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perplexity-policy-guardrails Implement Perplexity lint rules, policy enforcement, and automated guardrails.
Use when setting up code quality rules for Perplexity integrations, implementing
pre-commit hooks, or configuring CI policy checks for Perplexity best practices.
Trigger with phrases like "perplexity policy", "perplexity lint",
"perplexity guardrails", "perplexity best practices check", "perplexity eslint".
npx skills add jeremylongshore/claude-code-plugins-plus-skills --skill perplexity-policy-guardrails ai automation claude-code devops mcp ai-agents
Perplexity Policy Guardrails
Overview
Policy enforcement for Perplexity Sonar API. Since Perplexity performs live web searches, guardrails must address: query content moderation (what users can search for), citation reliability (filtering low-quality sources), cost control (model selection + token limits), and responsible AI usage.
Policy Pipeline
User Query
│
▼
Query Moderation (block harmful queries)
│
▼
PII Sanitization (strip personal data)
│
▼
Quota Check (daily limit by user tier)
│
▼
Model Selection (enforce tier-appropriate model)
│
▼
Perplexity API Call
│
▼
Citation Quality Scoring (filter low-trust sources)
│
▼
Response to User
Prerequisites
Perplexity API configured
Content moderation policy defined
User tier system in place
Redis for quota tracking (optional: in-memory for simple apps)
Instructions
Step 1: Query Content Moderation
const BLOCKED_PATTERNS = [
/\b(write|generate|create)\s+(malware|virus|exploit|ransomware)\b/i,
/\b(personal|private)\s+(address|phone|ssn)\s+of\s+\w+/i,
/\b(bypass|circumvent|hack)\s+(security|firewall|authentication)\b/i,
/\b(how to|tutorial)\s+(stalk|dox|harass)\b/i,
];
const MAX_QUERY_LENGTH = 2000;
class PolicyError extends Error {
constructor(public code: string, message: string) {
super(message);
this.name = "PolicyError";
}
}
function moderateQuery(query: string): string {
if (query.length > MAX_QUERY_LENGTH) {
throw new PolicyError("QUERY_TOO_LONG", `Query exceeds ${MAX_QUERY_LENGTH} characters`);
}
for (const pattern of BLOCKED_PATTERNS) {
if (pattern.test(query)) {
throw new PolicyError("CONTENT_BLOCKED", "Query blocked by content policy");
}
}
return query;
}
Step 2: Model Selection Policy interface ModelPolicy {
model: string;
maxTokens: number;
costPerRequest: number;
}
const MODEL_POLICIES: Record<string, ModelPolicy> = {
free: { model: "sonar", maxTokens: 256, costPerRequest: 0.005 },
basic: { model: "sonar", maxTokens: 1024, costPerRequest: 0.005 },
pro: { model: "sonar-pro", maxTokens: 2048, costPerRequest: 0.02 },
enterprise: { model: "sonar-pro", maxTokens: 4096, costPerRequest: 0.02 },
};
function enforceModelPolicy(
userTier: string,
requestedModel?: string
): ModelPolicy {
const policy = MODEL_POLICIES[userTier] || MODEL_POLICIES.free;
// Prevent free users from using expensive models
if (requestedModel === "sonar-pro" && !["pro", "enterprise"].includes(userTier)) {
console.warn(`User tier ${userTier} not allowed sonar-pro, using sonar`);
return MODEL_POLICIES.free;
}
return requestedModel ? { ...policy, model: requestedModel } : policy;
}
Step 3: Per-User Usage Quotas class UsageQuota {
private usage: Map<string, { count: number; resetAt: number }> = new Map();
private readonly limits: Record<string, number> = {
free: 50,
basic: 200,
pro: 1000,
enterprise: 5000,
};
check(userId: string, tier: string = "free"): void {
const key = `${userId}:${new Date().toISOString().slice(0, 10)}`;
const entry = this.usage.get(key) || { count: 0, resetAt: this.endOfDay() };
// Reset if past end of day
if (Date.now() > entry.resetAt) {
entry.count = 0;
entry.resetAt = this.endOfDay();
}
const limit = this.limits[tier] || this.limits.free;
if (entry.count >= limit) {
throw new PolicyError(
"QUOTA_EXCEEDED",
`Daily quota exceeded (${entry.count}/${limit}). Resets at midnight UTC.`
);
}
entry.count++;
this.usage.set(key, entry);
}
getUsage(userId: string): { used: number; limit: number; remaining: number } {
const key = `${userId}:${new Date().toISOString().slice(0, 10)}`;
const entry = this.usage.get(key);
const used = entry?.count || 0;
return { used, limit: 50, remaining: Math.max(0, 50 - used) };
}
private endOfDay(): number {
const d = new Date();
d.setUTCHours(23, 59, 59, 999);
return d.getTime();
}
}
Step 4: Citation Quality Scoring const TRUSTED_TLDS = new Set(["gov", "edu", "org"]);
const HIGH_QUALITY_DOMAINS = new Set([
"nature.com", "science.org", "arxiv.org", "wikipedia.org",
"nih.gov", "cdc.gov", "who.int",
]);
const LOW_QUALITY_DOMAINS = new Set([
"reddit.com", "quora.com", "medium.com", "yahoo.com",
]);
interface CitationQuality {
url: string;
trust: "high" | "medium" | "low";
domain: string;
}
function scoreCitations(citations: string[]): {
scored: CitationQuality[];
highTrustPercent: number;
} {
const scored = citations.map((url) => {
const domain = new URL(url).hostname;
const tld = domain.split(".").pop() || "";
let trust: "high" | "medium" | "low" = "medium";
if (TRUSTED_TLDS.has(tld) || HIGH_QUALITY_DOMAINS.has(domain)) {
trust = "high";
} else if (LOW_QUALITY_DOMAINS.has(domain)) {
trust = "low";
}
return { url, trust, domain };
});
const highTrust = scored.filter((s) => s.trust === "high").length;
return {
scored,
highTrustPercent: citations.length > 0 ? highTrust / citations.length : 0,
};
}
Step 5: Full Policy Pipeline const quota = new UsageQuota();
async function policiedSearch(
query: string,
userId: string,
userTier: string = "free",
requestedModel?: string
) {
// 1. Content moderation
const moderated = moderateQuery(query);
// 2. PII sanitization
const { clean } = sanitizeQuery(moderated);
// 3. Quota check
quota.check(userId, userTier);
// 4. Model policy
const policy = enforceModelPolicy(userTier, requestedModel);
// 5. API call
const response = await perplexity.chat.completions.create({
model: policy.model,
messages: [{ role: "user", content: clean }],
max_tokens: policy.maxTokens,
});
// 6. Citation quality
const citations = (response as any).citations || [];
const quality = scoreCitations(citations);
return {
answer: response.choices[0].message.content,
citations: quality.scored,
citationQuality: quality.highTrustPercent,
model: response.model,
tokens: response.usage?.total_tokens,
};
}
Error Handling Issue Cause Solution Query blocked Content moderation triggered Review patterns, adjust if false positive Quota exceeded User hit daily limit Upgrade tier or wait for reset Model downgraded User tier restricts access Inform user of tier limitations Low citation quality All sources from forums Add search_domain_filter for trusted sources
Output
Query content moderation with blocked patterns
Model selection enforced by user tier
Per-user daily quotas
Citation quality scoring and filtering
Full policy pipeline combining all layers
Resources
Next Steps For architecture patterns, see perplexity-architecture-variants.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Create or update AgentSkills. Use when designing, structuring, or packaging skills with scripts, references, and assets.
Set up and use 1Password CLI (op). Use when installing the CLI, enabling desktop app integration, signing in (single or multi-account), or reading/injecting/running secrets via op.
CLI to manage emails via IMAP/SMTP. Use `himalaya` to list, read, write, reply, forward, search, and organize emails from the terminal. Supports multiple accounts and message composition with MML (MIME Meta Language).
