All notable changes to this project will be documented in this file.
- Fix an import problem on
uv synccaused by a yankedopentelemetry-resourcedetector-gcpversion - Add optional HTTP-based path for
eval generateusing--url(in-progress feature, stay tuned)
- Cloud telemetry moved to ADK's
otel_to_cloud, across the CLI and deploys.playgroundandrungain an--otel-to-cloudflag that forwards ADK's current--otel_to_cloud; the old--trace-to-cloudstays as a hidden, still-functional alias that warns when used. On the deployment side, Agent Runtime now exports throughotel_to_cloud(gated onGOOGLE_CLOUD_AGENT_ENGINE_ENABLE_TELEMETRY) and generated projects configure Cloud telemetry declaratively in Terraform instead of at runtime. Bundledgoogle-adkmoves to>=2.2.0with theotel-gcpextra, and the observability skill was updated to match. - Scaffolds now default to
gemini-3.6-flash. - Agent Analytics now captures GenAI completions on Agent Runtime. The BigQuery telemetry log sink is configured per deployment target, so Agent Runtime deployments route their GenAI request/response logs into BigQuery instead of leaving the completions view empty.
- Managed Agents guidance in the ADK code skill. The bundled ADK cheatsheet gained a Managed Agents section covering when to use
ManagedAgent, Gemini API vs Agent Platform (GEAP) setup, and a runnable create-and-use example.
- Guided brainstorming for new agents. The workflow skill's Phase 0 is now an interactive brainstorming dialogue that helps you shape an agent's spec before any code is written, and surfaces its assumptions for review when it can't ask.
eval generateandeval gradeno longer clutter output with benign third-party warnings and progress bars that never affected results. This output is still shown on failure and can be re-enabled for debugging.- Generated projects now name the default scaffolded eval metric module
tests/eval/response_quality.py(wasmetrics.py) to match the metric it implements. - Broad Windows compatibility fixes across the CLI.
- Fixed a command-name typo in user-facing hints so they point to the correct
agents-clicommand. - Refreshed the bundled skills, including pointing the RAG samples at
core/python/ingoogle/adk-samples.
Agents CLI is now 1.0 — Generally Available. This is our first GA release: a stable, production-ready CLI for scaffolding, evaluating, and deploying ADK agents on Google Cloud.
- Redeploys now preserve the existing deployment spec on Agent Runtime and Cloud Run instead of resetting unspecified settings.
- Agent Runtime deploys now honor
.gcloudignoreand.gitignorewhen packaging source, so uploads no longer include ignored files. - RAG is now a clone-and-study recipe: start from the
rag-vector-search/rag-agent-searchsamples ingoogle/adk-samples(surfaced via the workflow skill). Theagentic_ragtemplate, the--datastoreflag, and theinfra datastore/data-ingestioncommands were removed and now print a redirect. - Generated projects now consolidate Python environment configuration into a single templated
.envfile. - Eval commands now tolerate ADK toolsets when introspecting eval metadata, so agents that use toolsets no longer fail metadata collection.
- GKE Cloud Build deploys are now resilient to log-streaming limits and no longer fail when the build log stream is truncated.
- Refreshed the bundled skills: RAG samples point to
core/on adk-samplesmain, the always-active workflow skill was generalized and trimmed, and the ADK code guidance notesstreaming_agent_run_with_eventsfor debugging on Agent Runtime.
publish gemini-enterprisenow registers Agent Runtime deployments via ADK by default, which Gemini Enterprise invokes natively and reliably. A2A registration remains the default for Cloud Run and GKE; requesting A2A on Agent Runtime now warns and recommends ADK. Re-publishing an A2A agent no longer creates duplicate registrations, and A2A agent cards now carry the correct public URL on the first deploy.agents-cli updatenow exits non-zero and clearly reports when a skill fails to update, instead of always printing a misleading green "Skills updated." banner. Also fixes failure messages rendering in the wrong color on Windows PowerShell.- Refreshed the generated project
uv.lockfiles for all templated agents, updating bundledgoogle-adkfrom 2.2.0 to 2.3.0.
- Agent Runtime deploys now serve ADK web, A2A, and the reasoning engine from a single unified container app.
- Cloud Trace spans no longer capture LLM prompts and responses, keeping sensitive content out of traces.
- Refreshed the bundled skills: correctness fixes, de-duplication, and a leaner always-active workflow guide, plus a2ui documented in the ADK code cheatsheet.
- Fixed run and playground commands on Windows
- Fixed stale GCS bucket in failure-investigation guide
- Added Agent Registry fleet management to publish skill
deploynow surfaces machine-shape parameters as flags for Agent Runtime and Cloud Run.deployadds a--service-nameoverride.runprints a copy-pasteable resume command in the session footer.runno longer tears down a reused local server on a plain run.scaffold upgradenow builds the prior-version template viauvx.- Skills setup/update no longer hangs on large
npxoutput (a pipe-buffer deadlock). - The project-root notice now only prints when the command actually changes directory.
- Fixed pre-existing inaccuracies in the bundled skills and generated project READMEs.
- Source code is now published to the public GitHub repo: https://github.com/google/agents-cli
- Scaffolded Python templates now use ADK 2.0 GA. New
adk,adk_a2a, andagentic_ragprojects pingoogle-adk[gcp]>=2.0.0,<3.0.0; the[gcp]extra restores the OpenTelemetry GCP exporters and bundles the BigQuery client, so the separate[bigquery-analytics]extra is no longer needed. Cloud SQL sessions on Cloud Run and GKE keep working under 2.0. The bundled ADK coding skill and its reference docs were refreshed for 2.0. - Agent Runtime deploys no longer overwrite a user-supplied
AGENT_VERSION(orNUM_WORKERS) passed via--update-env-vars, matching Cloud Run behavior. The "version not found" warning now names thepyproject.tomlfield to set. - Fixed a stale
deployment/terraform/dev/path in the Cloud Trace observability guide so it matches the currentsingle-projectterraform layout.
eval generatenow works on ADK 2.x projects that use built-in tools such asVertexAiSearchTool. Raised thegoogle-cloud-aiplatformfloor to 1.156.0, which carries the SDK fix.- Skills installed via
agents-cli setupare now visible to Antigravity. Global skills are mirrored into the Antigravity skill directories. updatenow surfaces errors clearly instead of failing silently.- Agent deploys tolerate a corrupt or malformed
deployment_metadata.jsoninstead of crashing. - Deployment timestamps are now timezone-aware.
- A malformed
AGENTS_CLI_EXPERIMENTSvalue no longer crashes the CLI. agents-cli installnow runs with--locked, so a drifteduv.lockfails fast instead of silently resolving new dependency versions.
- The eval data format changed from ADK
EvalSetto Vertex AIEvaluationDataset. Existingtests/eval/evalsets/*.evalset.jsonfiles are no longer read byagents-cli eval generateand friends. See Migrating Eval Datasets for the conversion.scaffold upgradenow prints a notice when legacy files are detected.
- Added
eval dataset synthesizefor LLM-driven user-simulation dataset generation. - Added
eval generateto run agent inference over anEvaluationDatasetand emit traces. - Added
eval gradeto score agent traces against built-in or custom metrics. - Added
eval submitto submit an end-to-end cloud-side evaluation run on Vertex AI Eval Service. - Added
eval resultsto fetch results from a completed cloud evaluation run. - Added
eval analyzefor failure-mode analysis over graded results. - Added
eval metric listto discover built-in evaluation metrics. - Rewrote the
evalskill end-to-end to cover the Quality Flywheel workflow (dataset, generate, grade, analyze, optimize).
- Minor skills consistency fixes
- Add --dryrun as an alias for --dry-run
- Smarter skills installation
- Cache credentials for better performance
- Fix is_authenticated to work without gcloud
- Fix agent runtime deploy error to be clearer
- Remove 'beta' from gcloud commands that no longer need them
- Fix broken doc links
- Auto gen lockfile if it is missing before trying to export it in deploy
- Moved agent-cli project config into a language-independent agents-cli-manifest.yaml file
- Old config embedded in pyproject.toml can be automatically migrated with
agents-cli scaffold upgrade
- Old config embedded in pyproject.toml can be automatically migrated with
- Added
eval optimizecommand - add --network-attachment and --dns-peering-* flags to deploy
- Misc startup performance improvements
- Avoid crashes related to terminal encodings
- Fixes #15
- Smarter tool path resolution, especially for Windows
- Fixes #14
- Updated dependency version locks
- Fixes #13
- Added manifest support for Claude and Gemini CLI plugin support
- Fix some bugs around preserving the right config metadata when scaffolding and enhancing and/or upgrading
- Misc doc and skill fixes
- Visual Explainer page for Agents CLI lifecycle at https://google.github.io/agents-cli/
- Cleaned up some dead template code
- Default
infracommands to terraform plan instead of apply - Fix
playgroundto work for Cloud Shell and other similar envs and be more transparent about the underlying command - Update skills to cover need for cloud sql role
- Make
agents-cli infoprint OS info for easier bug reporting - Make
runonly start a background server when requested with--start-server - Clearer display string for ADC auth
- Fix broken doc links
- Fix missing target description for agent_runtime
- Document & image fixes
- Project metadata fixes
- Preserve multi-hop traces in completions_view BigQuery SQL
- Detect legacy ADK skills during setup
- Save inline artifacts to .google-agents-cli/artifacts/
- Fix some Windows shell interaction issues
- Remove unprocessed pass-through args for
deploy, updated skills and --help text - Fix agents-cli considering the user as authenticated when auth got stale
- Auto stop local
runserver on error
- Performance improvements, particularly for CLI startup time
- Doc cleanups
- Initial public release