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/unitoneai/securityskills/patch-prioritizationnpx skills add UnitOneAI/SecuritySkills --skill patch-prioritizationgit clone --depth 1 https://github.com/UnitOneAI/SecuritySkillsWhat 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 | $0.00088 | $0.05564 |
| Opus 5 | $0.00044 | $0.02782 |
| Sonnet 5 | $0.00018 | $0.01113 |
| Haiku 4.5 | $0.00009 | $0.00556 |
Grade A, and why
patch-prioritization 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 2d 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 — 413 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Patch Prioritization & SLA Management -- SSVC 2.1 / EPSS v3 / CISA KEV
Frameworks: SSVC 2.1 (CERT/CC), EPSS v3 (FIRST.org), CISA KEV (DHS/CISA) Role: Security Engineer, vCISO Time: 20-40 min Output: Prioritized patch plan with SLA assignments, exception documentation, and risk acceptance artifacts
When to Use
If a target is provided via arguments, focus the review on: $ARGUMENTS
Use this skill when managing a vulnerability remediation backlog, when assigning or validating patch SLAs, when a patch window needs to be scheduled against business constraints, when evaluating compensating controls as interim mitigation, or when processing risk acceptance or exception requests for deferred patches.
Do not use when: The task is initial CVE triage and severity scoring (use cve-triage), detection rule creation for unpatched systems (use detection-engineering), or SBOM-level dependency analysis (use sbom-analysis).
Context the Agent Needs
Before starting, collect or confirm:
- Vulnerability inventory: List of CVEs or vulnerability findings pending remediation, including scanner source (Qualys, Tenable, Rapid7, Snyk, Trivy)
- Current SLA assignments: Existing SLA tiers and deadlines for each finding, if previously triaged
- Asset inventory context: Business criticality, exposure (internet-facing, internal, air-gapped), owner, and environment (production, staging, dev) for affected systems
- Patch availability: Whether vendor patches, hotfixes, or workarounds exist for each CVE
- Change management constraints: Maintenance windows, freeze periods, change advisory board (CAB) schedules
- Compensating controls inventory: WAF rules, network segmentation, EDR policies, disabled features currently in place
- Compliance mandates: Applicable regulatory requirements (CISA BOD 22-01, PCI DSS 4.0 Requirement 6.3.3, HIPAA, FedRAMP)
- Historical EPSS data: EPSS score trends over 7/30/90 days if available (API: https://api.first.org/data/v1/epss)
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.
- 2d ago First seen · 413 lines · 88 tokens per session scan A bde59ea64258
patch-prioritization is a skill published in the GitHub repository UnitOneAI/SecuritySkills (58 stars, last pushed 2mo ago), licensed MIT. It adds 88 tokens to every session and 5,564 once invoked, about $0.0004 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.
Other skills, from other repositories
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cis-aws-foundations-4.1
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cis-aws-foundations-4.3
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cis-aws-foundations-2.1.1
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cis-aws-foundations-2.1.3
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