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Connect your coding agent, run a public decision, and explain the result from its trace. Then move to a small policy of your own. The first 20 minutes is a suggested learning session, not a measured completion guarantee. Install downloads, host access and human review take different amounts of time. Authoring is a separate stage with an invitation and model-provider access.

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Before you start

  • An installed, signed-in Claude Code or Codex host and Node.js/npm for the MCP server and skill installer.
  • A project directory you control. Start a new agent session there after setup.
  • No Aethis key or model-provider key for public decisions. Your coding agent’s own access is separate.
  • For authoring later: invited access, an Aethis credential profile, and a securely supplied Anthropic key reference.

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1. Connect your host

Start a new Claude Code session and confirm that Aethis tools are available.
If you use the Aethis CLI, aethis mcp install --target claude-code or aethis mcp install --target codex configures the chosen host. --target all includes Codex and requires its executable to be installed. The installer records non-secret profile/configuration references, not key values. Preserve any deliberate existing host overrides; an ambiguous configuration needs review before replacement.

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2. Install and discover the skills

From your project directory:
Select the four Aethis skills in the installer, then start a fresh host session. Ask:
Expected result: the host discovers the four skills and callable MCP tools. A successful shell install alone does not establish discovery inside a running host.

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3. Make and explain a public decision

Expected result: eligible, no blocking field_errors, and a trace from the selected ruleset. The first-decision page shows the corresponding no-key HTTP call. Now check an intentional input error:
Expected result: the misspelt field produces undetermined with a field error; the corrected call returns the original outcome. You have now connected the host, discovered skills/tools, evaluated a case and used the schema to recover from an input error.

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4. Go deeper: author one small policy

Authoring is invite-only and generation uses your model-provider capacity. Finish authentication setup before continuing. Keep credentials out of chat, source files, command arguments and transcripts.
Use aethis login to establish a saved profile, then run the install command for your host again and restart it. The installer pins the selected profile name and configuration location. If a one-off environment key or endpoint conflicts with that profile, save/select the intended profile before installing; do not paste the key into host configuration to bypass the refusal. Supply the provider key through the MCP process’s secure environment or a macOS keychain reference. Pass only its reference name, such as anthropic_key_env: "PARTNER_QA_ANTHROPIC_KEY". A variable in an unrelated terminal is not available to an already-running desktop host. See key management.
Follow Author your first ruleset for exact calls and review checkpoints. Completion means the approved tests pass on the selected project and the published result, with retained identity—not merely that generation stopped.

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Resume after a tool timeout

The host can stop waiting before server generation finishes. Keep the project_id before starting generation. Call aethis_generation_status for that exact project; do not start another generation because a host tool timed out. Use short read-only status calls until the job is terminal, then follow its retry readiness. A lost creation response is a separate uncertainty: inspect existing projects rather than assume nothing was created.

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5. Advanced: versions, composition and integration

Use Versions and replay to run regression-compare on an approved corpus, inspect an existing synthetic composition, replay its immutable release through REST, and integrate decisions in an application. The Python SDK, CLI, MCP server and REST API have distinct supported operations. The TypeScript SDK is not released. A working example on one interface does not certify every workflow on another.