Dd Audit

Organization

datadog-labs

dd-audit

Audit Trail investigations - who changed what, key compromise, cost spike root cause, compliance evidence (SOC 2/PCI), and AI activity auditing.

Overview

Publisher	datadog-labs
Repository	`agent-skills`
Skill name	`dd-audit`
Stars	172
Forks	28
Bundled files	1
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by datadog-labs on GitHub. Read the source before you install it.

Installation

Install the Dd Audit AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/datadog-labs/agent-skills.git /tmp/agent-skills
mkdir -p .claude/skills
cp -r /tmp/agent-skills/dd-audit .claude/skills/dd-audit

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dd Audit in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dd Audit on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dd Audit is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Datadog Audit Trail

Investigate user activity, configuration changes, access patterns, and compliance evidence using pup audit-logs.

Sub-Skills

Sub-skill	Use when
security-investigation	"Who changed X?", "What did this user do?", "Show me deletions in the last 24h"
key-compromise	"Was this API key compromised?", "What did key XYZ do?", "Investigate suspicious key activity"
cost-spike-investigation	"Why did my bill go up?", "What caused this usage spike?", "Investigate LLM cost increase"
compliance-report	"Generate SOC 2 evidence", "PCI audit log", "User provisioning report for auditor"
ai-activity-audit	"What did the AI assistant do?", "Audit MCP tool calls", "AI governance report"

Prerequisites

bash
pup auth login   # OAuth2 (recommended)
# or set DD_API_KEY + DD_APP_KEY with audit_logs_read scope

Commands

bash
# List recent events
pup audit-logs list --from 1h --limit 100

# Search with a query
pup audit-logs search --query "@action:deleted" --from 24h

# JSON output for piping to jq
pup audit-logs search --query "@usr.email:alice@example.com" --from 7d -o json | jq '.data[].attributes'

Event Schema Quick Reference

Field	Description	Example values
`@usr.email`	Actor email	`alice@example.com`
`@evt.actor.type`	How action was taken	`USER`, `API_KEY`, `SUPPORT_USER`
`@action`	Verb	`created`, `modified`, `deleted`, `accessed`, `login`
`@evt.name`	Event category	`Dashboard`, `Monitor`, `Authentication`, `Access Management`
`@asset.type`	Resource type	`dashboard`, `monitor`, `api_key`, `role`, `user`
`@asset.id`	Resource identifier	`abc-123`
`@metadata.api_key.id`	API key used (if applicable)	`key_abc123`
`@metadata.app_key.id`	App key used (if applicable)	`app_abc123`
`@network.client.ip`	Client IP address	`1.2.3.4`
`@network.client.geoip.country.name`	Country	`United States`
`@network.client.geoip.as.name`	ASN name	`Amazon.com`
`@http.url_details.path`	API endpoint path	`/api/v1/dashboard/xyz`

Search Syntax

Same Lucene-style syntax as Log Explorer:

Query	Meaning
`@evt.name:Dashboard`	Exact field match
`@action:deleted`	Action filter
`@usr.email:alice@example.com`	Specific user
`@evt.name:Monitor AND @action:modified`	Compound
`-@action:deleted`	Negation
`@usr.email:*`	Field exists
`@network.client.ip:1.2.3.4`	IP filter

Retention

Default retention is 90 days. If querying beyond 90 days, archive to S3/GCS/Azure Blob must be configured. Always check whether the requested time window falls within retention before running a query.

Troubleshooting

Problem	Cause	Fix
403 Forbidden	Missing `audit_logs_read` scope	Add scope to app key in Datadog UI
Empty results	Time window outside retention	Check archive config; default max is 90 days
Timeout	Query too broad	Narrow time window or add more filters
No IP data	Internal action or pre-enrichment event	Not all events have geo data

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

compliance-report/references/control-mapping.md4 KB

Frequently asked questions

What does the Dd Audit AI skill do?

Audit Trail investigations - who changed what, key compromise, cost spike root cause, compliance evidence (SOC 2/PCI), and AI activity auditing.

Why use Dd Audit on TypingMind?

Because you install it once and use it with any model. Dd Audit is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dd Audit in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/datadog-labs/agent-skills/tree/main/dd-audit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dd Audit?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dd Audit?

As many as you like. As long as a model supports skills, you can use Dd Audit with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dd Audit AI skill free?

Yes. It is published on GitHub by datadog-labs under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Datadog Audit Trail

Sub-Skills

Prerequisites

Commands

Event Schema Quick Reference

Search Syntax

Retention

Troubleshooting

References

Bundled files

Frequently asked questions

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