Cxas Agent Foundry

Agent Foundry

End-to-end lifecycle for GECX conversational agents: build, test, debug, iterate.

Step tracking — MANDATORY (Phase 0, blocking)

Before doing ANY work — including running setup, asking questions, or scaffolding files — initialize <project>/todo.md from the relevant sub-skill's checklist (verbatim). The checklist is a contract, not a suggestion. If todo.md doesn't exist for the current task, refuse to proceed and create it first.

Long debug/build runs skip verification steps under pressure (e.g., pushing without linting, scaffolding without a TDD, claiming "deployed" without actually pushing). The checklist exists because of this. The instinct to skip a step is the moment the checklist earns its keep — that's when you must consult it, not the moment to bypass it.

Quick Reference

# Lint: dispatch agents/lint-fixer.md sub-agent — DO NOT run `cxas lint` on the main thread.
# Lint output is verbose; keep it inside the sub-agent context.

# Push local files to platform (only after lint-fixer returns status: clean)
cxas push --app-dir <project>/cxas_app/<AppName> \
  --to projects/<project_id>/locations/<location>/apps/<app_id> \
  --project-id <project_id> --location <location>

# Pull platform state to local (use --version-id to export an immutable version snapshot instead of live draft)
cxas pull projects/<project_id>/locations/<location>/apps/<app_id> \
  --project-id <project_id> --location <location> --target-dir <project>/cxas_app/ \
  [--version-id <version_id_or_name>]

# Run evals + triage + report (single command)
python .agents/skills/cxas-agent-foundry/scripts/run-and-report.py --message "what changed" --runs 5

# Generate dynamic interactive HTML dashboard with Gemini LLM failure clustering and parameter filters
python .agents/skills/cxas-agent-foundry/scripts/generate_interactive_report.py --input <path_to_sim_results.json> --output <path_to_report.html>

# Inspect app architecture
python .agents/skills/cxas-agent-foundry/scripts/inspect-app.py

# Triage failures
python .agents/skills/cxas-agent-foundry/scripts/triage-results.py --last 3

# Run all 6 build-verification gates against the deployed app
python .agents/skills/cxas-agent-foundry/scripts/gate-check.py

# Tune scoring thresholds (similarity, hallucination, extra-tools)
python .agents/skills/cxas-agent-foundry/scripts/app-thresholds.py show

# Sync callback Python code into evals/callback_tests/agents/ + create test.py symlinks.
# Required for tests to be discoverable by test_all_callbacks_in_app_dir.
python .agents/skills/cxas-agent-foundry/scripts/sync-callbacks.py                  # post-push: pull from platform
python .agents/skills/cxas-agent-foundry/scripts/sync-callbacks.py --from-local <app_dir>  # pre-push: copy from local app dir

# Snapshot app version (create immutable platform backup)
cxas versions create --app-name projects/<project_id>/locations/<location>/apps/<app_id> \
  --display-name "v1.0.0-snapshot" --description "Pre-refactor baseline"

# List and compare app versions
cxas versions list --app-name projects/<project_id>/locations/<location>/apps/<app_id>
cxas versions compare --app-name projects/<project_id>/locations/<location>/apps/<app_id> \
  --source <version_id_1> --target <version_id_2> --web

# Cold-start setup (first-time only — venv + project bootstrap)
.agents/skills/cxas-agent-foundry/scripts/setup.sh
python .agents/skills/cxas-agent-foundry/scripts/setup-project.py

Disambiguation: gate-check.py and inspect-app.py overlap on "show me the architecture" but gate-check.py is the answer whenever the user is about to push, finished building, or wants a verification pass. inspect-app.py is for a quick "what's in here" look without the verification gates. When in doubt, use gate-check.py.

Sub-agents

For heavy diagnosis/analysis work that would otherwise burn main-thread context, dispatch one of these sub-agents via the Agent tool. Pass the contents of the relevant .md file as the prompt, then add the inputs the file lists.

For running evals: there is no sub-agent. Use scripts/run-and-report.py --json-summary <path> > /dev/null 2>&1 and read the summary file — see references/debug.md → "Quick Start". The work was deterministic, so it lives in the script.

Reasoning intensity is a hint to the runtime: HIGH sub-agents benefit from more thinking budget / a stronger model, LOW sub-agents are recipe-driven and don't. Each sub-agent file repeats this hint at the top with a one-line justification.

Environment Readiness Check (run BEFORE routing)

Before routing to any sub-skill, check these signals in order:

1. Virtualenv exists? -- Check if .venv/ directory exists
2. Config exists? -- Check if .active-project file exists and the referenced <project>/gecx-config.json exists
3. Has built before? -- Check if any <project>/cxas_app/ directory has content

Detect Intent and Route

Read what the user wants and load the appropriate sub-skill:

Any phrasing that implies creating, building, or setting up an agent/app routes to references/build.md — even if it sounds like "just create the app shell." "Create a new cxas app" is NOT a shortcut to scaffolding; it triggers the full build flow (todo.md → interview/PRD → TDD + approval → scaffold → lint → evals → push). Skipping the interview / TDD because the user said "create" instead of "build" is a routing failure.

Editing an existing agent (instruction tweak, tool change, callback fix) routes to build.md's "Editing an Existing Agent" section — the standard pull → edit → lint → push → run-evals cycle. Don't skip lint or the eval run after — silent regressions are how 90% rates drop to 70%.

If the intent is unclear, ask: "Are you looking to build/create evals, run them, or debug failures?"

Before Starting

Check memory for project-specific context (app ID, variable handling rules, audio scoring workarounds). If not available, ask the user.