Search
AI & LLM Engineering · datadog-labs/agent-skills
Skills
Sort:BestMost starsTrending todayTrending this weekTrending this monthNewestRecently updatedName
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Bootstrap a reproducible LLM Observability experiment through the Python ddtrace SDK or the Node dd-trace SDK. | datadog-labs/ | 177 | — | ~2.3k | Automated safety check: Pass | MIT | 2 days ago |
| 2 | Instrument the current project with Datadog LLM Observability for Python or Node.js/Next.js backends that call LLMs or run AI agents. | datadog-labs/ | 177 | — | ~2.9k | Automated safety check: Pass | MIT | 2 days ago |
| 3 | Bootstrap evaluators from production traces — by default propose online LLM-judge evaluators and, after you confirm, create them in Datadog as disabled drafts (never auto-enabled); on request emit… | datadog-labs/ | 177 | — | ~25k | Automated safety check: Pass | MIT | 2 days ago |
| 4 | Investigate a Datadog product usage or cost spike by correlating Usage Metering data (when/what spiked) with Audit Trail config changes (who changed what in the preceding window). | datadog-labs/ | 177 | — | ~1.3k | Automated safety check: Pass | MIT | 2 days ago |
| 5 | Recommends the right Datadog products for a codebase and/or a stated goal — grounded in a tech-stack→product map and a use-case→product map built from Datadog product capabilities and common… | datadog-labs/ | 177 | — | ~12k | Automated safety check: Pass | MIT | 2 days ago |
