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Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability.
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Based on SOC occupation classification
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Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc.) into focused tools people will pay for. Not just 'ChatGPT but different' - products that solve specific problems with AI. Covers prompt engineering for products, cost management, rate limiting, and building defensible AI businesses. Use when: AI wrapper, GPT product, AI tool, wrap AI, AI SaaS.
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Free lite skill — drafts one friendly (level-1) client document-request email for a single tax client from a short brief plus the practice profile. A strict subset of client-doc-chaser (no batch, no escalation levels 2/3), carrying the pack's full guard. Use to try the kit before buying, or as the directory-published funnel skill. Triggers - "client document request email", "chase a client's documents", "free document request writer", "doc-chaser-lite".
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| name | datadog-cli |
| description | Datadog CLI for searching logs, querying metrics, tracing requests, and managing dashboards. Use this when debugging production issues or working with Datadog observability. |
A CLI tool for AI agents to debug and triage using Datadog logs and metrics.
You MUST read the relevant reference docs before using any command:
export DD_API_KEY="your-api-key"
export DD_APP_KEY="your-app-key"
Get keys from: https://app.datadoghq.com/organization-settings/api-keys
npx @leoflores/datadog-cli <command>
For non-US Datadog sites, use --site flag:
npx @leoflores/datadog-cli logs search --query "*" --site datadoghq.eu
| Command | Description |
|---|---|
logs search | Search logs with filters |
logs tail | Stream logs in real-time |
logs trace | Find logs for a distributed trace |
logs context | Get logs before/after a timestamp |
logs patterns | Group similar log messages |
logs compare | Compare log counts between periods |
logs multi | Run multiple queries in parallel |
logs agg | Aggregate logs by facet |
metrics query | Query timeseries metrics |
errors | Quick error summary by service/type |
services | List services with log activity |
dashboards | Manage dashboards (CRUD) |
dashboard-lists | Manage dashboard lists |
npx @leoflores/datadog-cli logs search --query "status:error" --from 1h --pretty
npx @leoflores/datadog-cli logs tail --query "service:api status:error" --pretty
npx @leoflores/datadog-cli errors --from 1h --pretty
npx @leoflores/datadog-cli logs trace --id "abc123def456" --pretty
npx @leoflores/datadog-cli metrics query --query "avg:system.cpu.user{*}" --from 1h --pretty
npx @leoflores/datadog-cli logs compare --query "status:error" --period 1h --pretty
| Flag | Description |
|---|---|
--pretty | Human-readable output with colors |
--output <file> | Export results to JSON file |
--site <site> | Datadog site (e.g., datadoghq.eu) |
30m, 1h, 6h, 24h, 7d2024-01-15T10:30:00Z# 1. Quick error overview
npx @leoflores/datadog-cli errors --from 1h --pretty
# 2. Is this new? Compare to previous period
npx @leoflores/datadog-cli logs compare --query "status:error" --period 1h --pretty
# 3. Find error patterns
npx @leoflores/datadog-cli logs patterns --query "status:error" --from 1h --pretty
# 4. Narrow down by service
npx @leoflores/datadog-cli logs search --query "status:error service:api" --from 1h --pretty
# 5. Get context around a timestamp
npx @leoflores/datadog-cli logs context --timestamp "2024-01-15T10:30:00Z" --service api --pretty
# 6. Follow the distributed trace
npx @leoflores/datadog-cli logs trace --id "TRACE_ID" --pretty
See workflows.md for more debugging workflows.