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Skill

/design-mitigation

Design an intervention that prevents, detects, responds to, removes, or relaxes a failure mode/constraint; state residual risk and validation evidence.

From plugin
de-anthropocentric-research-engine
499200 skills
Install
$ npx -y skills add yogsoth-ai/de-anthropocentric-research-engine --skill design-mitigation --agent claude-code

How it fires

How this skill gets triggered: by you, by Claude, or both.

  • Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
  • You can call itInvoke it directly when you want it.
  • Slash command/design-mitigation

Context preview

The summary Claude sees to decide when to auto-load this skill.

Design an intervention that prevents, detects, responds to, removes, or relaxes a failure mode/constraint; state residual risk and validation evidence.

SKILL.md

design-mitigation.SKILL.md
name: design-mitigation
description: "Design an intervention that prevents, detects, responds to, removes, or relaxes a failure mode/constraint; state residual risk and validation evidence."

design-mitigation

Purpose

Design an intervention that prevents, detects, responds to, removes, or relaxes a failure mode.

Input contract

required: [failure_mode, causal_mechanism, resource_limits]
optional: [existing_controls, timeline, acceptance_criteria]
constraints: [residual risk and validation evidence must be explicit]

Procedure

1. Classify the failure and locate controllable causal points. 2. Generate prevention, detection, response, removal, and relaxation options. 3. Sequence selected actions with resources and validation tests. 4. Estimate residual risk and define escalation conditions.

If the mitigation has an explicit mechanism and measurable target, consider `validate-mitigation-effect` as the next tactic.

Output contract

produces: [mitigation_plan, validation_tests, residual_risk, success_criteria]
delta_fields: [decisions, findings, uncertainties]

Quality gates

  • Plan contains at least 3 sequenced actions when a multi-step intervention is feasible.
  • Each action has an owner-independent resource statement, validation test, and success criterion.
  • Residual risk is not reported as zero without evidence.

Parameterization

Caller supplies failure taxonomy, causal graph, intervention classes, resource schema, timeline, and risk scale.

Failure and counterexamples

Reject vague actions, controls that do not touch the mechanism, or plans without residual-risk accounting.

Provenance map

  • concept: stress-test/mitigation-design-sop
  • concept: stress-test/re-scoring
  • concept: convergence/removal-path
  • intermediate: Pass3/design-mitigation
  • intermediate: Pass3/design-removal-path
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Ships withde-anthropocentric-research-engine

The complete research orchestration system for AI-native science. What It Does Design Philosophy Architecture (v3.2.2) Quick Start Configuration Roadmap License DARE is not a tool that helps you do research. It is the researcher.

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