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 paruff/uFawkesAI --skill e2e-rollbackgit clone --depth 1 https://github.com/paruff/uFawkesAIWrote 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/paruff/ufawkesai/e2e-rollback)<a href="https://agentmods.dev/skills/paruff/ufawkesai/e2e-rollback"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/e2e-rollback.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 | $0.00034 | $0.00433 |
| Opus 5 | $0.00017 | $0.00217 |
| Sonnet 5 | $0.00007 | $0.00087 |
| Haiku 4.5 | $0.00003 | $0.00043 |
Grade A, and why
e2e-rollback 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 8d 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
Skill: E2E Rollback Testing
Load trigger:
"load e2e-rollback skill"> DORA: Cap 5 (Operational Resilience) Token cost: Low
Purpose
Validate rollback behavior under deployment failure.
Responsibilities
- Trigger failed deployment
- Validate rollback
- Validate GitOps state consistency
- Validate cluster state consistency
Inputs
- Failure scenario
Outputs
rollback-report.jsoncluster-diff.txt
Sub-Skills
| Skill | Purpose |
|---|---|
e2e-rollback/trigger |
Trigger controlled failure |
e2e-rollback/state-validation |
Validate rollback state |
Rollback Flow
1. Deploy invalid manifest
2. Controller detects failure
3. Controller triggers rollback
4. Previous version restored
5. GitOps state consistent
6. Cluster state consistent
Validation Rules
- Rollback triggered correctly
- Previous version restored
- GitOps state consistent
- Cluster state consistent
- No drift
Output Format
{
"skill": "e2e-rollback",
"status": "pass | fail",
"trigger": { "invalid_manifest_injected": true },
"rollback": { "triggered": true, "version": "v1.2.3", "time_s": 30 },
"gitops_state": "consistent",
"cluster_state": "consistent",
"drift": "none"
}
Success Criteria
- Successful rollback
- No drift
What ships with it
2 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.
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.
- 8d ago First seen · 80 lines · 34 tokens per session scan A 74d228feecd7
e2e-rollback is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 15d ago), licensed MIT. It adds 34 tokens to every session and 433 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 2026-08-31.
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