Devops Infrastructure
CloudAI-X/claude-workflow-v2
Guides Docker, CI/CD pipelines, deployment strategies, infrastructure as code, and observability setup.
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring…
Install Google Agents CLI Observability
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observability --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/google-agents-cli-observability .claude/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .claude/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observabilityType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observability --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/google-agents-cli-observability .agents/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .agents/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observability --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/google-agents-cli-observability .cursor/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .cursor/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/pifferologo/cloud-agents-cli.git --path skills/google-agents-cli-observability--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observability --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/google-agents-cli-observability .gemini/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .gemini/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observabilityInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/google-agents-cli-observability .github/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .github/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install pifferologo/cloud-agents-cli google-agents-cli-observability --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/pifferologo/cloud-agents-cli.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/google-agents-cli-observability .opencode/skills/google-agents-cli-observability && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "google-agents-cli-observability" agent skill from https://github.com/pifferologo/cloud-agents-cli/tree/main/skills/google-agents-cli-observability into .opencode/skills/google-agents-cli-observability/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "google-agents-cli-observability", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
Facts
- Skill name
google-agents-cli-observability- GitHub stars
- 129
- Used in
- 1 other repo
- Token cost
- ~2.5k tokens
- SKILL.md length
- 953 words
- Files
- 3 (incl. references)
- Skills in repo
- 7
- Repo updated
- First seen
- Licence
- Apache-2.0
At a glance
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring…
- Works in 2 steps: Switch to Terraform-managed. Delete the… → Keep the SDK-deployed instance. Skip…
- Wants to set up tracing
- SKILL.md covers Observability Tiers, Cloud Trace, Prompt-Response Logging and BigQuery Agent Analytics Plugin, plus 4 more sections
- Reaches adk.dev
What it does
Google Agents CLI Observability is an agent skill from pifferologo/cloud-agents-cli. This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or…
Its SKILL.md is about 2.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/bigquery-agent-analytics.md` and `references/cloud-trace-and-logging.md`).
It sits in DevOps & Cloud, covering Observability, Data warehousing and Deployment. It works with Google BigQuery, MLflow and Terraform. The repository describes itself as: google cloud agent cli for Drive, Gmail, Calendar, Sheets, Docs, Chat, Admin, and more. Dynamically built from piffer labs. The licence is Apache-2.0.
When your agent uses it
- Wants to set up tracing
- Monitor my ADK agent
- Configure logging
- Add observability
Example prompts
- “set up tracing”
- “monitor my ADK agent”
- “configure logging”
- “/google-agents-cli-observability”
Requirements
- Python 3
Workflow steps
2 steps, taken from the first numbered list in SKILL.md.
- Switch to Terraform-managed. Delete the SDK-deployed Reasoning Engine, then run agents-cli infra single-project followed by agents-cli…
- Keep the SDK-deployed instance. Skip infra single-project and set the observability env vars on the running instance directly via the…
What it can do on your machine
Read from SKILL.md and the folder at commit 5957f5a. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Network
Hosts in commands or code, which the agent is likely to contact:
adk.dev
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
Google Agents CLI Observability loads about 2.5k tokens when it runs, and up to ~3.9k if it reads all its reference files. Until then it costs about 150 tokens; SKILL.md has 953 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
Safety
Auto-check passed
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
SKILL.md
The full file from pifferologo/cloud-agents-cli at commit 5957f5a, republished under its Apache-2.0 licence (© pifferologo). 953 words, ~2,473 tokens.
Download SKILL.mdSave it as
.claude/skills/google-agents-cli-observability/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.- name
- google-agents-cli-observability
- description
- This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents. Covers Cloud Trace, prompt-response logging, BigQuery Agent Analytics, third-party integrations (AgentOps, Phoenix, MLflow, etc.), and troubleshooting. Part of the Google ADK (Agent Development Kit) skills suite. Do NOT use for deployment setup (use google-agents-cli-deploy) or API code patterns (use google-agents-cli-adk-code).
- metadata.author
- metadata.license
- Apache-2.0
- metadata.version
- 0.6.1
ADK Observability Guide
Cloud Trace works out of the box — no infrastructure needed. Prompt-response logging and BigQuery Agent Analytics require Terraform-provisioned infrastructure (service account, GCS bucket, BigQuery dataset). Run
agents-cli infra single-project --project PROJECT_IDto provision these resources. Seereferences/cloud-trace-and-logging.mdfor details, env vars, and verification commands. If your project isn't scaffolded yet, see/google-agents-cli-scaffoldfirst.
Order of operations for agent_runtime deployments
For deployment_target = agent_runtime, run agents-cli infra single-project before the first agents-cli deploy. The Terraform module owns the entire Reasoning Engine resource (display_name, service account, deployment spec, env vars), so applying it after a SDK-based deploy creates a state mismatch — Terraform has no record of the SDK-deployed instance and cannot layer env vars onto it without taking ownership of the whole resource.
If you have already run agents-cli deploy, you have two options:
- Switch to Terraform-managed. Delete the SDK-deployed Reasoning Engine, then run
agents-cli infra single-projectfollowed byagents-cli deploy. Sessions and any in-flight state on the previous instance are lost. - Keep the SDK-deployed instance. Skip
infra single-projectand set the observability env vars on the running instance directly via thevertexaiclientupdateAPI. You will also need to grant the instance's service account the IAM permissions required to emit telemetry — writing to the logs GCS bucket, BigQuery dataset access, log writer, etc. Seedeployment/terraform/single-project/iam.tfandtelemetry.tfin your scaffolded project for the full set of bindings the Terraform module would otherwise provision. Terraform-managed env vars are not available in this mode.
Reference Files
| File | Contents |
|---|---|
references/cloud-trace-and-logging.md | Scaffolded project details — Terraform-provisioned resources, environment variables, verification commands, enabling/disabling locally |
references/bigquery-agent-analytics.md | BQ Agent Analytics plugin — enabling, key features, GCS offloading, tool provenance |
Observability Tiers
Choose the right level of observability based on your needs:
| Tier | What It Does | Scope | Default State | Best For |
|---|---|---|---|---|
| Cloud Trace | Distributed tracing — execution flow, latency, errors via OpenTelemetry spans | All templates, all environments | Always enabled | Debugging latency, understanding agent execution flow |
| Prompt-Response Logging | GenAI interactions exported to GCS, BigQuery, and Cloud Logging | ADK agents only | Disabled locally, enabled when deployed | Auditing LLM interactions, compliance |
| BigQuery Agent Analytics | Structured agent events (LLM calls, tool use, outcomes) to BigQuery | ADK agents with plugin enabled | Opt-in (--bq-analytics at scaffold time) | Conversational analytics, custom dashboards, LLM-as-judge evals |
| Third-Party Integrations | External observability platforms (AgentOps, Phoenix, MLflow, etc.) | Any ADK agent | Opt-in, per-provider setup | Team collaboration, specialized visualization, prompt management |
Ask the user which tier(s) they need — they can be combined. Cloud Trace is always on; the others are additive.
Cloud Trace
ADK uses OpenTelemetry to emit distributed traces. Every agent invocation produces spans that track the full execution flow.
Span Hierarchy
invocation
└── agent_run (one per agent in the chain)
├── call_llm (model request/response)
└── execute_tool (tool execution)Setup by Deployment Type
| Deployment | Setup |
|---|---|
| Agent Runtime | Automatic — traces are exported to Cloud Trace by default |
| Cloud Run (scaffolded) | Automatic — setup_telemetry() configures Cloud Trace/Logging exporters |
| GKE (scaffolded) | Automatic — setup_telemetry() configures Cloud Trace/Logging exporters |
| Cloud Run / GKE (manual) | Configure OpenTelemetry exporter in your app |
| Local dev | Works with agents-cli playground; traces visible in Cloud Console |
View traces: Cloud Console → Trace → Trace explorer
For detailed setup instructions (Agent Runtime CLI/SDK, Cloud Run, custom deployments), fetch https://adk.dev/integrations/cloud-trace/index.md.
Prompt-Response Logging
Captures GenAI interactions (model name, tokens, timing) and exports to GCS (JSONL) and BigQuery (via direct log sinks and external tables). Privacy-preserving by default — only metadata is logged unless explicitly configured otherwise.
Key env var: OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT — OTel GenAI semantic-conventions standard (modes: span_only, event_only, span_and_event, no_content). The scaffolded setup_telemetry() collapses every non-false value to NO_CONTENT (metadata-only); false disables capture. Logging is disabled locally unless LOGS_BUCKET_NAME is set.
For scaffolded project details (Terraform resources, env vars, privacy modes, enabling/disabling, verification commands), see references/cloud-trace-and-logging.md.
For ADK logging docs (log levels, configuration, debugging), fetch https://adk.dev/observability/logging/index.md.
Show full SKILL.md (352 more words)Show less
BigQuery Agent Analytics Plugin
Optional plugin that logs structured agent events to BigQuery. Enable with --bq-analytics at scaffold time. See references/bigquery-agent-analytics.md for details.
Third-Party Integrations
ADK supports several third-party observability platforms. Each uses OpenTelemetry or custom instrumentation to capture agent behavior.
| Platform | Key Differentiator | Setup Complexity | Self-Hosted Option |
|---|---|---|---|
| AgentOps | Session replays, 2-line setup, replaces native telemetry | Minimal | No (SaaS) |
| Arize AX | Commercial platform, production monitoring, evaluation dashboards | Low | No (SaaS) |
| Phoenix | Open-source, custom evaluators, experiment testing | Low | Yes |
| MLflow | OTel traces to MLflow Tracking Server, span tree visualization | Medium (needs SQL backend) | Yes |
| Monocle | 1-call setup, VS Code Gantt chart visualizer | Minimal | Yes (local files) |
| Weave | W&B platform, team collaboration, timeline views | Low | No (SaaS) |
| Freeplay | Prompt management + evals + observability in one platform | Low | No (SaaS) |
Ask the user which platform they prefer — present the trade-offs and let them choose. For setup details, fetch the relevant ADK docs page from the Deep Dive table below.
Troubleshooting
| Issue | Solution |
|---|---|
| No traces in Cloud Trace | Verify setup_telemetry() runs at startup and the service account has the cloudtrace.agent role |
| Prompt-response data not appearing | Check LOGS_BUCKET_NAME is set; verify SA has storage.objectCreator on the bucket; check app logs for telemetry setup warnings |
| Privacy mode misconfigured | Check OTEL_INSTRUMENTATION_GENAI_CAPTURE_MESSAGE_CONTENT value — use NO_CONTENT for metadata-only, false to disable |
| BigQuery Analytics not logging | Verify plugin is configured in app/agent.py; check BQ_ANALYTICS_DATASET_ID env var is set |
| Third-party integration not capturing spans | Check provider-specific env vars (API keys, endpoints); some providers (AgentOps) replace native telemetry |
| Traces missing tool spans | Tool execution spans appear under execute_tool — check trace explorer filters |
| High telemetry costs | Switch to NO_CONTENT mode; reduce BigQuery retention; disable unused tiers |
Deep Dive: ADK Docs (WebFetch URLs)
For detailed documentation beyond what this skill covers, fetch these pages:
| Topic | URL |
|---|---|
| Observability overview | https://adk.dev/observability/index.md |
| Agent activity logging | https://adk.dev/observability/logging/index.md |
| Cloud Trace integration | https://adk.dev/integrations/cloud-trace/index.md |
| BigQuery Agent Analytics | https://adk.dev/integrations/bigquery-agent-analytics/index.md |
| AgentOps | https://adk.dev/integrations/agentops/index.md |
| Arize AX | https://adk.dev/integrations/arize-ax/index.md |
| Phoenix (Arize) | https://adk.dev/integrations/phoenix/index.md |
| MLflow tracing | https://adk.dev/integrations/mlflow-tracing/index.md |
| Monocle | https://adk.dev/integrations/monocle/index.md |
| W&B Weave | https://adk.dev/integrations/weave/index.md |
| Freeplay | https://adk.dev/integrations/freeplay/index.md |
Related Skills
/google-agents-cli-deploy— Deployment targets, CI/CD pipelines, and production workflows/google-agents-cli-workflow— Development workflow, coding guidelines, and operational rules/google-agents-cli-adk-code— ADK Python API quick reference for writing agent code
© pifferologo, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 2 other files (references) in skills/google-agents-cli-observability of pifferologo/cloud-agents-cli.
- SKILL.md
- references/bigquery-agent-analytics.md
- references/cloud-trace-and-logging.md
Open the folder on GitHubat commit 5957f5a
Used in 1 other repository
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in pifferologo/cloud-agents-cli, which our catalogue first saw on October 7, 2026.
Compare with similar skills
Google Agents CLI Observability next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Google Agents CLI Observability this skillpifferologo/cloud-agents-cli | 129 | 1 repos | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Devops InfrastructureCloudAI-X/claude-workflow-v2 | 1.4k | — | ~2.7k | Automated safety check: Notes | MIT | |
| Agent Platform Alert Configurationgoogle/skills | 21k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | |
| Snowflake Deploy Medicjeremylongshore/tons-of-skills-marketplace | 2.8k | — | ~3.9k | Automated safety check: Pass | MIT | |
| Backend Dev Guidelineslangfuse/langfuse | 36k | — | ~1.9k | Automated safety check: Pass | Custom licence | |
| Agentsop Observability Setupagentsope/SkillAlchemy | 459 | — | ~4.4k | Automated safety check: Pass | MIT |
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Questions about Google Agents CLI Observability
What does Google Agents CLI Observability do?
This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring…. Google Agents CLI Observability is an agent skill from pifferologo/cloud-agents-cli. This skill should be used when the user wants to "set up tracing", "monitor my ADK agent", "configure logging", "add observability", "debug production traffic", or needs guidance on monitoring deployed ADK (Agent Development Kit) agents.
When should I use Google Agents CLI Observability?
Google Agents CLI Observability fits situations like: wants to set up tracing; monitor my ADK agent; configure logging; add observability.
How do I install Google Agents CLI Observability in Claude Code?
Run `npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a claude-code`. Or copy the skill folder (skills/google-agents-cli-observability in pifferologo/cloud-agents-cli) into .claude/skills/google-agents-cli-observability in your project. Claude Code loads it when a task matches its description.
How do I install Google Agents CLI Observability in Codex?
Run `npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a codex`. Or copy the skill folder (skills/google-agents-cli-observability in pifferologo/cloud-agents-cli) into .agents/skills/google-agents-cli-observability in your project. Codex loads it when a task matches its description.
Can I use Google Agents CLI Observability in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add pifferologo/cloud-agents-cli --skill google-agents-cli-observability -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/google-agents-cli-observability, .gemini/skills/google-agents-cli-observability, .github/skills/google-agents-cli-observability and .opencode/skills/google-agents-cli-observability in your project.
What does Google Agents CLI Observability need to run?
SKILL.md names no scripts, command-line tools or credentials: Google Agents CLI Observability is instructions for the agent only. Our summary lists: Python 3.
Does Google Agents CLI Observability access the network?
SKILL.md names 1 domain. In commands or code: adk.dev; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.
Is Google Agents CLI Observability safe to install?
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
What licence does Google Agents CLI Observability use?
Google Agents CLI Observability is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Google Agents CLI Observability use?
About 2.5k tokens (SKILL.md is roughly 9.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.5k tokens, read only when the agent opens those files.
What are the alternatives to Google Agents CLI Observability?
Skills that share tags, products or a category with Google Agents CLI Observability: Devops Infrastructure (CloudAI-X/claude-workflow-v2, 1.4k stars), Agent Platform Alert Configuration (google/skills, 21k stars), Snowflake Deploy Medic (jeremylongshore/tons-of-skills-marketplace, 2.8k stars) and Backend Dev Guidelines (langfuse/langfuse, 36k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Google Agents CLI Observability?
pifferologo (a GitHub user) maintains it in pifferologo/cloud-agents-cli, which has 129 GitHub stars. The repository holds 7 skills in this directory. The repository was last updated on September 3, 2026.
Source: pifferologo/cloud-agents-cli on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.