Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add jjmartres/ai-coding-agents --skill datadoggit clone --depth 1 https://github.com/jjmartres/ai-coding-agentsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/jjmartres/ai-coding-agents/datadog)<a href="https://agentmods.dev/skills/jjmartres/ai-coding-agents/datadog"><img src="https://agentmods.dev/badge/skills/jjmartres/ai-coding-agents/datadog/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/jjmartres/ai-coding-agents/datadog"><img src="https://agentmods.dev/badge/skills/jjmartres/ai-coding-agents/datadog.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00051 | $0.01918 |
| Opus 5.5 | $0.00020 | $0.00767 |
| Sonnet 5.5 | $0.00010 | $0.00384 |
| Haiku 4.5 | $0.00005 | $0.00192 |
Grade A, and why
datadog scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 278 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Datadog
This skill will help you to interact with Datadog, through the unofficial datadog-cli to search Datadog logs, query metrics, tail logs in real-time, trace distributed requests, investigate errors, compare time periods, find log patterns, check service health, or export observability data.
When to Use This Skill
- Trigger phrases include:
- "search logs"
- "tail logs"
- "query metrics"
- "check Datadog"
- "find errors"
- "trace request"
- "compare errors"
- "what services exist"
- "log patterns"
- "CPU usage"
- "service health"
- "get service activity"
How to Use
Log Search
datadog logs search --query "<query>" [--from <time>] [--to <time>] [--limit <n>] [--sort <order>]
Examples:
datadog logs search --query "status:error" --from 1h
datadog logs search --query "service:api status:error @http.status_code:500" --from 1h
Live Tail (Real-time Streaming)
Stream logs as they arrive. Press Ctrl+C to stop.
datadog logs tail --query "<query>" [--interval <seconds>]
Examples:
datadog logs tail --query "status:error"
datadog logs tail --query "service:api" --interval 5
Trace Correlation
Find all logs for a distributed trace across services.
datadog logs trace --id "<trace-id>" [--from <time>] [--to <time>]
Example:
datadog logs trace --id "abc123def456" --from 24h
Log Context
Get logs before and after a specific timestamp to understand what happened.
datadog logs context --timestamp "<iso-timestamp>" [--before <time>] [--after <time>] [--service <svc>]
Examples:
datadog logs context --timestamp "2024-01-15T10:30:00Z" --before 5m --after 2m
datadog logs context --timestamp "2024-01-15T10:30:00Z" --service api --before 10m
Error Summary
Quick breakdown of errors by service, type, and message.
datadog errors [--from <time>] [--to <time>] [--service <svc>]
Examples:
datadog errors --from 1h
datadog errors --service payment-api --from 24h
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 278 lines · 51 tokens per session scan A 8cc813541e5d
datadog is a skill published in the GitHub repository jjmartres/ai-coding-agents (48 stars, last pushed 4d ago), licensed MIT. It adds 51 tokens to every session and 1,918 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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