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 overlay-resolutiongit 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/overlay-resolution)<a href="https://agentmods.dev/skills/paruff/ufawkesai/overlay-resolution"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/overlay-resolution/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/paruff/ufawkesai/overlay-resolution"><img src="https://agentmods.dev/badge/skills/paruff/ufawkesai/overlay-resolution.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 | $0.00032 | $0.00493 |
| Opus 5 | $0.00016 | $0.00246 |
| Sonnet 5 | $0.00006 | $0.00099 |
| Haiku 4.5 | $0.00003 | $0.00049 |
Grade A, and why
overlay-resolution-testing 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: Overlay Resolution Testing
Load trigger:
"load overlay-resolution-testing skill"> DORA: Cap 4 (CI/CD Automation) Token cost: Low
Purpose
Validate that OBS resolves environment overlays correctly.
Responsibilities
- Validate dev/stage/prod overlays
- Validate configmap and secret references
- Validate patch merging
Inputs
overlays/- OBS output
Outputs
overlay-resolution.json
Overlay Structure
overlays/
├── dev/
│ ├── kustomization.yaml
│ ├── configmap.yaml
│ └── patches/
├── staging/
│ ├── kustomization.yaml
│ ├── configmap.yaml
│ └── patches/
└── prod/
├── kustomization.yaml
├── configmap.yaml
└── patches/
Validation Rules
- All overlays resolve cleanly
- Configmaps valid
- Secrets references valid
- Patches applied correctly
- No missing bases
Output Format
{
"skill": "overlay-resolution-testing",
"status": "pass | fail",
"overlays": {
"dev": {"resolve": "pass", "configmaps": "pass", "secrets": "pass", "patches": "pass"}, # pragma: allowlist secret
"staging": {"resolve": "pass", "configmaps": "pass", "secrets": "pass", "patches": "pass"}, # pragma: allowlist secret
"prod": {"resolve": "pass", "configmaps": "pass", "secrets": "pass", "patches": "pass"} # pragma: allowlist secret
}
}
Success Criteria
- All overlays resolve cleanly
- No missing bases or overlays
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 · 79 lines · 32 tokens per session scan A 115d625d61f4
overlay-resolution-testing is a skill published in the GitHub repository paruff/uFawkesAI (2 stars, last pushed 19d ago), licensed MIT. It adds 32 tokens to every session and 493 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 2026-09-03.
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