Find agent skills by outcome

- list-requests — confirm decisions are being recorded

filter by conclusion to see blocks

Adapt the response format to your framework (e.g.

res.status(429).json(...) for Express).

console.warn(Arcjet error:

decision.reason.message);

return Response.json({ error: Forbidden }

{ status: 403 });

detectPromptInjectionMessage: userMessage

// injection detection

requested: 1

// tokens to deduct for rate limiting

const decision = await aj.protect(req

{

sensitiveInfoValue: userMessage

// PII scanning

Pass the requested parameter at protect() time to deduct tokens proportional to model cost. For exam...

deduct 1 token per message

Set characteristics to track per-user: [userId] if authenticated

defaults to IP-based.

Use tokenBucket() / token_bucket() for AI endpoints — the requested parameter can be set proportiona...

directly linking rate limiting to cost. It also allows short bursts while enforcing an average rate

- JS: `sensitiveInfo({ deny: [EMAIL

CREDITCARDNUMBER

Arcjet rules run before the request reaches your AI model — blocking prompt injection

PII leakage

Detects jailbreaks

role-play escapes

Check for an existing shared Arcjet client (see /arcjet:protect-route for full setup). If none exist...

set one up first with shield() as the base rule. The user will need to register for an Arcjet account at https://app.arcjet.com then use the ARCJET_KEY in their environment variables.

Read https://docs.arcjet.com/llms.txt for comprehensive SDK documentation covering all frameworks

rule types

Secure AI/LLM endpoints with layered protection: prompt injection detection

PII blocking

description: Protect AI chat and completion endpoints from abuse — detect prompt injection and jailb...

block PII and sensitive info from leaking in responses

Visual symbol table — per ELV system (CCTV

FAS

Add AI protection

Best practices — legend-first

one device type at a time

pdfcount

$analysisofai_characteristics (Identify areas that sound robotic

overly formal

mc

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