How to use
- Copy the installation command and review the source package before installing it in your own agent environment.
- Check the source document for required tools, credentials and supported hosts.
- Describe your input and desired deliverable; review the output against the source material.
npx skills add https://github.com/yogsoth-ai/de-anthropocentric-research-engine --skill select-critical-caseBefore you start
- Installation does not include a model subscription, API allowance or permission to access your files.
- Repository stars and installation counts describe activity, not an independent quality or security test.
Original skill document
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
select-critical-case
Purpose
Select most-likely, least-likely, or otherwise inference-maximizing cases that can decisively support or refute a claim.
Input contract
yaml
required: [claim, case_universe, selection_logic]
optional: [likelihood_model, boundary_conditions]
constraints: [case selection rule and inference purpose must be explicit]Procedure
- Define the eligible case universe and selection objective.
- Rank cases under the declared logic.
- Select and justify the critical case, including excluded cases.
Output contract
yaml
produces: [critical_case, selection_rationale, excluded_cases, inference_role]
delta_fields: [findings, evidence_updates, uncertainties, decisions]Quality gates
- Selected case must be traceable to the stated selection logic.
Failure and counterexamples
Do not call a convenient case critical without comparing it to the declared universe.
Provenance map
- resolved: critical-case-design
- resolved: counterexample-heuristics
