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Telemetry
Prompts for Claude Code, Codex, Cursor, and custom agents

Agent telemetry prompt pack

Choose what you want to measure, then paste its prompt into your coding agent. The agent adds structured events you can query for product growth, retention, AI costs, revenue, APIs, or jobs.

Choose what to measure

Copy the right prompt

Start from the product, AI cost, revenue, API, or background-job prompt instead of writing analytics requirements from scratch.

Ask the agent to add event tracking

Each prompt asks the agent to find important code paths, add structured events, avoid sensitive payloads, and verify ingestion.

Query the events your agent adds

The prompts specify fields you can query to measure activation, retention, reliability, cost, and revenue.

full-project

Instrument the core product

Ask an agent to find your main product workflows, add structured events, and create a first dashboard.

full-project

Instrument the core product

text
Instrument this project with structured logs using /skill.md.

Use this Telemetry API key: YOUR_API_KEY

Anonymous keys support logging and synchronous SQL without signup. Claim the existing workspace at https://telemetry.sh/register with the same key before creating dashboards or alerts. If it is unclaimed, query the event to verify delivery and report which features need signup.

Please:
1. Find the most important user-facing flows, background jobs, and AI/tooling workflows.
2. Add structured logging with snake_case table and field names.
3. Capture the key signals for each workflow, including status, latency, identifiers, and error context when relevant.
4. Run one real user-facing or operational flow through the instrumented application and verify its event appears in Telemetry. Do not use telemetry_quickstart for this milestone.
5. Run a read-only query over that real event, then create a high-level dashboard with charts and tables that summarize the most important signals in this project.
6. Tell me what you instrumented, which real flow you verified, which tables you created, and which dashboard views I should review first.

Keep event payloads small and focused. Make dashboard labels and charts easy to scan.

ai-costs

Track OpenAI and LLM costs

Track model usage, token costs, latency, tool calls, and failed AI requests.

ai-costs

Track OpenAI and LLM costs

text
Instrument this project with Telemetry so we can understand OpenAI and LLM usage.

Use /skill.md and this Telemetry API key: YOUR_API_KEY

Please log:
1. Every model request with model, provider, route, feature, input_tokens, output_tokens, total_tokens, estimated_cost_usd, latency_ms, status, and error_type when relevant.
2. Tool calls made by the agent or assistant, including tool_name, status, latency_ms, and result_category.
3. User-facing AI workflow outcomes, including feature, status, retry_count, and whether the user accepted, copied, saved, or discarded the result.
4. A dashboard with daily cost, cost by feature, failures by model, p95 latency, and accepted output rate.

Keep prompts and raw completions out of telemetry unless I explicitly approve storing them.

checkout

Track signup to paid conversion

Find where visitors drop off during signup, onboarding, and checkout. Track what paying teams do next.

checkout

Track signup to paid conversion

text
Instrument the acquisition and revenue funnel with Telemetry.

Use /skill.md and this Telemetry API key: YOUR_API_KEY

Please add structured events for:
1. Marketing page views, CTA clicks, pricing plan selection, docs CTA clicks, and prompt copies.
2. Registration attempts, successful registrations, onboarding steps, team creation, first API key creation, and first telemetry event received.
3. Checkout start, checkout success, plan changes, billing portal opens, and payment failures.
4. Activation milestones: first table created, first query run, first dashboard created, first alert created, and second active day.

Create a dashboard for visitor to signup, signup to activated team, activated team to paid, and weekly retention by activation milestone.

api-reliability

Track API reliability

Measure API request volume, latency, and errors, then identify affected customers.

api-reliability

Track API reliability

text
Add Telemetry instrumentation for API reliability.

Use /skill.md and this Telemetry API key: YOUR_API_KEY

Please log each important API endpoint with route_template, method, status_code, status, latency_ms, user_id or team_id when available, request_size_bytes, response_size_bytes, and error_type.

Create:
1. A table for API request events.
2. Charts for request volume, error rate, p50 and p95 latency, and top failing endpoints.
3. Alerts for elevated 5xx rate, slow p95 latency, and sudden traffic drops.

Do not log request bodies, auth headers, cookies, secrets, or raw user content.

background-jobs

Track background jobs

See which queues, cron tasks, imports, billing syncs, or webhooks are slow or failing.

background-jobs

Track background jobs

text
Instrument background jobs and async workers with Telemetry.

Use /skill.md and this Telemetry API key: YOUR_API_KEY

Please log job_started, job_completed, and job_failed events with job_name, queue_name, attempt, status, duration_ms, scheduled_at, started_at, completed_at, item_count, retry_count, and error_type.

Create a dashboard showing throughput by job, failures by job, p95 duration, retry volume, oldest pending job, and dead-letter events. Add alerts for stalled jobs and repeated failures.

retention

Track product usage and retention

Measure activation, return visits, and feature adoption. See which early actions correlate with retained accounts.

retention

Track product usage and retention

text
Instrument product usage and retention with Telemetry.

Use /skill.md and this Telemetry API key: YOUR_API_KEY

Please add structured events for:
1. Signup, onboarding step completion, team creation, first successful integration, and first meaningful product action.
2. Core feature usage with feature_name, action, surface, team_id, user_id, status, latency_ms, and error_type when relevant.
3. Retention milestones: second active day, first saved dashboard, first shared artifact, first alert created, and first return after seven days.
4. Expansion signals: invited teammate, upgraded plan intent, billing page viewed, usage limit reached, and support requested.

Create a dashboard for activation rate, weekly active teams, feature adoption, retained teams by first action, and upgrade-intent events.

Templates

Copy a workflow-specific brief

Integrations

Add events to your existing stack

OpenAI agent telemetry

Log OpenAI agent runs, tool calls, model usage, latency, cost, and final outcomes with structured events.

Open guide

Browser JavaScript and Web Vitals telemetry

Send Core Web Vitals and approved frontend result fields through a rate-limited server proxy. Keep the Telemetry API key on the server.

Open guide

Vercel AI SDK telemetry

Track streaming completions, token usage, retries, latency, and accepted results from AI SDK workflows.

Open guide

Inngest and Trigger.dev job telemetry

Instrument async workers, scheduled jobs, retries, failures, and dead-letter events with SQL-ready logs.

Open guide

Stripe webhook telemetry

Debug payment, subscription, invoice, retry, and downstream billing sync behavior without storing webhook bodies.

Open guide

Supabase and Postgres app telemetry

Track product workflows, database-adjacent jobs, API routes, and customer-facing failures from server code.

Open guide

Cloudflare Worker telemetry

Log edge request status, latency, provider failures, cron runs, and queue workers from Cloudflare Workers.

Open guide

Node.js and Express structured logging

Instrument Express route outcomes with stable route templates, status codes, request latency, and safe correlation fields.

Open guide

Next.js server event analytics

Send SQL-ready events from Next.js route handlers and server actions without exposing an ingestion key to the browser.

Open guide

Python and FastAPI structured logging

Capture FastAPI request outcomes and latency with the asynchronous Telemetry client and normalized route names.

Open guide

OpenTelemetry context in structured events

Connect Telemetry business events to existing OpenTelemetry traces by recording safe trace and span identifiers at workflow boundaries.

Open guide

AWS Lambda structured event monitoring

Track Lambda invocations, cold starts, duration, retries, and business outcomes with compact structured events.

Open guide

Go HTTP server structured logging

Add typed request-outcome events to Go HTTP services for route error rates, latency percentiles, and release comparisons.

Open guide

Ruby on Rails structured event analytics

Record Rails controller and background-workflow outcomes through Telemetry's HTTP API with safe, queryable fields.

Open guide

Django and Celery structured event monitoring

Connect Django request outcomes and Celery task lifecycles with safe identifiers, latency, retries, and final status.

Open guide

Laravel structured logging and queue analytics

Send Laravel request, command, queue, and billing outcomes as typed events without exposing application secrets or payloads.

Open guide

.NET and Serilog structured event analytics

Add a focused Telemetry outcome event beside Serilog diagnostics for ASP.NET request latency, failures, releases, and customer impact.

Open guide

Spring Boot structured event monitoring

Record Spring MVC and scheduled-workflow outcomes through Telemetry's HTTP API with stable routes, latency, status, and trace context.

Open guide

Temporal workflow observability

Track Temporal workflow outcomes, activity retries, schedule-to-start latency, and business milestones without recording workflow payloads.

Open guide

BullMQ queue monitoring

Measure BullMQ queue wait, execution duration, retries, failures, and dead-letter growth with SQL-ready lifecycle events.

Open guide

AWS SQS queue observability

Track SQS message age, receive attempts, processing outcomes, batch behavior, and dead-letter routing without storing message bodies.

Open guide

Kafka consumer lag and processing analytics

Monitor Kafka consumer outcomes, partition lag, processing latency, retries, and poison-message handling with structured events.

Open guide

Anthropic Claude API telemetry

Track Claude API token usage, model, latency, stop reason, errors, cost context, and reviewed product outcomes without storing prompts.

Open guide

LangGraph agent observability

Measure LangGraph run outcomes, node and tool failures, retries, checkpoints, human handoffs, latency, and reviewed task quality.

Open guide

node-postgres pool and query telemetry

Instrument node-postgres query fingerprints, connection acquisition, pool pressure, timeouts, transaction outcomes, and database errors without logging SQL parameters.

Open guide

Prisma ORM database telemetry

Measure Prisma operation fingerprints, model and method latency, failures, result counts, releases, and database-dependent workflows without collecting raw query parameters.

Open guide

Kubernetes workload telemetry

Send approved Kubernetes restart, readiness, and rollout fields to Telemetry. Use SQL to compare workloads.

Open guide

Google Gemini API telemetry

Track Gemini request latency, model usage, tokens, finish reason, errors, and reviewed product outcomes without storing prompts or generated content.

Open guide

Amazon Bedrock model telemetry

Measure Bedrock Converse requests by model or inference profile, token usage, latency, stop reason, retries, and business outcome.

Open guide

Azure OpenAI Responses telemetry

Track Azure OpenAI deployment usage, token cost, latency, failures, and product outcomes with editable SQL-ready events.

Open guide

LangChain agent outcome telemetry

Connect LangChain agent runs and tool outcomes to product-facing cost, reliability, handoff, and acceptance metrics without duplicating raw traces.

Open guide

Pino structured event analytics

Keep Pino diagnostic logs and send selected completion events to Telemetry to analyze Node.js requests, jobs, and product reliability.

Open guide

Winston structured event analytics

Connect Winston application diagnostics to small SQL-ready request, workflow, and job outcomes without duplicating the entire log stream.

Open guide

NestJS request and workflow telemetry

Instrument NestJS controllers and providers with normalized route outcomes, latency, errors, releases, and approved account context.

Open guide

Flask and SQLAlchemy telemetry

Record Flask request results and SQLAlchemy transaction behavior with approved Python event fields, consistent route templates, and safe error categories.

Open guide

Sidekiq job telemetry

Track Sidekiq execution outcomes, attempts, queue wait, errors, and releases from server middleware without copying job arguments.

Open guide

Redis and node-redis telemetry

Measure Redis command outcomes, latency, cache behavior, reconnects, and bounded error categories alongside node-redis.

Open guide

Claude Agent SDK telemetry

Track Claude Agent SDK run outcomes, duration, tool activity, turns, cost, and approved product signals without storing prompts or tool payloads.

Open guide

Pydantic AI agent telemetry

Measure Pydantic AI run outcomes, validated outputs, retries, tool activity, latency, usage, and product acceptance with safe structured events.

Open guide

CrewAI workflow telemetry

Track CrewAI crew and flow outcomes, task counts, handoffs, retries, latency, cost, and accepted results without retaining agent conversations.

Open guide

Google ADK agent telemetry

Measure Google Agent Development Kit sessions, run outcomes, tool activity, handoffs, latency, and approved product signals with SQL-ready events.

Open guide

Mastra agent telemetry

Track Mastra agent and workflow outcomes, tool activity, latency, retries, cost, and product acceptance alongside built-in traces and evals.

Open guide

LlamaIndex agent telemetry

Track LlamaIndex agent and workflow outcomes, tool activity, latency, retrieval versions, cost, and reviewed quality with structured events.

Open guide

DSPy program evaluation telemetry

Measure DSPy program latency, failures, metric scores, optimizer versions, model cost, and accepted outcomes across releases with SQL-ready events.

Open guide

AutoGen task flow, state, and timeout monitoring

Track AutoGen task-flow state, timeouts, team and agent outcomes, tool activity, handoffs, latency, failures, cost, and releases with compact structured events.

Open guide

Semantic Kernel agent telemetry

Measure Semantic Kernel function and agent outcomes, tool activity, model usage, latency, cost, and releases alongside OpenTelemetry traces.

Open guide

MCP server and tool telemetry

Track Model Context Protocol tool outcomes, latency, errors, approvals, retries, clients, and releases without storing arguments or returned content.

Open guide

RabbitMQ queue telemetry

Track RabbitMQ publish confirmation, delivery, acknowledgement, redelivery, queue wait, retries, and dead-letter outcomes with structured events.

Open guide

MySQL query and pool telemetry

Track normalized MySQL operations, pool wait, transaction outcomes, controlled error categories, and release regressions without storing raw SQL or parameters.

Open guide

MongoDB operation telemetry

Track named MongoDB operations, latency, result counts, retries, transaction outcomes, and release regressions without collecting documents or query values.

Open guide

Google Cloud Run telemetry

Track Cloud Run request and job outcomes, cold-start context, instance concurrency, retries, latency, and releases with application-owned structured events.

Open guide

Google Cloud Pub/Sub telemetry

Track Pub/Sub publish, delivery, acknowledgement, redelivery, ordering, queue age, and dead-letter outcomes with stable message identifiers.

Open guide

Azure Functions telemetry

Track Azure Functions HTTP, timer, queue, and event-trigger outcomes with invocation, retry, latency, release, and customer-impact context.

Open guide

Azure Service Bus telemetry

Track Azure Service Bus sends, receives, lock renewal, settlement, redelivery, deferral, and dead-letter outcomes without collecting message bodies.

Open guide

OpenAI Responses API telemetry

Measure OpenAI Responses API latency, token usage, tool activity, failures, and downstream outcomes without collecting prompts or generated content.

Open guide

LiteLLM gateway and SDK telemetry

Track LiteLLM provider routing, retries, fallbacks, token usage, latency, cost estimates, and accepted outcomes across a controlled model gateway.

Open guide

Elixir Phoenix telemetry integration

Listen for Phoenix request lifecycle events and forward the final request result with approved fields. Exclude connection data, parameters, and exception text.

Open guide

AWS ECS and Fargate telemetry integration

Add ECS task family, revision, availability zone, and release context to application outcomes using the local task metadata endpoint.

Open guide

GitHub Actions workflow telemetry integration

When a GitHub Actions workflow finishes, send its run, attempt, job, conclusion, duration, and release fields.

Open guide

n8n workflow telemetry

Use the n8n HTTP Request node to send approved fields for workflow completion, failure, retries, item counts, and downstream delivery results to Telemetry.

Open guide

Use cases

Choose a setup guide for your application

View pricing

Claude Code observability

Ask Claude Code to add event logging while it implements a feature, then verify the events in Telemetry.

Open setup page

Cursor Telemetry setup

Paste this prompt into Cursor to add event tables, track signup steps, and build dashboards.

Open setup page

Codex instrumentation prompt

Ask Codex to add product events, verify that they arrive, and report which workflows still need logging.

Open setup page

OpenAI cost monitoring

Track OpenAI and LLM costs by model, feature, and customer. Use SQL dashboards to compare spending with latency, failures, and accepted outputs.

Open setup page

Product analytics for retention

Ask an agent to add structured events, then compare the early actions of teams that return, leave, or upgrade.

Open setup page

AI agent telemetry and observability

Record agent runs and tool calls in Telemetry tables. Query retries, latency, cost, failures, and whether users accepted the results.

Open setup page

Background job monitoring

Use structured events to see job throughput, retries, failures, dead letters, queue health, and p95 duration.

Open setup page

Webhook debugging

Track webhook delivery, processing, retries, deduplication, downstream jobs, and failures without storing raw payloads.

Open setup page

API reliability monitoring

Track API request volume, status codes, latency, timeouts, customer impact, and failed endpoints with SQL.

Open setup page

Crypto and onchain automation monitoring

Track indexed events, agent actions, transaction costs, wallet workflows, tool calls, and failed automation jobs.

Open setup page

Infrastructure metrics with SQL

Send structured infrastructure events when you need queryable host and container history without a large monitoring rollout.

Open setup page

Usage-based billing analytics

Record billable usage with events that won't count retries twice. Track quotas and overages, then reconcile totals with your billing provider.

Open setup page

Security and audit-log analytics

Record authentication failures, access changes, and privileged actions. Use these events to reconstruct an incident timeline, and exclude credentials and private payloads.

Open setup page

AI agent security monitoring

Monitor tool authorization, policy denials, approval queues, risky action classes, and release changes without storing prompts, credentials, or tool payloads.

Open setup page

AI agent quality and evaluation

Compare agent task success across releases using reviewer decisions, human handoffs, and run costs.

Open setup page

Database reliability monitoring with SQL

Track safe query fingerprints, pool pressure, transaction rollbacks, lock contention, replication lag, and migration outcomes without collecting raw SQL parameters.

Open setup page

Frontend performance monitoring with SQL

Track typed LCP, INP, and CLS samples by stable route and release, then use SQL to find frontend regressions without collecting raw URLs or page content.

Open setup page

Kubernetes reliability monitoring with SQL

Query Kubernetes workload changes alongside application events. See whether restarts are part of a planned rollout and whether users are seeing failures.

Open setup page

SaaS revenue analytics with SQL

Track subscription revenue changes alongside invoices, entitlements, and product events. Reconcile the totals with your billing provider before reporting MRR.

Open setup page

Telemetry data quality monitoring with SQL

Check event freshness, required fields, types, duplicates, schema versions, and volume. Catch logging errors before your team acts on a misleading dashboard or alert.

Open setup page

Comparisons

PostHog for backend events

PostHog combines product analytics, funnels, retention, SQL, and a data warehouse. Telemetry focuses on backend event tables and SQL dashboards. A coding agent can add the instrumentation from your codebase.

Read comparison

Datadog alternative for startups

Datadog covers observability and security across your infrastructure. Telemetry hosts structured application events, SQL dashboards, and threshold alerts for teams that need to query their own workflows.

Read comparison

ClickHouse logging API without running ClickHouse

ClickHouse is a columnar analytics database, and ClickStack adds observability tools. Telemetry hosts event ingestion, SQL queries, dashboards, and alerts so you do not have to assemble or operate that stack.

Read comparison

Axiom alternative for structured event analytics

Axiom offers event ingestion, search, APL queries, dashboards, and monitors. Telemetry uses typed application event tables and SQL. Its coding-agent prompts help you add instrumentation and build queries from your codebase.

Read comparison

Better Stack Logs alternative for SQL event analytics

Better Stack combines logs, dashboards, alerting, incident management, and uptime monitoring. Telemetry focuses on application event tables and SQL queries, with prompts that help a coding agent add instrumentation to your codebase.

Read comparison

Honeycomb alternative for lightweight wide events

Honeycomb supports high-cardinality debugging with wide events and distributed traces. Telemetry stores application and business events in SQL tables, with dashboards and threshold alerts.

Read comparison

Grafana Loki alternative for structured log SQL

Grafana Cloud and Loki combine logs, metrics, traces, dashboards, and alerts. Telemetry hosts JSON event tables and SQL for teams that need to analyze application workflows.

Read comparison

Sentry alternative for structured events and SQL

Sentry combines error monitoring, tracing, profiling, session replay, and logs around application health. Telemetry is the narrower alternative when a team's first requirement is custom structured workflow events and SQL analysis rather than exception-centric debugging.

Read comparison

Splunk alternative for structured events

Splunk offers search, security analytics, logs, infrastructure monitoring, APM, real-user monitoring, and OpenTelemetry collection. Telemetry focuses on application events that you choose to send and query with SQL.

Read comparison

Elastic alternative for structured event SQL

Elastic Observability combines Elasticsearch, Kibana, logs, metrics, APM, profiling, and OpenTelemetry collection. Telemetry is the focused alternative when the main job is managed application-event ingestion and SQL analysis without operating or modeling a broader Elastic deployment.

Read comparison

New Relic alternative for structured events

New Relic is a broad observability platform spanning APM, infrastructure, logs, browser, mobile, synthetics, errors, and NRQL. Telemetry is the narrower choice when a team wants custom structured outcomes, SQL, and a lightweight event-analysis workflow.

Read comparison

Telemetry vs Langfuse for AI observability

Langfuse provides LLM traces, prompt management, evaluations, datasets, and experiments. Telemetry stores events for agent runs and product activity so you can query their cost, reliability, and results with SQL.

Read comparison

Telemetry vs LangSmith for AI observability

LangSmith provides tracing, evaluations, datasets, experiments, and deployment options for LLM applications. Telemetry stores the final results of AI and application tasks in event tables you can query with SQL.

Read comparison

Telemetry vs Arize Phoenix

Arize Phoenix is an open-source AI observability and evaluation platform built around traces, prompts, datasets, and experiments. Telemetry focuses on compact structured outcomes and SQL.

Read comparison

Telemetry vs Pydantic Logfire

Pydantic Logfire combines OpenTelemetry-based application monitoring with AI tracing and conversation views. Telemetry stores selected application outcomes in tables you can query with SQL.

Read comparison

Telemetry vs Mixpanel

Mixpanel is a product and digital analytics platform built around behavioral reports such as insights, funnels, flows, retention, and cohorts. Telemetry is the narrower choice for SQL over application-owned product and operational events.

Read comparison

Telemetry vs Amplitude

Amplitude is a digital analytics platform with product-analysis workflows for events, funnels, retention, journeys, cohorts, and experimentation. Telemetry focuses on compact structured events and explicit SQL.

Read comparison

Telemetry vs Braintrust

Braintrust is an AI evaluation and observability platform built around experiments, datasets, scorers, prompts, and production traces. Telemetry focuses on SQL over selected AI and product outcomes.

Read comparison

Telemetry vs Helicone

Helicone combines an AI gateway with LLM request observability, sessions, cost analytics, caching, and alerts. Telemetry is a provider-neutral SQL layer for selected AI and application outcomes.

Read comparison

Telemetry vs Opik

Opik is an open-source LLM evaluation and observability platform with traces, datasets, metrics, experiments, and test suites. Telemetry uses SQL to analyze selected AI and application results.

Read comparison

Telemetry vs W&B Weave

W&B Weave is an AI observability and evaluation platform with traces, datasets, scorers, versioning, feedback, and production monitoring. Telemetry focuses on SQL over selected AI and product outcomes.

Read comparison

Telemetry vs MLflow for GenAI

MLflow provides OpenTelemetry-compatible GenAI tracing, evaluations, prompt versioning, experiments, and production monitoring. Telemetry stores selected task results in event tables that you can join with other application data using SQL.

Read comparison

Telemetry vs OpenLIT

OpenLIT is an open-source, OpenTelemetry-native AI engineering platform with auto-instrumentation, traces, evaluations, prompts, experiments, dashboards, and collectors. Telemetry focuses on SQL outcome events.

Read comparison