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 skills add opendatahub-io/autofix-skills --skill autofix-cve-resolvegit clone --depth 1 https://github.com/opendatahub-io/autofix-skillsWrote 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/opendatahub-io/autofix-skills/autofix-cve-resolve)<a href="https://agentmods.dev/skills/opendatahub-io/autofix-skills/autofix-cve-resolve"><img src="https://agentmods.dev/badge/skills/opendatahub-io/autofix-skills/autofix-cve-resolve/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/opendatahub-io/autofix-skills/autofix-cve-resolve"><img src="https://agentmods.dev/badge/skills/opendatahub-io/autofix-skills/autofix-cve-resolve.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00059 | $0.01652 |
| Opus 5 | $0.00030 | $0.00826 |
| Sonnet 5 | $0.00012 | $0.00330 |
| Haiku 4.5 | $0.00006 | $0.00165 |
Grade C, and why
autofix-cve-resolve scanned grade C with 1 finding 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 12d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
- NEVER run `rm -rf` on paths outside `/tmp` How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: CVE Resolve Orchestrator
Orchestrate CVE remediation using a Python state machine for deterministic routing. You call specialized agent prompts in sequence for each affected repository and branch. You NEVER write fix code yourself — you only parse context, resolve repos, route to agents, create PRs, and write the verdict.
Initialize pipeline
python3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py init tmp/cve-state.yaml
Loop: State machine dispatch
Repeat until the state machine reaches finalize:
# Get next action
python3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py next tmp/cve-state.yaml
This returns a JSON object with:
action: what to doprompt_file: which prompt file to read (null for orchestrator-only actions)args: context for the actionphase: current phase
Execute the action
Based on the current phase:
parse — Extract CVE details from .autofix-context/ticket.json:
- CVE ID, container, package, component, severity, Jira key
- Resolve repositories via
component-repository-mappings.json - Check for automation-ignore comments
- Write repos to state:
python3 ${CLAUDE_SKILL_DIR}/scripts/state.py set tmp/cve-state.yaml repos '[{"name":"org/repo","branches":["main","release-1.0"],"type":"upstream"}]' - Verify the CVE is publicly known before proceeding:
If this returns non-zero, the CVE is not found in public vulnerability databases and may be embargoed. Transition withpython3 ${CLAUDE_SKILL_DIR}/scripts/cve_pipeline.py check-cve tmp/cve-state.yamlembargoedinstead ofparsed. - Transition:
parsed(orignoreif automation-ignore found, orembargoedif CVE is not publicly known)
scan — Read prompts/scan-agent.md and execute for the repo/branch from args.
Read ONLY the verdict from autofix-output/cve-scan-result.json.
- Transition:
presentorabsent
route — Based on scan verdict:
present/present_by_version→ transition:fixabsent/informational→ transition:vexin_base_imagewith no newer tag → transition:skipscan_failed→ transition:skip
What ships with it
18 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
- prompts/fix-agent.md 11 KB
- prompts/review-agent.md 45 B
- prompts/scan-agent.md 3.3 KB
- prompts/verify-agent.md 2.7 KB
- prompts/vex-agent.md 4.3 KB
- references/templates.md 4.6 KB
- references/verdict-schema.md 2.1 KB
- schemas/cve-fix-result.json 1.7 KB
- schemas/cve-scan-result.json 493 B
- schemas/cve-verdict.json 2.9 KB
- schemas/cve-verify-result.json 422 B
- schemas/cve-vex-result.json 1.1 KB
- scripts/check-existing-prs.sh 4.3 KB runs code
- scripts/cve_pipeline.py 11 KB runs code
- scripts/scan.sh 8.1 KB runs code
- scripts/state.py 7.8 KB runs code
- scripts/verify.sh 6.2 KB runs code
- scripts/write_json.py 8.4 KB runs code
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.
- 12d ago First seen · 157 lines · 59 tokens per session scan C d014e855c91b
autofix-cve-resolve is a skill published in the GitHub repository opendatahub-io/autofix-skills (2 stars, last pushed 12d ago), licensed Apache-2.0. It adds 59 tokens to every session and 1,652 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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