evaluate-falsifiability SKILL.md skillA
evaluate-falsifiability from yogsoth-ai/de-anthropocentric-research-engine is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add yogsoth-ai/de-anthropocentric-research-engine/evaluate-falsifiability@git:20260923.cbc38aaPins git:20260923.cbc38aa in mdr.lock. Pin the fingerprint instead.
- Audit grade
- A, 17 of 17 checks passed
- Kind
- SKILL.md skill
- Repository
- yogsoth-ai/de-anthropocentric-research-engine
- Path
skills/evaluate-falsifiability/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260923.cbc38aa, committed Sep 23, 2026
- Size
- 1,390 bytes
- Repository stars
- 508
- License
- Apache-2.0
Determine what observation would falsify a hypothesis and flag unfalsifiable formulations.
Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.
What the file says
# evaluate-falsifiability ## Purpose Evaluate whether a claim or hypothesis exposes observations that could count against it. ## Input contract ```yaml required: [claim, prediction_set, observation_domain] optional: [auxiliary_assumptions, measurement_limits] constraints: [falsifying conditions must be observable within the declared domain] ``` ## Procedure 1. Translate the claim into testable predictions and boundary conditions. 2. Identify observations that would contradict the claim under its assumptions. 3. Check whether those observations are measurable and independent of the claim's definition. 4. Classify falsifiability and list needed operationalization. ## Output contract ```yaml produces: [falsifiability_assessment, falsifying_observations, operationalization_gaps, assumption_dependencies] delta_fields: [findings, hypothesis_updates, uncertainties, open_questions] ``` ## Quality gates - At least one non-vacuous potential counter-observation is explicit for a falsifiable claim. - Auxiliary assumptions are separated from the core claim. ## Failure and counterexamples Do not call a claim falsifiable merely because it can be criticized rhetorically. …
Read the whole file at its exact version.
How to install
mdr add yogsoth-ai/de-anthropocentric-research-engine/evaluate-falsifiability@sha256:1547f99c5788d32dThe line at the top of this page pins the label git:20260923.cbc38aa, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.
[](https://markdownregistry.com/a/art_gooaxpgss3bsyvra)
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Versions
The registry has recorded 1 version of this file, committed on Sep 23, 2026.
Audit of the latest version
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Source
yogsoth-ai/de-anthropocentric-research-engine · 508 stars · license Apache-2.0 · pushed 2026-10-23 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_gooaxpgss3bsyvra GET https://markdownregistry.com/api/v1/resolve?ref=yogsoth-ai/de-anthropocentric-research-engine/evaluate-falsifiability GET https://markdownregistry.com/api/v1/blob/1547f99c5788d32db7e03e5eabdb8e00cf26282d94546ec1836a40b58d4b5ab2
Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.
Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.