Skip to content
Agentmart
Submit a tool

falsification-first-audit

Convert a sharp scientific claim into the cheapest decisive falsification program.

Skill by yogsoth-ai

IndexedApache-2.0★ 505
Write a review

Install

Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.

npx agentmarket install skill/yogsoth-ai-falsification-first-audit

Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.

Get the weekly diff

The weekly diff: one email a week with new agent tools, notable updates and grade changes, plus security alerts for tools you follow. Double opt-in, one-click unsubscribe.

We use your email only for this newsletter. Privacy

About

Convert a sharp scientific claim into the cheapest decisive falsification program. Steelman the claim into a precise testable form, specify observations/computations that could break it, execute the most informative probes first, and return only BROKEN, CORROBORATED, or UNFALSIFIABLE rather than a resilience score.

Use cases: security, research

No reviews yet. Installed it? Reviews come from verified installers only. How reviews work

Permissions

What this skill can do and what it asks for, from its SKILL.md and code. Checked Oct 26, 2026.

Tools
No tools found
Secrets
None asked for
Install scripts
None found

Network hosts it talks to 1

  • codeload.github.com · found in install command

Files it touches

  • ~/.claude/skills/falsification-first-audit

What's inside

Skill name
falsification-first-audit
Description
Convert a sharp scientific claim into the cheapest decisive falsification program. Steelman the claim into a precise testable form, specify observations/computations that could break it, execute the most informative probes first, and return only BROKEN, CORROBORATED, or UNFALSIFIABLE rather than a resilience score.
License
Apache-2.0
Instructions
57 lines in SKILL.md · view on GitHub

Files (1)

  • SKILL.md

SKILL.md (first lines)

# falsification-first-audit
## Purpose
Convert a sharp claim into the cheapest decisive falsification program and return BROKEN, CORROBORATED, or UNFALSIFIABLE.
## Input contract
```yaml
mode_contracts:
  sharp-claim: &falsification_input
    required: [claim, scope, available_evidence]
    optional: [mechanism, candidate_tests]
    constraints: [claim_must_expose_observable_consequences_and_boundary_conditions]
  truthseeking-debate: *falsification_input
  truthseeking-red-team: *falsification_input
```
## Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.

1. You MUST load skill `sharpen-falsifiable-claim` to sharpen the claim. You MUST load skill `surface-assumptions` to expose its assumptions.
2. You MUST load skill `design-falsification-test` to design the cheapest decisive falsification test.
3. You MUST load skill `execute-probe` to execute the most informative probe.
4. You MUST load skill `classify-falsification-verdict` to classify only the permitted truth-seeking verdict.
   If the claim depends on a structural mapping, consider `audit-structural-equivalence`. If the test or oracle may be circular, consider `audit-validator-independence`. If agreement among paths may not be independent, consider `audit-convergence-independence`. If simplicity is carrying the claim, consider `audit-explanatory-compression`. If survival is confined to an uncertain region, consider `map-validity-envelope`.
Deviation: if no legitimate falsifier can be specified or reached, stop with UNFALSIFIABLE; do not substitute a resilience score.
## Output contract
```yaml
mode_contracts:
  sharp-claim:
    produces: [claim_falsifiability, refutation_condition, attacks_attempted, outcome_bucket, refutation_or_surviving_forbidden_content, honest_residue]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions]
  truthseeking-debate:
    produces: [most_falsifiable_form, committed_refuter, cross_examination_findings, attack_severity, outcome_bucket, refutation_or_forbidden_content]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions]
  truthseeking-red-team:
    produces: [claim_load_rank, assumption_classification, refutation_condition, refutation_attempt, outcome_bucket, framing_risk_brief]
    delta_fields: [findings, evidence_updates, hypothesis_updates, uncertainties, decisions]
```
## Thresholds and quality gates
- Verdict is BROKEN only when a legitimate falsifier succeeds; CORROBORATED only after an adequate test fails to falsify; otherwise UNFALSIFIABLE.
- Preserve scope, power/precision assumptions, and probe provenance.
## Failure and counterexamples
Post-hoc accommodation, unfalsifiable wording, or an unreachable test cannot support CORROBORATED.
## Provenance map
- resolved: falsification-first-stress-test
- resolved: adversarial-debate-truthseeking
- resolved: red-team-truthseeking
## Preserved source criteria ledger
| source | source line | kind | source criterion |
|---|---:|---|---|
| v4 architecture | node desc | textual | Return only BROKEN, CORROBORATED, or UNFALSIFIABLE; no resilience score. |
## Context checkpoint / Delta notes
Append sharpened claim, test design, probe result, verdict, and unresolved falsifier questions.

## Mode branches
- `sharp-claim`: direct falsification program.
- `truthseeking-debate`: combine with adversarial exchange while preserving verdict semantics.
- `truthseeking-red-team`: use attack probes while preserving verdict semantics.

From yogsoth-ai/de-anthropocentric-research-engine, Apache-2.0.

More from yogsoth-ai/de-anthropocentric-research-engine

Signals

Stars
505
Forks
43
Open issues
1
Last commit (this folder)
Sep 23, 2026 (1 month ago)
Last release
Oct 23, 2026 (5 days ago)

From GitHub (fetched Oct 24, 2026).

Details

License
Apache-2.0
First seen
Oct 24, 2026
Last checked
Oct 24, 2026

More from yogsoth-ai

Cite this page

falsification-first-audit skill. Agent Mart. https://agentmart.dev/skills/yogsoth-ai-falsification-first-audit (last updated 2026-10-24)