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 Arvo-AI/aurora --skill datadoggit clone --depth 1 https://github.com/Arvo-AI/auroraWrote 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/arvo-ai/aurora/datadog)<a href="https://agentmods.dev/skills/arvo-ai/aurora/datadog"><img src="https://agentmods.dev/badge/skills/arvo-ai/aurora/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/arvo-ai/aurora/datadog"><img src="https://agentmods.dev/badge/skills/arvo-ai/aurora/datadog.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00028 | $0.02543 |
| Opus 5.5 | $0.00011 | $0.01017 |
| Sonnet 5.5 | $0.00006 | $0.00509 |
| Haiku 4.5 | $0.00003 | $0.00254 |
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 29d 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 — 189 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Datadog Integration
Overview
Datadog integration for querying observability data during Root Cause Analysis. Datadog is a REMOTE service. Use ONLY the query_datadog API tool. All data is accessed via a single unified tool with resource_type parameter.
Instructions
Tool Usage
query_datadog(resource_type=TYPE, query=QUERY, time_from=START, time_to=END, limit=N, interval=MS, account=LABEL)
Resource Types
'accounts'-- List the connected Datadog organizations. Takes no query and calls no Datadog API. See "Multiple Organizations" below.'logs'-- Search log entries. query=Datadog log query syntax e.g."service:web status:error"'metrics'-- Query metric timeseries (raw points). query=metric query e.g."avg:system.cpu.user{*}"'metric_stats'-- Percentile summary per series (p50/p95/p99/max/mean). Same metric query syntax as'metrics', but returns one compact row per series instead of raw points. Use this for capacity and right-sizing questions over long windows.'monitors'-- List monitors with status. query=name filter (optional)'events'-- Platform events. query=source filter (optional)'traces'-- APM spans/traces. query=span query e.g."service:web @http.status_code:500"'hosts'-- Infrastructure hosts. query=host filter (optional)'incidents'-- Datadog incidents. Lists active/recent incidents (requires Incident Management; may 403 if not enabled).
Multiple Organizations
Several Datadog orgs may be connected. They hold separate data: a service present in more than one has different logs, metrics and hosts in each.
resource_type='accounts' returns the connected orgs with their labels, sites and org names.
Pass account=<label> on any other resource type to query one; omitting it uses the primary.
Every response carries an account field naming the org that answered.
Labels default to each org's own Datadog name and can be overridden, so assume no particular
naming scheme or count. Match the labels from accounts against the alert's own context (its
environment, region, service or tenant tags). This matters because alerts from every org can
arrive through one pipeline, and querying the wrong one does not error -- it returns that
org's healthy data, which reads as "the service is fine" and derails the investigation. If no
label clearly matches, query the primary and say so rather than guessing.
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.
- 29d ago Changed · +26 lines e51aa7012d46
- 1mo ago First seen · 163 lines · 28 tokens per session scan A 37f1e716dde8
datadog is a skill published in the GitHub repository Arvo-AI/aurora (442 stars, last pushed today), licensed Apache-2.0. It adds 28 tokens to every session and 2,543 once invoked, about $0.0001 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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