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 pyworkload/3x-ui-mcp --skill reality-inboundgit clone --depth 1 https://github.com/pyworkload/3x-ui-mcpWrote 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/pyworkload/3x-ui-mcp/reality-inbound)<a href="https://agentmods.dev/skills/pyworkload/3x-ui-mcp/reality-inbound"><img src="https://agentmods.dev/badge/skills/pyworkload/3x-ui-mcp/reality-inbound/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/pyworkload/3x-ui-mcp/reality-inbound"><img src="https://agentmods.dev/badge/skills/pyworkload/3x-ui-mcp/reality-inbound.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 | $0.00094 | $0.01512 |
| Opus 5.5 | $0.00038 | $0.00605 |
| Sonnet 5.5 | $0.00019 | $0.00302 |
| Haiku 4.5 | $0.00009 | $0.00151 |
Grade A, and why
reality-inbound 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 1mo 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 — 121 lines — stays where its author put it; the contents beside it link to each section on GitHub.
REALITY inbound
REALITY hides the server by completing a real TLS 1.3 handshake with a third-party
site (dest) and stealing its certificate for anyone who is not a genuine client.
There is no domain to register and no certificate to renew — but the whole design
rests on picking a good dest, and that choice is not something the panel checks
for you.
Choosing the target
Four properties are mandatory, and scan_reality_target verifies all of them:
TLS 1.3, HTTP/2 in ALPN, X25519 key exchange, and a certificate that chains to a
trusted root. A candidate failing any one of them cannot be used at all.
The rest is judgment the scanner cannot make:
- Not fronted by a CDN with nodes in your users' country. Two separate problems: your server becomes a port-forwarder into that CDN for anyone who probes it, and a censor sees traffic leaving to a foreign IP for a domain that resolves locally — an anomaly that stands out precisely because the domain is popular.
- Not one of the giants.
google.com,microsoft.com,apple.comand friends are the most-analysed SNIs on earth and are usually CDN'd locally. Xray-core agrees loudly enough to have hard-coded it: aserverNamesentry containingappleoricloudlogs "REALITY: Choosing apple, icloud, etc. as the target may get your IP blocked by the GFW" at startup. - Reachable and not itself blocked where the users are. A blocked SNI is worse than no camouflage.
- Low RTT from the panel server, not from you. Every client handshake is
proxied to
dest, so its latency is added to connection setup.scan_reality_targetsranks candidates by feasibility first, then latency. - Plausibly close to the VPS. A site in the same datacenter or AS as the server is both fast and unremarkable.
The trick worth knowing: scan_reality_targets accepts CIDR ranges and discovers
candidates by reading the certificates hosts actually serve. Scanning the
neighbourhood of your own VPS finds local, low-latency, unpopular targets that no
published "good dest" list contains — and published lists are exactly the ones a
censor also reads.
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.
- 1mo ago First seen · 121 lines · 94 tokens per session scan A 8bc7379b0a5d
reality-inbound is a skill published in the GitHub repository pyworkload/3x-ui-mcp (5 stars, last pushed 4d ago), licensed MIT. It adds 94 tokens to every session and 1,512 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-09-05.
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