claude

ai-alignment-reasoning

Alignment reasoning and harm anticipation translated into practitioner design skills.

3,339 on GitHubby MC Deanv1.2.0MITupdated 2 months agoai
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Plugin ai-alignment-reasoning from marketplace designer-skills in Owl-Listener/designer-skills. Commands read from the repo's manifest — 1 month ago.

What it installs

Skills (8)

  • bias-detection-design

    Designing review workflows to surface and mitigate bias in AI outputs.

  • consent-and-agency

    Designing for informed user consent, opt-out, and human override.

  • escalation-design

    When and how AI should escalate to humans, refuse, or ask for clarification.

  • guardrail-design

    Defining behavioral boundaries — what the AI should and shouldn't do.

  • harm-anticipation

    Proactively identifying failure modes, misuse, and unintended consequences.

  • transparency-patterns

    Showing users what the AI knows, doesn't know, and how confident it is.

  • trust-calibration

    Helping users form warranted trust in the AI — neither overtrust nor undertrust — through deliberate confidence and source signalling.

  • value-specification

    Translating organisational values and user expectations into system constraints.

Slash commands (3)

  • /ai-alignment-reasoning:design-guardrails

    Create a complete guardrail specification for an AI feature.

  • /ai-alignment-reasoning:red-team

    Run a structured red-teaming exercise to find alignment failures.

  • /ai-alignment-reasoning:write-policy

    Draft an AI behavior policy covering safety, tone, and boundaries.

View source on GitHub

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