Release v1.1.0

Release v1.1.0

• 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 generate and eval grade no 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 (was metrics.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-cli command.
• Refreshed the bundled skills, including pointing the RAG samples at core/python/ in google/adk-samples.

Release v1.0.0

Release v1.0.0

Agents CLI is now 1.0 - GA

• Redeploys now preserve the existing deployment spec on Agent Runtime and Cloud Run instead of resetting unspecified settings.
• Agent Runtime deploys now honor .gcloudignore and .gitignore when 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-search samples in google/adk-samples (surfaced via the workflow skill). The agentic_rag template, the --datastore flag, and the infra datastore / data-ingestion commands were removed and now print a redirect.
• Generated projects now consolidate Python environment configuration into a single templated .env file.
• 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-samples main, the always-active workflow skill was generalized and trimmed, and the ADK code guidance notes streaming_agent_run_with_events for debugging on Agent Runtime.

Release v0.6.1

Release v0.6.1

• publish gemini-enterprise now 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 update now 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.lock files for all templated agents, updating bundled google-adk from 2.2.0 to 2.3.0.

Release v0.6.0

Release v0.6.0

• 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.

Release v0.5.1

Release v0.5.1

• Fixed run and playground commands on Windows
  • #34
  • #35
  • Thanks to @Abdullah-k0de for discovering and reporting these!
• Fixed stale GCS bucket in failure-investigation guide
• Added Agent Registry fleet management to publish skill

Release v0.5.0

Release v0.5.0

• deploy now surfaces machine-shape parameters as flags for Agent Runtime and Cloud Run.
• deploy adds a --service-name override.
• run prints a copy-pasteable resume command in the session footer.
• run no longer tears down a reused local server on a plain run.
• scaffold upgrade now builds the prior-version template via uvx.
• Skills setup/update no longer hangs on large npx output (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

Release v0.4.0

Release v0.4.0

• Scaffolded Python templates now use ADK 2.0 GA. New adk, adk_a2a, and agentic_rag projects pin google-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.
  • #24
• Agent Runtime deploys no longer overwrite a user-supplied AGENT_VERSION (or NUM_WORKERS) passed via --update-env-vars, matching Cloud Run behavior. The "version not found" warning now names the pyproject.toml field to set.
• Fixed a stale deployment/terraform/dev/ path in the Cloud Trace observability guide so it matches the current single-project terraform layout.

Release v0.3.1

Release v0.3.1

• eval generate now works on ADK 2.x projects that use built-in tools such as VertexAiSearchTool. Raised the google-cloud-aiplatform floor to 1.156.0, which carries the SDK fix.
  • #27
• Skills installed via agents-cli setup are now visible to Antigravity. Global skills are mirrored into the Antigravity skill directories.
  • #26
• update now surfaces errors clearly instead of failing silently.
• Agent deploys tolerate a corrupt or malformed deployment_metadata.json instead of crashing.
• Deployment timestamps are now timezone-aware.
• A malformed AGENTS_CLI_EXPERIMENTS value no longer crashes the CLI.
• agents-cli install now runs with --locked, so a drifted uv.lock fails fast instead of silently resolving new dependency versions.

Release v0.3.0

Release v0.3.0

• The eval data format changed from ADK EvalSet to Vertex AI EvaluationDataset. Existing tests/eval/evalsets/*.evalset.json files are no longer read by agents-cli eval generate and friends. See Migrating Eval Datasets for the conversion. scaffold upgrade now prints a notice when legacy files are detected.

• Added eval dataset synthesize for LLM-driven user-simulation dataset generation.

• Added eval generate to run agent inference over an EvaluationDataset and emit traces.

• Added eval grade to score agent traces against built-in or custom metrics.

• Added eval submit to submit an end-to-end cloud-side evaluation run on Vertex AI Eval Service.

• Added eval results to fetch results from a completed cloud evaluation run.

• Added eval analyze for failure-mode analysis over graded results.

• Added eval metric list to discover built-in evaluation metrics.

• Rewrote the eval skill end-to-end to cover the Quality Flywheel workflow (dataset, generate, grade, analyze, optimize).

• Minor skills consistency fixes

Release v0.2.1

Release v0.2.1

• Add --dryrun as an alias for --dry-run
• Smarter skills installation
  • #23
• Cache credentials for better performance
• Fix is_authenticated to work without gcloud
  • #16
• 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
  • #17