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Map the structure of disagreement across perspectives using Policy Delphi, Argument Delphi, or SAST methods.
Passed 18 of 22 test cases with the skill, and 6 of 22 without it.
and 9 more in the full report
13 fixed5 passed either way3 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 13 test cases the skill fixed. Same model, same prompt, with and without the skill.
Generative AI training on copyrighted material has split rights holders, tech firms, open-source developers, and legal scholars. Format your analysis as structured YAML representing the opinion landscape with clusters, fault lines, and bridging possibilities rather than recommending a legal ruling.
| Checked | Without skill | With skill |
|---|---|---|
| Output includes top-level key fault_lines in valid YAML. | Passed | Passed |
| Each item under fault_lines includes a between field listing compared clusters. | Missed | Passed |
The instructions your model reads when the skill loads.
Purpose: Rather than forcing convergence, map the topology of disagreement — identify clusters of opinion, the arguments supporting each cluster, and the fault lines between them. Useful for wicked problems where premature consensus would be harmful.
When to use:
| Parameter | Constraint |
|---|---|
| Rounds | 1–2 (mapping, not converging) |
| Perspectives | ≥4 independent |
| Cluster minimum | ≥2 distinct clusters to be useful |
| Key | Type | Description |
|---|---|---|
| question | string | The focal question or issue |
| perspectives | array | List of perspective descriptions |
| judgments | array | Raw collected judgments |
| clusters | array | Identified opinion clusters |
| arguments | array | Extracted arguments per cluster |
| disagreement_map | object | Final visualization structure |
test cases passed, vs 6 / 22 without
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