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 datadog-labs/agent-skills --skill datadog-appgit clone --depth 1 https://github.com/datadog-labs/agent-skillsWrote 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/datadog-labs/agent-skills/datadog-app)<a href="https://agentmods.dev/skills/datadog-labs/agent-skills/datadog-app"><img src="https://agentmods.dev/badge/skills/datadog-labs/agent-skills/datadog-app/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/datadog-labs/agent-skills/datadog-app"><img src="https://agentmods.dev/badge/skills/datadog-labs/agent-skills/datadog-app.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 | $0.00117 | $0.00631 |
| Opus 5 | $0.00059 | $0.00316 |
| Sonnet 5 | $0.00023 | $0.00126 |
| Haiku 4.5 | $0.00012 | $0.00063 |
Grade A, and why
datadog-app 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 9d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- datadog-app — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 37 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Datadog Apps
Use this skill when a developer is building a Datadog Apps project with TypeScript, React, published packages, and the normal production Datadog site. If the user is modifying Datadog platform packages or testing package source changes, use a platform-engineer-oriented workflow instead.
Overview
Datadog Apps are locally developed web apps built with React and TypeScript or JavaScript. Use Apps when a project needs source control, code review, CI/CD, multi-engineer collaboration, AI-assisted local development, custom UI or logic, or backend code that integrates with services beyond low-code App Builder. Apps share App Builder's permissions model and can be embedded in Datadog surfaces such as dashboards and the Internal Developer Portal.
Reference Routing
Read only the reference needed for the user's task:
| User task | Read |
|---|---|
| Create, scaffold, configure prerequisites, or run locally | references/getting-started.md |
| Build, upload, publish, upload without publishing, add upload-no-publish script, configure Datadog site, or understand upload output | references/build-upload-publish.md |
| Add or update GitHub Actions deployment | references/cicd.md |
| Trigger or poll Workflow Automation from a backend function | references/workflow-http-trigger.md |
| Get started querying data from a Datadog App | references/querying-data/getting-started.md |
| Understand or configure Action Catalog connections | references/querying-data/connections.md |
| Query Datadog App datastores with DDSQL | references/querying-data/ddsql/datastores.md |
| Upgrade Datadog Apps dependencies or compare with a freshly scaffolded app | references/upgrading.md |
| Diagnose OAuth, API/application key auth, upload, Node, site, or backend function failures | references/troubleshooting.md |
Boundaries
- After scaffolding or when working inside an existing app, read the app project's
AGENTS.mdbefore making changes. - For backend function implementation details, rely on the generated app project's
AGENTS.md; this skill only covers local development auth choices and troubleshooting. - Preserve the app project's existing package manager, scripts, Datadog site, and repository conventions.
- Do not cover Datadog package/platform development in this skill.
- Low-code App Builder to Datadog Apps migration guidance is future work. Do not invent a migration process yet.
What ships with it
9 files 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.
- references/build-upload-publish.md 2.8 KB
- references/cicd.md 1.3 KB
- references/getting-started.md 4.6 KB
- references/querying-data/connections.md 2.8 KB
- references/querying-data/ddsql/datastores.md 3.2 KB
- references/querying-data/getting-started.md 6.5 KB
- references/troubleshooting.md 5.1 KB
- references/upgrading.md 2.7 KB
- references/workflow-http-trigger.md 7.5 KB
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.
- 9d ago First seen · 37 lines · 117 tokens per session scan A 4e993341b64f
datadog-app is a skill published in the GitHub repository datadog-labs/agent-skills (166 stars, last pushed 13d ago), licensed MIT. It adds 117 tokens to every session and 631 once invoked, about $0.0006 per session on Opus 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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