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 formulate-research-questionBefore 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.
Rendered from the source repository. Headings, examples, code, tables, links, and referenced images are preserved.
formulate-research-question
Purpose
Convert a hypothesis into a precise research question with fit-for-purpose framework, scope, feasibility, and success criteria.
Input contract
required: [hypothesis_or_gap, candidate_frameworks, feasibility_constraints]
optional: [assumptions, prior_findings, evidence_updates]
constraints: [consume named scientific objects; preserve provenance; keep unresolved uncertainty visible]Execution protocol
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
- You MUST load skill
apply-question-frameworkto construct the question under the selected framework. - You MUST load skill
assess-question-qualityto assess answerability, significance, and precision. - You MUST load skill
define-criteriato define the question-quality criteria. - You MUST load skill
set-thresholdto set the acceptance thresholds. - You MUST load skill
adjust-abstraction-scopeto correct the abstraction level and scope.
If the accepted question contains dependent subproblems, consider decompose-research-question as the next tactic.
Deviation: reorder only when a dependency is already satisfied or unavailable; record the reason and confidence effect.
Output contract
produces: [research_question, success_criteria, scope_decision]
delta_fields: [decisions, open_questions]Thresholds and quality gates
- Each output is traceable to an input object, operation, and evidence reference.
- Scope, assumptions, and unresolved alternatives remain explicit.
- Retain $\alpha$ 0.05 and power 0.8 wherever the predeclared statistical design requires them.
Failure and counterexamples
Stop synthesis when a required object is absent, a precondition is violated, or a counterexample invalidates the proposed conclusion; return the partial delta with the failure recorded.
Provenance map
- resolved: research-question
- resolved: framework-guided-formulation
- resolved: scope-calibration
- resolved: comparative-formulation
- resolved: feasibility-constrained-formulation
- resolved: framework-selection-and-application
- resolved: question-refinement-loop
Preserved source criteria ledger
| source | criterion | treatment |
|---|---|---|
| resolved v3 entries above | node-specific criteria | retained and specialized to the v4 object contract |
| experiment-execution/statistical-testing | $\alpha$ = 0.05 | fixed value retained where applicable |
| experiment-execution/sample-size-estimation | power = 0.8 | fixed value retained where applicable |
Context checkpoint / Delta notes
Return the node-specific research-state delta and preserve findings, evidence updates, uncertainties, decisions, open questions, and recommended jumps as applicable.
