Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/fabioespindula/awesome-nanoclaw-skillsnpx agentmods add skills/fabioespindula/awesome-nanoclaw-skills/xrayWrote 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/fabioespindula/awesome-nanoclaw-skills/xray)<a href="https://agentmods.dev/skills/fabioespindula/awesome-nanoclaw-skills/xray"><img src="https://agentmods.dev/badge/skills/fabioespindula/awesome-nanoclaw-skills/xray/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/fabioespindula/awesome-nanoclaw-skills/xray"><img src="https://agentmods.dev/badge/skills/fabioespindula/awesome-nanoclaw-skills/xray.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 | $0.00077 | $0.01564 |
| Opus 5 | $0.00039 | $0.00782 |
| Sonnet 5 | $0.00015 | $0.00313 |
| Haiku 4.5 | $0.00008 | $0.00156 |
Grade A, and why
xray 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 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.
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 — 173 lines — stays where its author put it; the contents beside it link to each section on GitHub.
XRay
Use this skill to turn content into visual understanding.
XRay is not a summary skill. It reveals structure, intent, assumptions, dependencies, and usable meaning.
Managed Auto Update
If this skill is installed as a managed Awesome NanoClaw Skill and ../awesome-updater/scripts/awesome_skills.py exists, run this before the normal workflow:
python3 ../awesome-updater/scripts/awesome_skills.py check awesome-updater --skills-dir .. || true
python3 ../awesome-updater/scripts/awesome_skills.py discover --skills-dir .. || true
python3 ../awesome-updater/scripts/awesome_skills.py check xray --skills-dir .. || true
Continue the normal workflow if the update or discover check fails because of network, GitHub, or local environment issues.
Load References
- Read
references/output-structure.mdbefore producing normal XRay output. - Read
references/source-type-behavior.mdbefore adapting the explanation to a prompt, spec, website, article, transcript, PDF, code, or technical document. - Use
references/sample-runs.mdfor help, documentation, and validation examples. Do not load sample runs for every normal XRay.
Triggers
Run this skill when the user:
- invokes
/xrayor/visual-explain; - asks for a mental map, visual explanation, scan, breakdown, or structure-first explanation;
- asks to explain a prompt, article, site, spec, doc, PDF excerpt, transcript, code, or complex concept;
- says phrases like "make a mental map of this", "explain this visually", "give me a scannable read", "decode this content", or "make this easy to understand".
Help Mode
If the user invokes /xray help, /xray examples, or /visual-explain help, explain usage instead of analyzing content.
The help response should include:
- what XRay does;
- when to use it;
- command forms:
/xray <content>,/xray short <content>,/xray long <content>,/visual-explain <content>, and/nanoskills help xray; - what input the user should provide;
- what output the user gets;
- curated examples;
- contextual examples when the visible conversation contains a usable topic, source, prompt, or document.
What ships with it
5 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.
- 12d ago First seen · 173 lines · 77 tokens per session scan A 6db45757393c
xray is a skill published in the GitHub repository fabioespindula/awesome-nanoclaw-skills (2 stars, last pushed 4mo ago), licensed MIT. It adds 77 tokens to every session and 1,564 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 2026-08-31.
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