abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Reframe a problem around functioning exceptions, existing strengths, positive deviance, and conditions under which desired behavior already occurs.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill appreciative-reframe -a windsurf -y
name: appreciative-reframe description: "Reframe a problem around functioning exceptions, existing strengths, positive deviance, and conditions under which desired behavior already occurs."
Reframe a problem around functioning exceptions, strengths, positive deviance, and conditions supporting desired behavior.
required: [problem_statement, functioning_exceptions] optional: [stakeholders, outcome_definition] constraints: [exceptions must be observed cases, not aspirations]
1. Identify cases where the desired behavior already occurs. 2. Extract the enabling conditions and strengths present in those cases. 3. Rewrite the research question around reproducing or extending those conditions.
produces: [exception_inventory, enabling_conditions, appreciative_reframe] delta_fields: [findings, hypothesis_updates, decisions]
Reject success stories that are unverified, incomparable, or explained only by selection bias.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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