81f72e8068
* initial version of a FAST pre-install skill * first round of testing * Update fast-0-org-setup-prereqs skill with improved UX and local path handling - Add explicit lockout warning and stop condition if the user is not a member of the provided Admin Principal group. - Streamline bootstrap project selection to only prompt for an override if the active gcloud project is rejected. - Restrict dataset discovery strictly to the `fast/stages/0-org-setup/datasets/` directory. - Improve location handling by referencing `defaults.schema.json` for Standard GCP and auto-configuring fixed regions for GCD. - Add comprehensive `local_path` management: prompt for customization, create directories, move `defaults.yaml` to the local data folder, and symlink `0-org-setup.auto.tfvars` back to the stage directory. * add testing scenarios, implement initial changes for scenario 2 * move skills * move to a skills/fast subfolder * Refactor fast-0-org-setup prereqs skill * Add skill-turn-harness utility tool * Use relative markdown links for skill references * Use descriptive titles for markdown links in skill references * Add descriptions to each phase in the prerequisites workflow map * Use backslash for markdown line breaks in skill map * Update README security warning to mention default .gitignore * shebang * Update fast prereqs skill rules to force sequential question flow and refine harness tool with proper ctrl+c handling and slugified log paths * Move playbook-gcp-dev.yaml to fast/prerequisites/gcp-dev.yaml and update fast prerequisites * docs(skill-turn-harness): detail autonomous pond testing approach * docs(skill-turn-harness): add final_state_checks to pond architecture and update toc * Refine fast prereqs SKILL and gcp-dev playbook to strictly align with one-question-at-a-time rule * feat(skill-turn-harness): update playbook schema for autonomous persona mode * feat(skill-turn-harness): implement autonomous persona testing mode and fallback logic * docs(skill-turn-harness): document the three modes of testing and update ToC * implement timeout, schema validation, configurable cli * chore: remove accidentally committed log files * chore: ignore logs directory * feat(skill-harness): implement tool execution interception, configurable workspace, and modularized validation * feat(skill-harness): add model configuration and update README * fix(skill-harness): automatically inject -y flag to gemini commands * docs(skill-harness): add TODO.md with analysis for skill environment dependencies * feat(skill-harness): add working_dir support and clean up fixtures - Implement working_dir in harness to run tests in specific directories. - Rename test fixtures and playbooks to be more descriptive. - Add E2E test for working_dir. - Apply code quality improvements to harness.py (imports, linting). - Update README with working directory considerations and usage notes. - Update phase3-bootstrap-and-iam.md skill doc to add execution rule against creating temp scripts. * fix: capture customer_id and respect relative paths * Implement isolated temp workspace sandboxing with symlinks in test harness * Configure GCD manual autonomous playbook and align Phase 3/4 steps order * Fix linting and schema tests failures - Add missing license headers to tools/skill-turn-harness files. - Fix trailing spaces and newlines in playbooks. - Ignore tools directory in schema tests workflow. TAG=agy CONV=1bb75453-c3e2-448b-bae9-8e332a068012 * Fix Python formatting with yapf TAG=agy CONV=1bb75453-c3e2-448b-bae9-8e332a068012 * Refactor skill-turn-harness to use Antigravity SDK - Migrated harness from gemini-cli subprocesses to Antigravity SDK. - Implemented real-time step streaming and console logging. - Added color-coded terminal output (dark gray headers, blue inputs, pink outputs). - Collapsed excessive newlines in streamed thoughts. - Excluded harness codebase from workspace copy to prevent agent cheating. - Enabled skills folder copy to resolve agent lookup loops. - Added key validation and CLI --debug flag. * Fix autonomous turn layout: print Turn ID before execution - Moved the [Autonomous Turn X] header print to before running the agent turn. - This groups the real-time thinking and tool calls under the correct Turn ID block, instead of displaying them before the label. * Remove obsolete .log.md from prerequisites skill directory
3.4 KiB
3.4 KiB
Phase 1: Environment & Authentication
Step 1: Environment Assessment & Initialization
Important
Do NOT Automate Environment Choice: You MUST explicitly ask the user to clarify their target environment (Standard GCP or GCD) and wait for their response. Do NOT assume or guess based on local config files or active credentials.
Do NOT Automate Command Execution Preference: You MUST ask how they prefer to run commands (automatic vs manual) and wait for their response.
- Ask the user to clarify their target environment: Standard GCP or Google Cloud Dedicated (GCD). Wait for their response.
- Once the environment is confirmed, ask how they prefer to run commands: Should you (Gemini CLI) run them automatically, or should you output them for manual execution? Remember this preference for the rest of the workflow. Wait for their response.
- If GCD is selected, ask the user if they are working in one of the known universes: S3NS (France) or Berlin (Germany).
- If S3NS: Pre-fill the following values:
- Universe Web Domain:
cloud.s3nscloud.fr - Universe API Domain:
s3nsapis.fr - Universe Name:
s3ns - Universe Prefix:
s3ns - Universe Region:
u-france-east1
- Universe Web Domain:
- If Berlin: Pre-fill the following values:
- Universe Web Domain:
cloud.berlin-build0.goog - Universe API Domain:
apis-berlin-build0.goog - Universe Name:
berlin - Universe Prefix:
eu0 - Universe Region:
u-germany-northeast1
- Universe Web Domain:
- If neither (Custom): Gather the 5 universe-specific details manually from the user.
- Action: Present the final list of the 5 universe values to the user for review. Ask for explicit confirmation and offer them the opportunity to change any of the values before proceeding.
- If S3NS: Pre-fill the following values:
Step 2: Authentication
- Ask the user if they are already authenticated with Google Cloud using the correct principal.
- If yes: Run (or ask the user to run)
gcloud config list account --format="value(core.account)"to retrieve the current authenticated principal. Show this principal to the user and explicitly ask them to confirm if this is the correct identity they want to use.- If they confirm: Proceed directly to Phase 2 (Step 3).
- If they do not confirm: Proceed with the authentication steps below.
- If no: Proceed with the authentication steps below.
- If yes: Run (or ask the user to run)
- Standard GCP: Provide or execute the command:
gcloud auth login gcloud auth application-default login - GCD: Automate or guide the user through WIF login. Ask for the workforce pool audience string first, then generate the configuration:
# (Use the gathered GCD variables to fill placeholders) gcloud config configurations create <UNIVERSE_NAME> gcloud config configurations activate <UNIVERSE_NAME> gcloud config set universe_domain <UNIVERSE_API_DOMAIN> gcloud iam workforce-pools create-login-config <AUDIENCE> \ --universe-cloud-web-domain="<UNIVERSE_WEB_DOMAIN>" \ --universe-domain="<UNIVERSE_API_DOMAIN>" \ --output-file="/tmp/wif-login-config-<UNIVERSE_NAME>.json" \ --activate gcloud auth login --login-config=/tmp/wif-login-config-<UNIVERSE_NAME>.json --no-launch-browser gcloud auth application-default login --login-config=/tmp/wif-login-config-<UNIVERSE_NAME>.json - Explicitly ask the user to confirm they have successfully authenticated before moving to the next phase.