abstract-structure
Remove domain surface details to expose transferable relational/mechanistic structure at a chosen abstraction level.
Detect and characterize reinforcing/balancing feedback loops, participating variables, delays, and possible breakpoints.
Claude Code
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop --agent claude-code
Codex
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a codex -y
Cursor
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a cursor -y
Gemini CLI
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a gemini-cli -y
GitHub Copilot
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a github-copilot -y
OpenCode
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a opencode -y
Windsurf
$ npx skills add yogsoth-ai/de-anthropocentric-research-engine --skill detect-feedback-loop -a windsurf -y
name: detect-feedback-loop description: "Detect and characterize reinforcing/balancing feedback loops, participating variables, delays, and possible breakpoints."
Detect reinforcing or balancing feedback loops in a causal or process structure and state the evidence for each loop.
required: [causal_graph, node_semantics, edge_polarity] optional: [time_delays, observed_series, intervention_records] constraints: [loop classification requires directed edges and polarity or transition evidence]
1. Normalize directed relations, polarity, and delays. 2. Enumerate simple cycles and identify reinforcing or balancing sign patterns. 3. Compare loops with observations or intervention evidence where available. 4. Report loop boundaries, uncertain edges, and testable implications.
produces: [feedback_loops, loop_classification, supporting_evidence, uncertain_edges, testable_implications] delta_fields: [findings, evidence_updates, uncertainties, recommended_jumps]
Do not infer feedback from a static co-occurrence or omit time direction where it determines loop meaning.
A research skill graph for AI-native science. 271 markdown files. No runtime, no dependencies, no build step.
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