abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Convert a hypothesis into a precise research question with fit-for-purpose framework, scope, feasibility, and success criteria.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill formulate-research-question -a windsurf -y
name: formulate-research-question description: "Convert a hypothesis into a precise research question with fit-for-purpose framework, scope, feasibility, and success criteria."
Convert a hypothesis into a precise research question with fit-for-purpose framework, scope, feasibility, and success criteria.
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]
Do not perform called SOP operations inline; each loaded SOP owns its contract and thresholds.
1. You MUST load skill `apply-question-framework` to construct the question under the selected framework. 2. You MUST load skill `assess-question-quality` to assess answerability, significance, and precision. 3. You MUST load skill `define-criteria` to define the question-quality criteria. 4. You MUST load skill `set-threshold` to set the acceptance thresholds. 5. You MUST load skill `adjust-abstraction-scope` to 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.
produces: [research_question, success_criteria, scope_decision] delta_fields: [decisions, open_questions]
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.
| 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 |
Return the node-specific research-state delta and preserve findings, evidence updates, uncertainties, decisions, open questions, and recommended jumps as applicable.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Evaluate competing arguments against stated criteria and produce a reasoned verdict with uncertainty.
Move a scientific object up/down in abstraction or narrow/broaden selected scope dimensions (population, mechanism, context,…
Run structured attack/defense/adjudication over a claim, candidate, criterion set, or current winner. Perspective, target,…
Aggregate criterion or comparison results into an ordered recommendation under an explicit rule.
Abstract relational structure from source domains, map it to the target, validate depth, and instantiate transferable mechanisms.
Direct browser control via CDP for web interaction: automation, scraping, testing, screenshots, and site/app work. Also covers…
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling…