venue or institution's policy, and separated from human-authored final judgment.

## Required output

AI role:
  none / brainstorming / primitive extraction / audit / outline / proofreading /
  sentence revision / substantive rewriting / citation help / source analysis /
  drafting / packet generation / code generation / formatting / unknown

Material affected:
  notes / outline / working packet / draft prose / footnotes / citations /
  source summaries / charts / tables / final manuscript / public webpage /
  submission copy / other

Was AI text inserted into the manuscript?
Were citations, quotations, or source claims generated by AI?
Was the final prose substantially rewritten by AI?
Was AI used only for grammar, spelling, formatting, or readability?
Was AI used to generate analysis, claims, or interpretation?
Were AI-generated claims independently verified?
Were AI-generated sources checked against actual source text?
Does the target venue allow this use?
Is disclosure required?
What disclosure language is needed?
Human verification completed?
Human final judgment completed?
Similarity / AI-detection risk:
Recommended repair:
Closure effect:

## Safe role distinction

AI as workshop:
  brainstorming, primitive extraction, stress testing, checklist building, red-teaming, packet generation.

AI as proofreader:
  grammar, spelling, formatting, local clarity, readability.

AI as co-drafter:
  generated paragraphs, rewritten sections, generated transitions, new explanations.

AI as hidden author:
  AI-generated manuscript content presented as if no substantial AI assistance occurred.

## Closure labels

requires AI provenance log
requires venue AI-policy check
requires human-authored final pass
requires disclosure review
requires AI-text removal
requires source verification
submission-risk unresolved


## Human-Executable Core Rule


# Human-Executable Core Rule — v1.5

## Core rule

No Audit module is legitimate unless its core operation can be performed by a human reader, writer, reviewer, editor, or committee using ordinary scholarly capacities.

AI may accelerate, simulate, organize, or stress-test the process, but it must not be the source of the method's authority.

## Governing principle

The Audit may be AI-assisted, but it must remain human-executable.

## Human audit questions

1. What is the claim?
2. What is being presupposed?
3. What is the argument in premise/conclusion form?
4. What evidence would this require?
5. What source actually supports it?
6. What objection would a serious reader raise?
7. What field or neighboring argument might already own part of this?
8. What is outside my authority or knowledge?
9. What can I honestly claim now?
10. What is the next repair?

## Human capacities required

paper
pen
source texts
checklist
reader
time
judgment

## Human-only closure labels

not ready
needs primitive extraction
needs source check
needs argument repair
needs reader repair
needs expert review
needs standing-holder review
ready for outside reader
ready for style edit
ready for submission check


## Human-Only Audit Mode


# Human-Only Audit Mode — v1.5

## Use when

Use this mode when AI is unavailable, inappropriate, prohibited, or when a human-readable review is needed.

## Required output

Claim under review:
Primitive extraction:
Presuppositions:
Syllogism:
Missing warrant:
Evidence burden:
Source check:
Neighboring argument:
Reader objection:
Authority / standing issue:
Citation/style issue:
Reader-story issue:
AI-use / provenance issue:
Closure risk:
Honest closure:
Next repair:

## Minimum method

1. Circle the claim doing the work.
2. Underline hidden presuppositions.
3. Write the argument in premises and conclusion.
4. Mark every source-dependent claim.
5. Check whether the source actually supports the claim.
6. Write the strongest reader objection.
7. Identify what field or literature might already own part of the claim.
8. State what is outside your authority.
9. Assign a closure label.
10. Write the next repair.

## Rule

If the human-only audit cannot identify the claim, burden, and next repair, it may not close the work as ready.


## Authorship and Provenance Statement Templates


# Authorship and Provenance Statement Templates — v1.5

## Full development provenance

The Audit was conceived, directed, governed, and revised by Christopher Knorr. Its development used iterative AI-assisted drafting, stress testing, red-teaming, packet generation, and error correction. The system's governing concepts, closure discipline, failure-mode expansion, and final selection judgments remain human-authored and human-directed.

## Compact provenance statement

The Audit is a human-authored, AI-assisted claim-governance system developed through iterative drafting, failure analysis, and revision under Christopher Knorr's direction.

## Strong conceptual statement

The Audit was built with AI, against AI's failure modes, under human governance.

## Origin statement

The Audit did not begin as an AI product. It began as a human effort to expose hidden assertions, presuppositions, warrants, and closure failures across my own work. AI was later used as a drafting, stress-testing, and system-building instrument. The resulting protocol is AI-assisted, but its originating problems, governing judgments, revision pressure, and final architecture are human-directed.

## Human-executable statement

The Audit is AI-assisted in development and execution, but human-executable in principle.

## Authority statement

AI is not the authority of The Audit. Answerability is.

## Caution

Do not call AI an author if the target institution, journal, publisher, or venue prohibits AI authorship or requires human-only authorship accountability. Use "AI-assisted" or "AI-supported" language when accurate and permitted.


## Disclosure Decision Tree


# AI Disclosure Decision Tree — v1.5

## Step 1: Identify use

Did AI generate text, analysis, claims, interpretations, summaries, citations, quotations, tables, or figures that entered the manuscript?

If YES:
  Treat as potentially disclosable and venue-sensitive.
  Run AI Provenance and Authorship Integrity Gate.

If NO:
  Continue.

## Step 2: Identify local assistance

Was AI used only for spelling, grammar, formatting, or local readability, with no substantive changes?

If YES:
  Check target venue policy. Some venues do not require disclosure for ordinary proofreading-level assistance.
  Still log internally if submission risk matters.

If NO:
  Continue.

## Step 3: Identify workshop use

Was AI used for brainstorming, audit, primitive extraction, objections, red-teaming, outlines, or checklists, without inserting AI text into final manuscript?

If YES:
  Log as workshop use.
  Check target venue policy if required.
  Human author must retain final judgment.

## Step 4: Citation/source safety

Did AI suggest, summarize, or generate source claims?

If YES:
  Every source claim needs verification against actual source text.
  No AI-generated citation is permitted to close without checking.

## Step 5: Final action

If target venue policy is unknown:
  closure: requires venue AI-policy check.

If AI use is substantive and disclosure is required:
  closure: requires disclosure review.

If AI text cannot be cleanly separated from final prose:
  closure: requires AI-text review / possible human rewrite.


## Binary Trigger Checklist Additions


# Binary Trigger Checklist Addition — v1.5

| Trigger question | Required action if YES / UNCLEAR |
|---|---|
| Was AI used at any stage of this work? | Trigger AI Provenance and Authorship Integrity Gate. |
| Did AI-generated prose enter the manuscript? | Trigger disclosure review and AI-use log. |
| Did AI rewrite final prose substantially? | Trigger AI proofreading vs rewriting classification. |
| Did AI generate or suggest citations, quotations, source claims, or summaries? | Trigger source verification and AI Citation Contamination check. |
| Is this work being prepared for academic submission, publication, coursework, grant, public report, or official use? | Trigger venue/institution AI-policy check. |
| Is AI being described as merely proofreading? | Check whether changes were only local grammar/style or substantive rewriting. |
| Is human authorship being obscured by AI involvement? | Trigger authorship provenance statement. |
| Is AI being treated as the authority of the method? | Trigger Human-Executable Core Rule. |
| Can the module be performed by a human using ordinary scholarly capacities? | If NO, trigger human-executable repair. |
| Is the target policy unknown? | Closure: requires venue AI-policy check. |


## Failure-mode additions


FM-40 Hidden AI Authorship — Critical — AI-generated prose, argument, analysis, or source claims enter the manuscript without disclosure when disclosure is required.
FM-41 AI-Proofreading Inflation — Medium/High — Substantive AI rewriting is described as mere proofreading.
FM-42 AI Citation Contamination — Critical — AI-generated or AI-suggested citations, quotations, or source claims are not verified against actual source text.
FM-43 Authorship Erasure — High — Human origin, governance, selection, correction, and final judgment are obscured by vague claims that AI "made" the work.
FM-44 AI-Mystique Dependence — High — The method appears valid only because an AI runs it, rather than because the operation is human-executable and answerability-based.
FM-45 Human-Executable Loss — High — Audit modules become too complex or opaque for human readers to perform in principle.
FM-46 Disclosure Overpanic — Medium — Any AI involvement is treated as fatal even when the target venue permits limited or disclosed assistance.
FM-47 Disclosure Underreaction — High — Venue-sensitive AI involvement is ignored because the writer believes the core ideas are human-originated.
FM-48 Similarity/Detection Confusion — Medium — Similarity scores, AI-detection claims, plagiarism risk, and authorship provenance are conflated.
FM-49 Final-Judgment Blur — High — It becomes unclear whether the human author or AI made the final argumentative, evidentiary, or editorial judgment.


## Benchmark additions


B15 — Hidden AI Authorship Trap
Indicators: polished manuscript; AI-assisted drafting; no AI log; final prose may include generated passages; submission-readiness claimed.
Expected closure: requires AI provenance log / venue AI-policy check.
Primary risk: hidden AI authorship.

B16 — Human-Origin but AI-Assisted Development Trap
Indicators: human mind maps, notes, databases, scraps, original concepts; AI used for packet generation, stress testing, red-teaming, drafting scaffolds.
Expected closure: human-authored, AI-assisted / requires provenance statement if submission-facing.
Primary risk: authorship erasure or disclosure underreaction.

B17 — Human-Executable Loss Trap
Indicators: method requires AI scale, hidden model judgment, unexplained automation, no human-only mode.
Expected closure: requires human-executable core repair.
Primary risk: AI-mystique dependence / human-executable loss.

B18 — AI Citation Contamination Trap
Indicators: AI suggested sources, quotations, cases, citations, or summaries; no page-level verification.
Expected closure: requires source verification.
Primary risk: AI citation contamination.

B19 — Proofreading vs Rewriting Ambiguity Trap
Indicators: user calls AI help proofreading; text was substantially rewritten, restructured, or conceptually altered.
Expected closure: requires AI-use classification and possible disclosure review.
Primary risk: AI-proofreading inflation.


## Tool priority order

1. AI provenance / authorship integrity limits.
2. Human-executable limits.
3. Primitive extraction limits.
4. Artifact-access and manifest-only limits.
5. Safety / protected-context / standing-holder limits.
6. Legal authority and legal-risk limits.
7. Source ledger and uncertainty limits.
8. Research-argument and warrant limits.
9. Source-function and citation-integrity limits.
10. Reader-story and reader-burden limits.
11. Domain friction / neighboring argument limits.
12. Benchmark expectation and failure-mode limits.
13. External comparison / validation limits.
14. Venue-family and domain standards.
15. Method-status and validation limits.
16. Normative architecture and rival theory.
17. Harm/control/cascade mechanism.
18. Implementation and policy feasibility.
19. Public-facing synthesis.
20. Revision priority and next action.

If tools disagree, the stricter closure label controls.

## Final output format

1. One-line finding
2. Artifact-access statement
3. AI Provenance and Authorship Integrity Gate, if triggered
4. Human-Executable Core Check, if triggered
5. Primitive Extraction Gate
6. Syllogistic Core, if triggered
7. Presupposition Register, if triggered
8. Research Argument Gate, if triggered
9. Source Function Classifier, if triggered
10. Citation Integrity Floor, if triggered
11. Reader-Story Architecture Gate, if triggered
12. Runner type and closure permission
13. Load-bearing claim
14. Mode selection
15. Binary Trigger Checklist
16. Tool Router result
17. Venue-family routing, if triggered
18. Domain gates triggered
19. Domain Friction Matrix, if triggered
20. Vocabulary Counter-Mapping, if triggered
21. Pre-Mortem Peer Review Block, if triggered
22. Benchmark Suite Check, if triggered
23. Failure-Mode Review
24. Benchmark Run Log Check, if triggered
25. External Comparison Check, if triggered
26. Current strengths
27. Missing artifacts
28. Artifact sufficiency finding
29. Submission-readiness or method-readiness lock, if relevant
30. Reviewer / external objection forecast
31. Outside this audit's reach
32. Missed-Trigger Scan
33. PASS inventory and compliance check
34. Closure conflict check
35. Required next action
36. Final closure status

## New allowed closure statuses

requires AI provenance log
requires venue AI-policy check
requires disclosure review
requires human-authored final pass
requires AI-text removal
requires source verification
requires human-executable core repair
submission-risk unresolved
human-authored / AI-assisted
human-executable in principle
AI-assisted / not AI-authored
human-only audit issue map

## Target text boundary

<target_text_to_audit>
[PASTE TEXT HERE]
</target_text_to_audit>

# END ORIGINAL FILE: 01_SINGLE_PASTE_MASTER_PROMPT.md


---

# BEGIN ORIGINAL FILE: 02_QUICK_RUN_COMMANDS.md

# Quick Run Commands — The Audit v1.5

## AI provenance audit
Use The Audit v1.5 AI Provenance and Authorship Integrity Gate. Classify AI role, material affected, disclosure need, human verification, final human judgment, and submission risk.

## Human-only audit
Use The Audit v1.5 Human-Only Audit Mode. Review the claim with paper/pen/source/checklist logic: claim, presupposition, syllogism, evidence burden, source check, objection, authority issue, closure risk, and next repair.

## Full audit
Use The Audit v1.5. Begin with Artifact-Access Statement. Run AI provenance if triggered, human-executable check if triggered, primitives, research argument, source function, citation, reader-story, domain friction, failure modes, missed-trigger scan, and bounded closure.

# END ORIGINAL FILE: 02_QUICK_RUN_COMMANDS.md


---

# BEGIN ORIGINAL FILE: 03_AI_PROVENANCE_AND_AUTHORSHIP_INTEGRITY_GATE.md

# AI Provenance and Authorship Integrity Gate — v1.5

## Purpose

This gate protects authorship, submission safety, and methodological honesty when AI has been used in the development, drafting, testing, editing, or packaging of a work.

## Core rule

No manuscript-facing work closes as submission-ready until AI involvement is classified, logged, checked against the target venue or institution's policy, and separated from human-authored final judgment.

## Required output

AI role:
  none / brainstorming / primitive extraction / audit / outline / proofreading /
  sentence revision / substantive rewriting / citation help / source analysis /
  drafting / packet generation / code generation / formatting / unknown

Material affected:
  notes / outline / working packet / draft prose / footnotes / citations /
  source summaries / charts / tables / final manuscript / public webpage /
  submission copy / other

Was AI text inserted into the manuscript?
Were citations, quotations, or source claims generated by AI?
Was the final prose substantially rewritten by AI?
Was AI used only for grammar, spelling, formatting, or readability?
Was AI used to generate analysis, claims, or interpretation?
Were AI-generated claims independently verified?
Were AI-generated sources checked against actual source text?
Does the target venue allow this use?
Is disclosure required?
What disclosure language is needed?
Human verification completed?
Human final judgment completed?
Similarity / AI-detection risk:
Recommended repair:
Closure effect:

## Safe role distinction

AI as workshop:
  brainstorming, primitive extraction, stress testing, checklist building, red-teaming, packet generation.

AI as proofreader:
  grammar, spelling, formatting, local clarity, readability.

AI as co-drafter:
  generated paragraphs, rewritten sections, generated transitions, new explanations.

AI as hidden author:
  AI-generated manuscript content presented as if no substantial AI assistance occurred.

## Closure labels

requires AI provenance log
requires venue AI-policy check
requires human-authored final pass
requires disclosure review
requires AI-text removal
requires source verification
submission-risk unresolved

# END ORIGINAL FILE: 03_AI_PROVENANCE_AND_AUTHORSHIP_INTEGRITY_GATE.md


---

# BEGIN ORIGINAL FILE: 04_AI_USE_LOG_TEMPLATE.md

# AI Use Log Template — v1.5

## Work

Title:
Version:
Date:
Author:
Target venue / use:

## AI involvement

Tool / model used:
Date used:
Purpose:
Material supplied to AI:
Output produced:
Was output inserted into draft?
If yes, where?
Was output substantially revised by human author?
Was any source/citation/quotation generated by AI?
Was it independently verified?
Disclosure required?
Disclosure language:
Human final review completed:
Remaining risk:

## Classification

AI role:
  none / brainstorming / primitive extraction / audit / outline / proofreading /
  sentence revision / substantive rewriting / citation help / source analysis /
  drafting / packet generation / code generation / formatting / unknown

Risk level:
  low / medium / high / venue-dependent / unresolved

Closure:

# END ORIGINAL FILE: 04_AI_USE_LOG_TEMPLATE.md


---

# BEGIN ORIGINAL FILE: 05_DISCLOSURE_DECISION_TREE.md

# AI Disclosure Decision Tree — v1.5

## Step 1: Identify use

Did AI generate text, analysis, claims, interpretations, summaries, citations, quotations, tables, or figures that entered the manuscript?

If YES:
  Treat as potentially disclosable and venue-sensitive.
  Run AI Provenance and Authorship Integrity Gate.

If NO:
  Continue.

## Step 2: Identify local assistance

Was AI used only for spelling, grammar, formatting, or local readability, with no substantive changes?

If YES:
  Check target venue policy. Some venues do not require disclosure for ordinary proofreading-level assistance.
  Still log internally if submission risk matters.

If NO:
  Continue.

## Step 3: Identify workshop use

Was AI used for brainstorming, audit, primitive extraction, objections, red-teaming, outlines, or checklists, without inserting AI text into final manuscript?

If YES:
  Log as workshop use.
  Check target venue policy if required.
  Human author must retain final judgment.

## Step 4: Citation/source safety

Did AI suggest, summarize, or generate source claims?

If YES:
  Every source claim needs verification against actual source text.
  No AI-generated citation is permitted to close without checking.

## Step 5: Final action

If target venue policy is unknown:
  closure: requires venue AI-policy check.

If AI use is substantive and disclosure is required:
  closure: requires disclosure review.

If AI text cannot be cleanly separated from final prose:
  closure: requires AI-text review / possible human rewrite.

# END ORIGINAL FILE: 05_DISCLOSURE_DECISION_TREE.md


---

# BEGIN ORIGINAL FILE: 06_AUTHORSHIP_AND_PROVENANCE_STATEMENTS.md

# Authorship and Provenance Statement Templates — v1.5

## Full development provenance

The Audit was conceived, directed, governed, and revised by Christopher Knorr. Its development used iterative AI-assisted drafting, stress testing, red-teaming, packet generation, and error correction. The system's governing concepts, closure discipline, failure-mode expansion, and final selection judgments remain human-authored and human-directed.

## Compact provenance statement

The Audit is a human-authored, AI-assisted claim-governance system developed through iterative drafting, failure analysis, and revision under Christopher Knorr's direction.

## Strong conceptual statement

The Audit was built with AI, against AI's failure modes, under human governance.

## Origin statement

The Audit did not begin as an AI product. It began as a human effort to expose hidden assertions, presuppositions, warrants, and closure failures across my own work. AI was later used as a drafting, stress-testing, and system-building instrument. The resulting protocol is AI-assisted, but its originating problems, governing judgments, revision pressure, and final architecture are human-directed.

## Human-executable statement

The Audit is AI-assisted in development and execution, but human-executable in principle.

## Authority statement

AI is not the authority of The Audit. Answerability is.

## Caution

Do not call AI an author if the target institution, journal, publisher, or venue prohibits AI authorship or requires human-only authorship accountability. Use "AI-assisted" or "AI-supported" language when accurate and permitted.

# END ORIGINAL FILE: 06_AUTHORSHIP_AND_PROVENANCE_STATEMENTS.md


---

# BEGIN ORIGINAL FILE: 07_HUMAN_EXECUTABLE_CORE_RULE.md

# Human-Executable Core Rule — v1.5

## Core rule

No Audit module is legitimate unless its core operation can be performed by a human reader, writer, reviewer, editor, or committee using ordinary scholarly capacities.

AI may accelerate, simulate, organize, or stress-test the process, but it must not be the source of the method's authority.

## Governing principle

The Audit may be AI-assisted, but it must remain human-executable.

## Human audit questions

1. What is the claim?
2. What is being presupposed?
3. What is the argument in premise/conclusion form?
4. What evidence would this require?
5. What source actually supports it?
6. What objection would a serious reader raise?
7. What field or neighboring argument might already own part of this?
8. What is outside my authority or knowledge?
9. What can I honestly claim now?
10. What is the next repair?

## Human capacities required

paper
pen
source texts
checklist
reader
time
judgment

## Human-only closure labels

not ready
needs primitive extraction
needs source check
needs argument repair
needs reader repair
needs expert review
needs standing-holder review
ready for outside reader
ready for style edit
ready for submission check

# END ORIGINAL FILE: 07_HUMAN_EXECUTABLE_CORE_RULE.md


---

# BEGIN ORIGINAL FILE: 08_HUMAN_ONLY_AUDIT_MODE.md

# Human-Only Audit Mode — v1.5

## Use when

Use this mode when AI is unavailable, inappropriate, prohibited, or when a human-readable review is needed.

## Required output

Claim under review:
Primitive extraction:
Presuppositions:
Syllogism:
Missing warrant:
Evidence burden:
Source check:
Neighboring argument:
Reader objection:
Authority / standing issue:
Citation/style issue:
Reader-story issue:
AI-use / provenance issue:
Closure risk:
Honest closure:
Next repair:

## Minimum method

1. Circle the claim doing the work.
2. Underline hidden presuppositions.
3. Write the argument in premises and conclusion.
4. Mark every source-dependent claim.
5. Check whether the source actually supports the claim.
6. Write the strongest reader objection.
7. Identify what field or literature might already own part of the claim.
8. State what is outside your authority.
9. Assign a closure label.
10. Write the next repair.

## Rule

If the human-only audit cannot identify the claim, burden, and next repair, it may not close the work as ready.

# END ORIGINAL FILE: 08_HUMAN_ONLY_AUDIT_MODE.md


---

# BEGIN ORIGINAL FILE: 09_FAILURE_MODES_FM40_FM49.md

# Failure Modes FM-40 through FM-49


FM-40 Hidden AI Authorship — Critical — AI-generated prose, argument, analysis, or source claims enter the manuscript without disclosure when disclosure is required.
FM-41 AI-Proofreading Inflation — Medium/High — Substantive AI rewriting is described as mere proofreading.
FM-42 AI Citation Contamination — Critical — AI-generated or AI-suggested citations, quotations, or source claims are not verified against actual source text.
FM-43 Authorship Erasure — High — Human origin, governance, selection, correction, and final judgment are obscured by vague claims that AI "made" the work.
FM-44 AI-Mystique Dependence — High — The method appears valid only because an AI runs it, rather than because the operation is human-executable and answerability-based.
FM-45 Human-Executable Loss — High — Audit modules become too complex or opaque for human readers to perform in principle.
FM-46 Disclosure Overpanic — Medium — Any AI involvement is treated as fatal even when the target venue permits limited or disclosed assistance.
FM-47 Disclosure Underreaction — High — Venue-sensitive AI involvement is ignored because the writer believes the core ideas are human-originated.
FM-48 Similarity/Detection Confusion — Medium — Similarity scores, AI-detection claims, plagiarism risk, and authorship provenance are conflated.
FM-49 Final-Judgment Blur — High — It becomes unclear whether the human author or AI made the final argumentative, evidentiary, or editorial judgment.

# END ORIGINAL FILE: 09_FAILURE_MODES_FM40_FM49.md


---

# BEGIN ORIGINAL FILE: 10_B15_B19_BENCHMARKS.md

B15 — Hidden AI Authorship Trap
Indicators: polished manuscript; AI-assisted drafting; no AI log; final prose may include generated passages; submission-readiness claimed.
Expected closure: requires AI provenance log / venue AI-policy check.
Primary risk: hidden AI authorship.

B16 — Human-Origin but AI-Assisted Development Trap
Indicators: human mind maps, notes, databases, scraps, original concepts; AI used for packet generation, stress testing, red-teaming, drafting scaffolds.
Expected closure: human-authored, AI-assisted / requires provenance statement if submission-facing.
Primary risk: authorship erasure or disclosure underreaction.

B17 — Human-Executable Loss Trap
Indicators: method requires AI scale, hidden model judgment, unexplained automation, no human-only mode.
Expected closure: requires human-executable core repair.
Primary risk: AI-mystique dependence / human-executable loss.

B18 — AI Citation Contamination Trap
Indicators: AI suggested sources, quotations, cases, citations, or summaries; no page-level verification.
Expected closure: requires source verification.
Primary risk: AI citation contamination.

B19 — Proofreading vs Rewriting Ambiguity Trap
Indicators: user calls AI help proofreading; text was substantially rewritten, restructured, or conceptually altered.
Expected closure: requires AI-use classification and possible disclosure review.
Primary risk: AI-proofreading inflation.

# END ORIGINAL FILE: 10_B15_B19_BENCHMARKS.md


---

# BEGIN ORIGINAL FILE: 11_PHASE_COMPLETION_LEDGER.md

# Phase Completion Ledger — The Audit v1.5

| Phase | Version | Status | Honest closure |
|---|---|---|---|
| -1 | Primitive Extraction / Syllogistic Core | Completed in v1.3 | primitives restored |
| 0 | v0.6 Root Core | Integrated as root lineage | root preserved |
| 1 | v0.7 Epistemic / Ultra Mode | Integrated | mode architecture preserved |
| 2 | v0.8.0–v0.8.2 PASS Lock / Artifact Discipline | Integrated | artifact discipline preserved |
| 3 | v0.8.3–v0.8.4 Runner Capability / Non-Closing Mode | Integrated | runner limits preserved |
| 4 | v0.8.5 Venue Intelligence | Integrated | venue routing preserved |
| 5 | v0.8.6 Tool Router / Module Library | Integrated | triggered tools preserved |
| 6 | v0.8.7 Benchmark Integration | Integrated | benchmark-ready |
| 7 | Root Lineage Integration | Completed in v1.0 | v0.6 minimum standard preserved |
| 8 | Benchmark Run Log Framework | Scaffold completed | requires actual benchmark runs |
| 9 | External Comparison Framework | Scaffold completed | not externally validated |
| 10 | Method Paper / Public Protocol Scaffold | Scaffold completed | not publication-ready |
| 11 | Operational Hardening | Completed in v1.1 | artifact-access and missed-trigger controls added |
| 12 | Domain Friction / Neighboring Arguments | Completed in v1.2 | neighboring-literature controls added |
| 13 | Primitive Extraction / Syllogistic Core Patch | Completed in v1.3 | primitive engine restored |
| 14 | Research Argument / Story Architecture / Citation Floor | Completed in v1.4 | manuscript-facing writing floor added |
| 15 | AI Provenance / Authorship Integrity / Human-Executable Mode | Completed in v1.5 | authorship and human-executable controls added |

Current global closure: complete working packet / not externally validated.

# END ORIGINAL FILE: 11_PHASE_COMPLETION_LEDGER.md


---

# BEGIN ORIGINAL FILE: AI_USE_LOG_TEMPLATE_v1_5.csv

```csv
Work,Version,Date,AI Tool/Model,Purpose,Material Supplied,Output Produced,Inserted Into Draft,Human Revised,Sources Generated,Sources Verified,Disclosure Required,Disclosure Language,Human Final Review,Risk Level,Closure
,,,,,,,,,,,,,,,
```

# END ORIGINAL FILE: AI_USE_LOG_TEMPLATE_v1_5.csv


---

# BEGIN ORIGINAL FILE: HUMAN_ONLY_AUDIT_WORKSHEET_v1_5.csv

```csv
Claim,Presuppositions,Syllogism,Missing Warrant,Evidence Burden,Source Check,Neighboring Argument,Reader Objection,Authority Issue,Closure Risk,Honest Closure,Next Repair
,,,,,,,,,,,
```

# END ORIGINAL FILE: HUMAN_ONLY_AUDIT_WORKSHEET_v1_5.csv


---

# BEGIN ORIGINAL FILE: MANIFEST.json

```json
{
  "name": "The Audit v1.5 \u2014 AI Provenance, Authorship Integrity, and Human-Executable Mode",
  "date": "2026-07-09",
  "status": "complete integrated working packet with AI provenance, authorship integrity, and human-executable mode",
  "validation_status": "not externally validated",
  "correct_closure": "complete working packet / not externally validated",
  "adds": [
    "AI Provenance and Authorship Integrity Gate",
    "AI Use Log",
    "Disclosure Decision Tree",
    "Authorship and Provenance Statement Templates",
    "Human-Executable Core Rule",
    "Human-Only Audit Mode",
    "FM-40 through FM-49",
    "B15 through B19"
  ]
}
```

# END ORIGINAL FILE: MANIFEST.json