Dd Audit AI Activity Agent Skill
Audit what the Bits AI assistant (MCP server) has done in your Datadog org — tool calls by user, resources accessed, and anomaly flags for AI governance.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/datadog-labs/agent-skills --skill dd-audit-ai-activityThe instruction itself
12 sections, as written by the authorAudit Trail: AI Activity Audit
Every Datadog MCP tool call is recorded in Audit Trail under the Bits AI SRE category. This skill surfaces what the AI assistant has done in your org — which users invoked it, which tools were called, and which resources were affected.
Prerequisites
pup auth login # OAuth2 (recommended)
# or set DD_API_KEY + DD_APP_KEY with audit_logs_read scope
Queries
All MCP tool activity in a time window
pup audit-logs search --query "@evt.name:\"MCP Server\"" --from 7d --limit 500 -o json \
| jq '[.data[] | {
timestamp: .attributes.timestamp,
user: .attributes.attributes.usr.email,
actor_type: .attributes.attributes.evt.actor.type,
action: .attributes.attributes.action,
resource_type: .attributes.attributes.asset.type,
resource_id: .attributes.attributes.asset.id,
ip: .attributes.attributes.network.client.ip,
country: .attributes.attributes.network.client.geoip.country.name
}]'
Activity by user (who is using the AI assistant most?)
pup audit-logs search --query "@evt.name:\"MCP Server\"" --from 30d --limit 1000 -o json \
| jq '[.data[] | .attributes.attributes.usr.email]
| group_by(.)
| map({user: .[0], tool_calls: length})
| sort_by(-.tool_calls)'
Resources modified by AI tool calls
pup audit-logs search \
--query "@evt.name:\"MCP Server\" @action:(created OR modified OR deleted)" \
--from 7d --limit 500 -o json \
| jq '[.data[] | {
timestamp: .attributes.timestamp,
user: .attributes.attributes.usr.email,
action: .attributes.attributes.action,
resource_type: .attributes.attributes.asset.type,
resource_id: .attributes.attributes.asset.id
}]'
AI activity for a specific user
pup audit-logs search \
--query "@evt.name:\"MCP Server\" @usr.email:[email protected]" \
--from 30d --limit 500 -o json \
| jq '[.data[] | {
timestamp: .attributes.timestamp,
action: .attributes.attributes.action,
resource_type: .attributes.attributes.asset.type,
resource_id: .attributes.attributes.asset.id
}]'
Weekly summary report
pup audit-logs search --query "@evt.name:\"MCP Server\"" --from 7d --limit 1000 -o json \
| jq '{
total_tool_calls: (.data | length),
unique_users: ([.data[] | .attributes.attributes.usr.email] | unique | length),
top_users: (
[.data[] | .attributes.attributes.usr.email]
| group_by(.)
| map({user: .[0], calls: length})
| sort_by(-.calls)
| .[:5]
),
actions_breakdown: (
[.data[] | .attributes.attributes.action]
| group_by(.)
| map({action: .[0], count: length})
| sort_by(-.count)
),
resource_types: (
[.data[] | .attributes.attributes.asset.type]
| group_by(.)
| map({type: .[0], count: length})
| sort_by(-.count)
)
}'
Anomaly Flags
| Signal | Governance concern |
|--------|--------------------|
| AI performing deleted actions on monitors or dashboards | Review whether destructive AI operations are expected |
| AI acting as SUPPORT_USER | Datadog support using AI on behalf of org |
| First-time user invoking AI tools | New user accessing AI assistant |
| High volume of tool calls in short window | Automated/batch AI usage |
| AI accessing resources outside user's normal scope | Potential over-permissioned AI session |
Output Format
AI Activity Audit — [Org] — [Date Range]
Total MCP tool calls: [N]
Unique users: [N]
Top users:
[[email protected]]: [N] calls
Actions breakdown:
accessed: [N]
modified: [N]
created: [N]
deleted: [N]
Resource types affected:
dashboard: [N]
monitor: [N]
Anomalies:
[List any flagged events with timestamp, user, action, resource]
Context
This skill is most useful for:
- Security reviews: Verifying AI actions were authorized and within expected scope
- Compliance audits: Demonstrating AI activity is logged and attributable to specific users
- Governance reports: Understanding adoption and risk surface of the AI assistant across the org
No other observability vendor audits their AI assistant's actions at this level of detail.
References
Other skills for the same job
different authors, same section of the catalogue
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How to use it
Take datadog-labs/dd-audit-ai-activity from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
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