Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/cxcscmu/skilllearnbench/cvss-score-extractionnpx skills add cxcscmu/SkillLearnBench --skill cvss-score-extractiongit clone --depth 1 https://github.com/cxcscmu/SkillLearnBenchWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/cxcscmu/skilllearnbench/cvss-score-extraction)<a href="https://agentmods.dev/skills/cxcscmu/skilllearnbench/cvss-score-extraction"><img src="https://agentmods.dev/badge/skills/cxcscmu/skilllearnbench/cvss-score-extraction.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00032 | $0.00864 |
| Opus 5 | $0.00016 | $0.00432 |
| Sonnet 5 | $0.00006 | $0.00173 |
| Haiku 4.5 | $0.00003 | $0.00086 |
Grade A, and why
cvss-score-extraction scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 123 lines — stays where its author put it; the contents beside it link to each section on GitHub.
CVSS Score Extraction
Overview
CVSS (Common Vulnerability Scoring System) scores quantify vulnerability severity from 0-10. Different sources may provide different scores, requiring intelligent fallback handling.
Score Sources
NVD (National Vulnerability Database)
- Official US government vulnerability database
- Provides CVSS v3.0 and v3.1 scores
- Most comprehensive coverage
- URL pattern:
https://nvd.nist.gov/vuln/detail/{CVE_ID}
GHSA (GitHub Security Advisory)
- GitHub's vulnerability advisory database
- Integrated with npm ecosystem
- URL pattern:
https://github.com/advisories/{GHSA_ID}
RedHat Security
- RedHat-specific vulnerability data
- Often has additional context
- URL pattern:
https://access.redhat.com/security/cve/{CVE_ID}
Source Priority
For optimal results, use this priority:
- NVD CVSS v3.1 (most reliable, modern scoring)
- NVD CVSS v3.0 (fallback, still reliable)
- GHSA CVSS (GitHub advisory ecosystem)
- RedHat CVSS (distribution-specific)
- N/A (if no score available)
Data Extraction Pattern
def extract_cvss_score(vuln_data):
"""
Extract CVSS score with source priority fallback.
vuln_data: vulnerability object from Trivy or similar
returns: (score, source) tuple
"""
# Check NVD first (most authoritative)
if 'nvd_cvss_v3_1' in vuln_data:
return (vuln_data['nvd_cvss_v3_1'], 'NVD')
if 'nvd_cvss_v3_0' in vuln_data:
return (vuln_data['nvd_cvss_v3_0'], 'NVD')
# Check GitHub Advisory
if 'ghsa_cvss' in vuln_data:
return (vuln_data['ghsa_cvss'], 'GHSA')
# Check RedHat
if 'redhat_cvss' in vuln_data:
return (vuln_data['redhat_cvss'], 'RedHat')
# No score available
return ('N/A', 'Unknown')
Handling Missing Scores
When CVSS scores are unavailable:
def get_cvss_with_fallback(cve_id, vuln_sources):
"""
Query multiple sources for CVSS score.
cve_id: CVE identifier (e.g., CVE-2021-12345)
vuln_sources: list of available data sources
returns: (score_value, source_name)
"""
for source in vuln_sources:
score = source.get_cvss(cve_id)
if score:
return (score, source.name)
# Fallback: use severity level as proxy
return ('N/A', 'No Score Available')
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 123 lines · 32 tokens per session scan A 720612a1b278
cvss-score-extraction is a skill published in the GitHub repository cxcscmu/SkillLearnBench (83 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 864 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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