troubleshooting
Skill: Troubleshooting
Diagnose and fix common issues with the Personize stack. Jump to the action that matches the symptom.
When to Use This Skill
- Recall returns irrelevant, empty, or noisy results
- Memorized data isn't being extracted correctly
- Guidelines aren't reaching agents or return wrong content
- Getting 429 rate limit errors or partial batch syncs
- Trigger.dev or n8n workflows are failing
- Shared workspace is going stale or agents aren't contributing
When NOT to Use This Skill
- Everything works and you want to confirm → use verify-setup
- Need to set up a new capability → use entity-memory, governance, data-sync, etc.
- Need to understand the architecture → use personalization
Actions
You have 6 actions available. Jump to the one that matches the developer's symptom.
| Action | When to Use | Reference |
|---|---|---|
| BAD-RECALL | Recall returns irrelevant, empty, or noisy results | reference/bad-recall.md |
| BAD-EXTRACTION | Memorized data isn't being extracted correctly | reference/bad-extraction.md |
| GOVERNANCE-MISS | Guidelines aren't reaching agents or return wrong content | reference/governance-miss.md |
| RATE-LIMITS | Getting 429 errors or partial batch syncs | reference/rate-limits.md |
| PIPELINE-FAILURE | Trigger.dev/n8n workflows failing or producing bad output | reference/pipeline-failure.md |
| WORKSPACE-STALE | Agents not contributing or workspace going stale | reference/workspace-stale.md |
Quick Diagnosis
If the developer isn't sure what's wrong, run this triage:
import { Personize } from '@personize/sdk';
const client = new Personize({ secretKey: process.env.PERSONIZE_SECRET_KEY! });
// 1. Can we connect?
try {
const me = await client.me();
console.log(`✅ Auth: ${me.data.organization.name}`);
console.log(` Plan: ${me.data.plan.name}`);
console.log(` Rate limits:`, me.data.rateLimits);
} catch (e) {
console.log('❌ Auth failed:', e.message);
console.log(' → Check PERSONIZE_SECRET_KEY');
}
// 2. Can we recall?
try {
const recall = await client.memory.recall({ query: 'test', limit: 1 });
console.log(`✅ Recall: working (${recall.data.memories.length} results)`);
} catch (e) {
console.log('❌ Recall failed:', e.message);
}
// 3. Can we fetch guidelines?
try {
const guidelines = await client.ai.smartGuidelines({ message: 'test' });
console.log(`✅ Guidelines: ${guidelines.data.compiledContext ? 'returning content' : '⚠️ empty (no guidelines set up?)'}`);
} catch (e) {
console.log('❌ Guidelines failed:', e.message);
}
// 4. Can we memorize?
try {
await client.memory.memorize({
email: 'troubleshoot-test@example.com',
content: 'Troubleshooting test entry',
});
console.log('✅ Memorize: working');
} catch (e) {
console.log('❌ Memorize failed:', e.message);
if (e.message.includes('429')) console.log(' → Rate limited. See RATE-LIMITS action.');
}
Based on results, jump to the appropriate action above.
Constraints
Keywords follow RFC 2119: MUST = non-negotiable, SHOULD = strong default (override with stated reasoning), MAY = agent discretion.
- MUST run diagnostic steps before suggesting fixes — because guessing wastes time and can introduce new problems.
- MUST ask the developer what they expected vs. what they got — because the same symptom can have different root causes depending on expectations.
- SHOULD rank root causes by likelihood and check the most likely first — because systematic diagnosis is faster than shotgun debugging.
- SHOULD verify the fix worked by re-running the failing operation — because a fix that doesn't resolve the symptom isn't a fix.
- MAY suggest preventive measures after fixing — because recurring issues waste developer time.
More from personizeai/personize-skills
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Stores and retrieves persistent memory about records — contacts, companies, employees, members, and more. Handles memorization (single and batch with per-property AI extraction), semantic recall, entity digests, and data export. Use this skill whenever the user wants to store data, sync records from a CRM or database, query or search memory, recall what's known about a person or company, assemble context for personalization, import CSV or spreadsheet data, or do anything involving the Personize SDK's memory methods (memorize, recall, smartRecall, smartDigest, search, memorizeBatch). Also use when the user mentions contacts, leads, accounts, customer data, or entity properties.
21entity-memory
Stores and retrieves persistent memory about records — contacts, companies, employees, members, and more. Handles memorization (single and batch with per-property AI extraction), semantic recall, entity digests, and data export. Use this skill whenever the user wants to store data, sync records from a CRM or database, query or search memory, recall what's known about a person or company, assemble context for personalization, import CSV or spreadsheet data, or do anything involving the Personize SDK's memory methods (memorize, recall, smartRecall, smartDigest, search, memorizeBatch). Also use when the user mentions contacts, leads, accounts, customer data, or entity properties.
12no-code-pipelines
Generates importable n8n workflow JSON files that sync data between Personize and 400+ apps. Produces ready-to-import workflows for batch sync, webhook ingestion, per-record AI enrichment, and data export — no code required. Use this skill whenever the user wants no-code integrations, visual workflows, n8n automation, or to connect Personize to HubSpot, Salesforce, Google Sheets, Slack, Postgres, or any app without writing code. Also trigger when they mention 'workflow automation', 'scheduled sync without code', 'visual pipeline', or 'connect Personize to [app]' and don't want to write TypeScript.
12code-pipelines
Builds, deploys, and iterates production-ready AI agent pipelines using Trigger.dev and the Personize SDK. Handles the full lifecycle: interview the user about what they want, design the schema and governance, write the pipeline code, deploy it, monitor results, and iterate based on feedback. Generates TypeScript tasks for outbound sequences, inbound lead processing, conversational reply handlers, enrichment pipelines, and account signal monitoring — all backed by Personize memory, AI context, and governance. Use this skill whenever someone wants to build an AI agent, automated workflow, email sequence, drip campaign, cold outreach, lead enrichment, reply handler, account monitor, CRM automation, daily digest, or any durable pipeline — whether they provide technical specs or just describe what they want in plain language. Also trigger for Trigger.dev, background tasks, self-scheduling follow-ups, GTM automation, 'build me an agent that...', or 'I want to automate...'.
11collaboration
Turn any record into a shared workspace where agents and humans collaborate. Attach a simple workspace schema to any entity — contacts, companies, deals, projects, tickets — and let any participant contribute updates, tasks, notes, and issues. Use this skill whenever the user wants multi-agent collaboration, shared context on an entity, agent handoffs, workspace-based coordination, or the three-layer agent operating model (Guidelines + Memory + Workspace). Also trigger when they mention multiple agents working on the same record, deal rooms, account intelligence, customer health monitoring, cross-functional coordination, or progressive autonomy for AI agents.
11governance
Manages organizational guidelines, policies, and best practices as governance variables accessible to all AI agents via SmartContext. Use this skill whenever the user wants to create, update, or manage guidelines, brand voice, compliance policies, playbooks, ICPs, sales playbooks, tone rules, or any organizational rules. Also trigger when the user mentions smartGuidelines, governance variables, GitOps sync of policies, team knowledge sharing, AI agent rules, or when they want all their AI tools to follow the same policies. Even if they just say 'set up rules' or 'add a policy', this is the right skill.
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