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 vfarcic/dot-ai --skill dot-ai-impact_analysisgit clone --depth 1 https://github.com/vfarcic/dot-aiWrote 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/vfarcic/dot-ai/dot-ai-impact_analysis)<a href="https://agentmods.dev/skills/vfarcic/dot-ai/dot-ai-impact_analysis"><img src="https://agentmods.dev/badge/skills/vfarcic/dot-ai/dot-ai-impact_analysis/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/vfarcic/dot-ai/dot-ai-impact_analysis"><img src="https://agentmods.dev/badge/skills/vfarcic/dot-ai/dot-ai-impact_analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00079 | $0.00187 |
| Opus 5 | $0.00039 | $0.00093 |
| Sonnet 5 | $0.00016 | $0.00037 |
| Haiku 4.5 | $0.00008 | $0.00019 |
Grade A, and why
dot-ai-impact_analysis 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 9d 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.
What it actually says
dot-ai impact_analysis
Analyze the blast radius of a proposed Kubernetes operation. Accepts free-text input: kubectl commands (e.g., "kubectl delete pvc data-postgres-0 -n production"), YAML manifests, or plain-English descriptions (e.g., "what happens if I delete the postgres database?"). Returns whether the operation is safe and a detailed dependency analysis with confidence levels.
Usage
dot-ai impact_analysis
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.
- 9d ago First seen · 16 lines · 79 tokens per session scan A 002300247429
dot-ai-impact_analysis is a skill published in the GitHub repository vfarcic/dot-ai (336 stars, last pushed yesterday), licensed MIT. It adds 79 tokens to every session and 187 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.
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