agent-platform-alert-configuration
Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files.
Skill by googleOfficial
Install
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About
Use cases: devops, security, writing, productivity
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Python package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/agent-platform-alert-configuration
Tools it pre-approves 3
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
terraformgcloudpython
What's inside
- Skill name
agent-platform-alert-configuration- Description
- Configures best-practice alerting policies for AI agents using OpenTelemetry (OTel) metrics, generating output as Terraform (.tf) configuration files. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, token usage, and quality metrics. Don't use for standard infrastructure monitoring unrelated to AI agents, or when the agent is not instrumented with OpenTelemetry (for Reliability, Cost, Safety, Security alerts). NOTE: Reliability, Cost, Safety, and Security alerts use generic OTel metrics and work across runtimes (such as Cloud Run, Vertex AI). Quality alerts rely on Vertex AI Online Monitors and are strictly bound to Vertex AI deployments.
- License
- Apache-2.0
- Allowed tools
- terraform, gcloud, python
- Metadata
- version: 1.0.1 · category: AiAndMachineLearning
- Instructions
- 302 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (29)
- SKILL.md
- attribution.md · references/
- cost_alert_policies.md · references/
- has_historical_traffic_data.md · references/
- no_historical_traffic_data.md · references/
- quality_alert_policies.md · references/
- reliability_alert_policies.md · references/
- safety_alert_policies.md · references/
- security_alert_policies.md · references/
- telemetry_enablement.md · references/
- analyze_traffic.py · scripts/
- analyze_traffic_test.py · scripts/
- check_telemetry.py · scripts/
- check_telemetry_test.py · scripts/
- config_utils.py · scripts/
- config_utils_test.py · scripts/
- create_online_monitor.py · scripts/
- create_online_monitor_test.py · scripts/
- gather_agent_info.py · scripts/
- gather_agent_info_test.py · scripts/
- lint_syntax.py · scripts/
- list_log_scope_table_names.py · scripts/
- list_log_scope_table_names_test.py · scripts/
- list_trace_scope_table_names.py · scripts/
- list_trace_scope_table_names_test.py · scripts/
- mock_traffic_data.py · scripts/
- requirements.txt · scripts/
- scan_duplicates.py · scripts/
- scan_duplicates_test.py · scripts/
SKILL.md (first lines)
# Agent Platform Alert Configuration
## Attribution
**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read [Usage Attribution](references/attribution.md). For commands executed
directly in the terminal (never in generated scripts, Terraform, or user code),
prefix `gcloud` with
`CLOUDSDK_METRICS_REQUEST_ATTRIBUTION="agent-skills/1.0 (skill:agent-platform-alert-configuration)"`
and append
`agent-skills/1.0 (skill:agent-platform-alert-configuration)`
to `User-Agent` headers.
## Critical Steps
### 1. Safety & Confirmation Tiers (CRITICAL)
Before executing any commands or writing configurations on behalf of the user,
you MUST adhere to the following safety tiers based on the action requested:
1. **Tier R: Read-only (`check_telemetry.py` / `gather_agent_info.py`)**
* **Rule**: No confirmation needed. You may execute these scripts
immediately to inspect telemetry status or gather agent configuration
details.
2. **Tier B: Billing & Resource Creation (`create_online_monitor.py` /
provisioning)**
* **Rule**: **Explicit User Confirmation Required**. These actions incur
additional billing charges and create cloud resources. The agent MUST
ALWAYS warn the user explicitly about the potential extra billing costs
of BOTH the Online Monitor (specifically mentioning **LLM evaluations**)
and Telemetry (specifically mentioning **Cloud Trace/Cloud Logging
export**). You MUST STOP and ask for explicit approval before proceeding
with provisioning or providing setup commands.
### 2. Prerequisites & Dependencies
#### Agent Telemetry
* **Disclaimer**: For Reliability, Cost, Safety, and Security alerts to
function, the underlying agent MUST be instrumented to emit OpenTelemetry
(OTel) metrics. If the agent does not emit these metrics, the alerting
policies will have no data stream to evaluate.
#### Python Environment
Before executing any python script in this skill you MUST install the required
dependencies in your environment. Run this command first:
```bash
pip install -r scripts/requirements.txt
```
### 3. Input Assumptions
* **Explicit Project Adherence**: You must ONLY configure alerts, query
telemetry, or interact with the Google Cloud Project(s) explicitly provided
by the user in the prompt. Do NOT assume or use other projects from your
environment or history unless the user explicitly directs you to do so.
* **Sequential File Transformations**: If the user explicitly asks to copy a
file and then modify it, you MUST perform these actions sequentially (copy
first, then modify) rather than writing the final content directly.
### 4. Execution Steps
1. **Mandatory Prerequisite Execution Protocol (SEQUENTIAL)**: Before
generating or writing ANY configuration, you MUST execute these steps in
order:
1. **Step 1: Streamlined Discovery (Mandatory)**: Run
`gather_agent_info.py` to automatically identify agent runtime, verify
telemetry, metric scopes, linked datasets, and more. This script covers
most of the manual verifications listed in subsequent steps.
* Command: `python3 scripts/gather_agent_info.py --project-id
{project_id} --agent-name {agent_name}`
* **Note**: If this script **fails**, returns **partial data**, or
doesn't produce everything you need, you MUST satisfy requirements
by running the manual fallback steps listed in Step 2 and then
perform Step 3 below. If Step 1 succeeds and provides all info,
**SKIP** to Step 3 (Pre-existing Policies Verification).
2. **Step 2: Metric Scope Verification (Fallback)**: Run this ONLY if Step
1 failed to determine the metric scope.
* **Action A (CLI)**: Run `gcloud beta monitoring metrics-scopes list
projects/{project_id}`. If a scoping project is returned, you MUST
deploy policies there.
* **Action B (Code Scan)**: Search Terraform configurations for
`google_monitoring_monitored_project` resources to extract the
scoping project.
* **Action C (Fallback)**: If ambiguous, ASK the user: "Are you using
a multi-project Cloud Monitoring Metric Scope? If so, what is the
scoping project ID?"
3. **Step 3: Pre-existing Policies Verification**: Avoid duplicates.
* **Action**: Scan the target directory to see if aggregated policies
already exist targeting the same metrics (grouped by
`reasoning_engine_id` or `gen_ai_agent_name`). Use
`scan_duplicates.py` to verify.
2. **Alert Policy Type Resource Files**: You MUST list and read files under
`references/` with names ending in `_alert_policies.md` to learn how to
configure alert policies based on type. By default you MUST configure all of
the following alert types UNLESS the user requests to generate explicit
alert policies and/or types. Follow their tables of content to help you find
the reference sections you need to read:
Alert Type | Reference File
:-------------- | :-------------
**Reliability** | [reliability_alert_policies.md](references/reliability_alert_policies.md)
**Quality** | [quality_alert_policies.md](references/quality_alert_policies.md)
**Cost** | [cost_alert_policies.md](references/cost_alert_policies.md)
**Safety** | [safety_alert_policies.md](references/safety_alert_policies.md)
**Security** | [security_alert_policies.md](references/security_alert_policies.md)
### 5. Outputs & Formats
* **Always configure the supported alerting policies** for the target agent:
* **For Reliability Monitoring**: You MUST configure exactly five alerting
policies:
1. **Latency** (anomaly monitoring)
2. **Error Rate - Fast Burn SLO** (1-Hour Window)
3. **Error Rate - Slow Burn SLO** (3-Day Window)
4. **Model Call Error Rate** (SQL-based Observability Analytics
Alerting)From google/skills, Apache-2.0.
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- Open issues
- 21
- Last commit (this folder)
- Oct 22, 2026 (5 days ago)
From GitHub (fetched Oct 24, 2026).
Details
- Version
- 1.0.1
- License
- Apache-2.0
- Repository
- github.com/google/skills
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
agent-platform-alert-configuration skill. Agent Mart. https://agentmart.dev/skills/google-agent-platform-alert-configuration (last updated 2026-10-24)