Find agent skills by outcome

requested: 1

// tokens to deduct for rate limiting

Coding & Debugging

Always include `shield()` (WAF) and `detectBot()` as base layers. Bots scraping AI endpoints are a common abuse vector. For endpoints accessed via browsers (e.g. chat interfaces)

consider adding Arcjet advanced signals for client-side bot detection that catches sophisticated headless browsers. See https://docs.arcjet.com/bot-protection/advanced-signals for setup.

const decision = await aj.protect(req

{

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 proportional to actual model token usage

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

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

deduct 1 token per message

Coding & Debugging

- Python: `detect_sensitive_info(deny=[SensitiveInfoType.EMAIL

SensitiveInfoType.CREDIT_CARD_NUMBER

Communication

- JS: `sensitiveInfo({ deny: [EMAIL

CREDIT_CARD_NUMBER

Detects jailbreaks

role-play escapes

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

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

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

PII leakage

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 jailbreak attempts

block PII and sensitive info from leaking in responses

Best practices — legend-first

one device type at a time

Add AI protection

---

Business

PDF Type detection — Vector vs Scanned

different extraction strategy for each

Visual symbol table — per ELV system (CCTV

FAS

pdfcount

---

Business

$humanization_strategy (Outline the specific techniques you will use to humanize the text

such as:

Business

$humanized_text (The rewritten text

incorporating the humanization strategy. Aim for a tone that is authentic

Education

$explanation_of_changes (Briefly explain the key changes made and why they contribute to a more humanized feel. For example: Replaced 'utilize' with 'use' for a more conversational tone

or Added a personal anecdote about [topic] to create a connection with the audience.)

$analysis_of_ai_characteristics (Identify areas that sound robotic

overly formal

Writing & Content

Tr

"You are a master wordsmith and expert in natural language processing, specializing in humanizing AI-generated text. Your goal is to transform robotic or overly formal lyrics and video scripts into en...