classify-assumption-vulnerability
SkillSecurityLets your agent rank assumptions by how critical they are and how likely they are to fail, flagging which need testing.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the classify-assumption-vulnerability skill
About this skill
Classify assumptions by load-bearing importance and vulnerability.
What this skill tells your AI
The instructions your AI receives, as published by yogsoth-ai/de-anthropocentric-research-engine in skills/classify-assumption-vulnerability/SKILL.md and read by ahel’s review.
Purpose
Classify assumptions by load-bearing importance and vulnerability to determine which require stress testing.
Input contract
required: [assumption_register, dependent_claims]
optional: [evidence_strength, perturbation_bounds]
constraints: [importance and vulnerability must be scored or categorized separately]
Procedure
- Link each assumption to the claims or causal edges it supports.
- Assess consequence of failure and current evidential support.
- Assign vulnerability class and prioritize assumptions for challenge.
Output contract
produces: [vulnerability_map, load_bearing_rank, challenge_queue]
delta_fields: [findings, assumption_updates, uncertainties, decisions]
Quality gates
- No assumption is ranked without a dependent claim and an evidence-status note.
Failure and counterexamples
Mark vulnerability unknown when consequence or support cannot be assessed; do not silently assign low risk.
Provenance map
deep-insight/abp-vulnerability-classification: resolved.
Signals
- GitHub stars
- 501
- Forks
- 41
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Key
classify-assumption-vulnerability- Source
- github.com/yogsoth-ai/de-anthropocentric-research-engine