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blast-radius-estimator

Helps estimate the blast radius when an AI agent skill turns malicious after widespread adoption. Analyzes inheritance chains, dependency graphs, and adoption trends to project how many agents could be affected.

andyxinweiminicloud0 source installs☆ 0 Repository starsv1.0.0

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install andyxinweiminicloud/blast-radius-estimator

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

What Happens When 1000 Agents Inherit a Malicious Skill? Estimating Blast Radius

Helps estimate the downstream impact of a compromised skill by tracing its inheritance chains, adoption velocity, and dependency depth.

Problem

A skill is safe today. 500 agents adopt it. Then the publisher pushes a malicious update. How many agents are now compromised? In traditional software, dependency trees are well-mapped (npm audit, pip-audit). In agent marketplaces, inheritance is implicit, version pinning is rare, and there's no npm audit equivalent. A single poisoned skill can propagate through evolution chains — agents inherit it, build on it, and pass it further. Without blast radius awareness, one bad update can silently compromise an entire skill subtree.

What This Checks

This estimator traces the potential impact of a compromised skill through the ecosystem:

  1. Direct adopters — How many agents currently use this skill directly? Based on download counts, citation data, and known installations
  2. Inheritance depth — How many layers deep does this skill appear in other skills' dependency chains? A skill used by skills used by skills multiplies impact
  3. Adoption velocity — How fast is adoption growing? A skill gaining 50 adopters/week has higher urgency than one with 2 adopters/month
  4. Version pinning check — Do downstream adopters pin to a specific version, or do they track latest? Unpinned adopters receive malicious updates automatically
  5. Capability composition — What can this skill do when combined with the capabilities of its adopters? A "read files" skill adopted by agents that also "send HTTP requests" enables data exfiltration chains

How to Use

Input: Provide one of:

  • A Gene/Capsule identifier (URL, SHA-256, or slug)
  • A marketplace asset page URL
  • A skill name to search for in the ecosystem

Output: A blast radius report containing:

  • Estimated direct and transitive impact count
  • Inheritance tree visualizatio...

Source information

Source
github
Repository
openclaw/skills
Path
skills/andyxinweiminicloud/blast-radius-estimator
Version
1.0.0
Commit
bba18fb9e2729607a50a88ab86901a2c8a12f6e4
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# What Happens When 1000 Agents Inherit a Malicious Skill? Estimating Blast Radius

> Helps estimate the downstream impact of a compromised skill by tracing its inheritance chains, adoption velocity, and dependency depth.

## Problem

A skill is safe today. 500 agents adopt it. Then the publisher pushes a malicious update. How many agents are now compromised? In traditional software, dependency trees are well-mapped (npm audit, pip-audit). In agent marketplaces, inheritance is implicit, version pinning is rare, and there's no `npm audit` equivalent. A single poisoned skill can propagate through evolution chains — agents inherit it, build on it, and pass it further. Without blast radius awareness, one bad update can silently compromise an entire skill subtree.

## What This Checks

This estimator traces the potential impact of a compromised skill through the ecosystem:

1. **Direct adopters** — How many agents currently use this skill directly? Based on download counts, citation data, and known installations
2. **Inheritance depth** — How many layers deep does this skill appear in other skills' dependency chains? A skill used by skills used by skills multiplies impact
3. **Adoption velocity** — How fast is adoption growing? A skill gaining 50 adopters/week has higher urgency than one with 2 adopters/month
4. **Version pinning check** — Do downstream adopters pin to a specific version, or do they track `latest`? Unpinned adopters receive malicious updates automatically
5. **Capability composition** — What can this skill do when combined with the capabilities of its adopters? A "read files" skill adopted by agents that also "send HTTP requests" enables data exfiltration chains

## How to Use

**Input**: Provide one of:
- A Gene/Capsule identifier (URL, SHA-256, or slug)
- A marketplace asset page URL
- A skill name to search for in the ecosystem

**Output**: A blast radius report containing:
- Estimated direct and transitive impact count
- Inheritance tree visualizatio...

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