abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Classify stakeholder salience using power, legitimacy, urgency, dependency, or a supplied salience schema.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill classify-stakeholder-salience -a windsurf -y
name: classify-stakeholder-salience description: "Classify stakeholder salience using power, legitimacy, urgency, dependency, or a supplied salience schema."
Classify stakeholder salience using power, legitimacy, urgency, dependency, or a supplied schema.
required: [stakeholder_set, salience_schema] optional: [power_evidence, legitimacy_evidence, urgency_evidence, dependency_evidence] constraints: [each classification dimension needs an evidence status]
1. Normalize stakeholders and their relevant claims or stakes. 2. Score or categorize each stakeholder on the supplied salience dimensions. 3. Record dependency and conflict effects, then produce a prioritized salience map.
produces: [salience_map, dimension_scores, dependency_notes, priority_order] delta_fields: [findings, evidence_updates, uncertainties, decisions]
Do not equate high power with high legitimacy, and do not collapse conflicting dimensions into one unexplained rank.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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