Datadog
Monitor infrastructure and applications via Datadog API and CLI. Use when querying metrics, logs, or managing monitors.From its SKILL.md
npx -y skills add fworks-tech/agenthood --skill datadogAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
4 things to look at
- reads credentialsReads from 2 credential sources: `$DD_API_KEY` and 1 more.
- 2 stars2 stars. Stars are a popularity signal and not a quality one, but at this level it is likely that nobody has read this closely except its author, and you would be relying on your own review.
- runs commandsInstructs the agent to run 4 commands, including `curl -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/query?from=<unix_start>&to=<unix_end>&query=<metric>"` and 3 more.
- fetches URLsInstructs the agent to fetch 2 URLs, including https://api.datadoghq.com/api/v1/ and 1 more.
SKILL.md
1.4 KB, 341 tokens by cl100k_base, as published. Nobody here has run it
Datadog
Use the Datadog API to monitor and query.
API Base
https://api.datadoghq.com/api/v1/
https://api.datadoghq.com/api/v2/
Common Operations
Metrics
- Query metrics:
curl -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/query?from=<unix_start>&to=<unix_end>&query=<metric>"
Monitors
- List monitors:
curl -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/monitor" - Mute monitor:
curl -X POST -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" "https://api.datadoghq.com/api/v1/monitor/<id>/mute"
Logs
- Query logs:
curl -H "DD-API-KEY: $DD_API_KEY" -H "DD-APPLICATION-KEY: $DD_APP_KEY" -H "Content-Type: application/json" -d '{"query":"service:myapp"}' "https://api.datadoghq.com/api/v2/logs/events/search"
Notes
- API key from https://app.datadoghq.com/organization-settings/api-keys
- EU site uses
api.datadoghq.euinstead ofapi.datadoghq.com
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.
Gives 0 of the 12 instructions most log analysis skills give in 341 tokens
Counted across 325 of the 341 authors here whose files we hold, read 2026-09-06
- Use structured JSON loggingin 32 of 325, across 30 files
- Link every alert to a runbookin 15 of 325, across 13 files
- Alert on symptoms, not causesin 11 of 325, across 10 files
- Include correlation IDs in every log linein 10 of 325
- Propagate trace context across service boundariesin 9 of 325, across 8 files
- Include request IDs for correlationin 8 of 325, across 6 files
- Include trace_id in every structured log entryin 8 of 325, across 7 files
- Include request and user context in every log entryin 8 of 325
- Correlate logs and traces with shared trace IDin 7 of 325, across 6 files
- Record exceptions and set span status on errorsin 7 of 325
- Confirm connection is ACTIVE before running workflowsin 6 of 325, across 3 files
- Call RUBE_SEARCH_TOOLS first for current schemasin 6 of 325, across 3 files
Said here and by no other author read
- Use the Datadog API to monitor and query
- Authenticate with DD-API-KEY and DD-APPLICATION-KEY headers
- Mute monitors by ID via POST
- Query logs via the v2 logs search endpoint
- Obtain API keys from Datadog organization settings
- Use api.datadoghq.eu for EU sites
Grouped from the skills themselves: near-identical wordings counted once, and counted by distinct author, so one author publishing three of these counts once. Length counted with cl100k_base; the agent that loads this file may tokenize it differently.