Audit Validator Independence logo

Audit Validator Independence

Organization
yogsoth-ai
audit-validator-independence

Audit whether a validator, benchmark, sandbox, or test can pass by construction because it embeds the same assumptions as the theory it claims to validate. Build a claim×validator-assumption matrix and demand at least one non-circular failure channel.

Overview

Publisheryogsoth-ai
Repositoryde-anthropocentric-research-engine
Skill nameaudit-validator-independence
Stars
505
Forks
43
Bundled files
Instructions only
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by yogsoth-ai on GitHub. Read the source before you install it.

Installation

Install the Audit Validator Independence AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/audit-validator-independence
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yogsoth-ai/de-anthropocentric-research-engine.git /tmp/de-anthropocentric-research-engine
mkdir -p .claude/skills
cp -r /tmp/de-anthropocentric-research-engine/skills/audit-validator-independence .claude/skills/audit-validator-independence
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Audit Validator Independence in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Audit Validator Independence on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Audit Validator Independence is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

audit-validator-independence

Purpose

Detect validators that pass by construction because they copy the target theory's assumptions.

Input contract

yaml
mode_contracts:
  validator: &validator_audit_input
    required: [target_claim, validator, validator_artifacts]
    optional: [data_generation, metric, oracle, acceptance_rule]
    constraints: [validator_assumptions_and_target_assumptions_must_be_separately_listed]
  benchmark: *validator_audit_input
  sandbox: *validator_audit_input
  simulation: *validator_audit_input

Execution protocol

Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.

  1. You MUST load skill enumerate-validator-assumptions to enumerate embedded validator assumptions.
  2. You MUST load skill build-noncircularity-matrix to cross-tabulate target and validator assumptions.
  3. You MUST load skill detect-pass-by-construction to detect copied assumptions. You MUST load skill design-falsification-test to design an independent failure channel. Deviation: if no non-circular channel is feasible, return blocked validation rather than a pass.

Output contract

yaml
mode_contracts:
  validator: &validator_audit_output
    produces: [noncircularity_matrix, red_cell_actions, validator_verdict, adversarial_ground_truth_set]
    delta_fields: [findings, evidence_updates, uncertainties, decisions, open_questions]
  benchmark: *validator_audit_output
  sandbox: *validator_audit_output
  simulation: *validator_audit_output

Thresholds and quality gates

  • At least one validator path must be independent of the target's defining assumptions.
  • Shared or derived-from-target dependencies must be explicit in the matrix.

Failure and counterexamples

Pass-by-construction is a finding, not evidence of corroboration. Unknown dependencies remain unresolved.

Provenance map

  • resolved: circular-validation-audit

Preserved source criteria ledger

sourcesource linekindsource criterion
v4 architecturenode desctextualBuild claim-validator assumption matrix and require a non-circular failure channel.

Context checkpoint / Delta notes

Append assumptions, matrix cells, circularity findings, and proposed independent test.

Mode branches

  • validator: inspect validator implementation assumptions.
  • benchmark: inspect benchmark construction and metric assumptions.
  • sandbox: inspect environment/oracle assumptions.
  • simulation: inspect simulator and initialization assumptions.

Frequently asked questions

What does the Audit Validator Independence AI skill do?

Audit whether a validator, benchmark, sandbox, or test can pass by construction because it embeds the same assumptions as the theory it claims to validate. Build a claim×validator-assumption matrix and demand at least one non-circular failure channel.

Why use Audit Validator Independence on TypingMind?

Because you install it once and use it with any model. Audit Validator Independence is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Audit Validator Independence in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yogsoth-ai/de-anthropocentric-research-engine/tree/main/skills/audit-validator-independence. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Audit Validator Independence?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Audit Validator Independence?

As many as you like. As long as a model supports skills, you can use Audit Validator Independence with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Audit Validator Independence AI skill free?

Yes. It is published on GitHub by yogsoth-ai under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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