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Skillssap-setup-btp-agent

sap-setup-btp-agent

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Updated 10-16 08:45

About this skill

Set up a BTP agent

Turn the user's intent into a minimal pilot.yaml, validate it, and render its inputs. The result is a credential-free, version-1 manifest plus a rendered .cookbook/generated.tfvars.json. The coordinator (cookbookctl) validates and renders locally; it makes no live changes to any BTP account.

Start or resume

  1. Work from the Cookbook repository root. Read pilot.yaml.example, docs/cookbookctl.md, and README.md before editing state.
  2. Run ./cookbookctl pilots --json (read-only, works without a manifest) to see the active pilot's stage progress and any parked pilots. Never print secrets or full environment files.
  3. Open with the question that summary answers: use the existing pilot state, or start fresh?
    • If only parked pilots exist, offer to restore one with ./cookbookctl unpark <dir> or start fresh.
    • If an active pilot exists, summarize its architecture and completed stages, then ask whether to resume, revise, or park it.
    • Resume preserves the confirmed architecture. Do not re-ask answered questions.
    • Revise preserves only the choices the user explicitly says to keep. Re-interview every dimension they want to change.
    • Park is the recommended path when the user wants a new pilot: ./cookbookctl park moves the manifest and all local workflow state to .cookbook/parked/<subdomain>-<stamp>/ without contacting BTP, and the next interview starts clean. ./cookbookctl unpark <dir> restores it later.
    • To start a fresh pilot in place of an existing one, park the current manifest and run the interview below from a blank decision set. Never carry the old agent specification or its architecture into the new one unless the user explicitly selects each reused choice.
  4. Otherwise ask for one starting mode:
    • Quick local prototype: follow recipes/01-scaffold-agent/README.md; BTP is not required yet.
    • Full setup: run the interview below, write pilot.yaml, validate, and render.
    • Resume: locate existing local state and report what is missing.

Do not write pilot.yaml until the user has confirmed the resulting summary.

Interview for a full setup

Use progressive disclosure. Ask a small group of related questions, record the answers, and only ask follow-ups enabled by those answers. Material choices require an explicit answer. "No preference" is a valid answer; recommend the first listed option and record it only after the user accepts it.

Prefer structured choices with concrete suggestions over free-text prompts throughout the interview: every question should offer selectable options (with a recommended default first) plus an escape hatch to type something else. Reserve plain free text for genuinely open content that no suggestion can cover.

1. Outcome

  • Do not open with free-text questions. Present the starter scenarios in templates/ as one multiple-choice question — structured options where the harness supports them (Claude Code: AskUserQuestion), a numbered list otherwise. One option per template, labeled with its scenario.title and one-line scenario.summary, plus a final Custom agent option for an outcome described from scratch.
  • When a scenario is selected, copy its agent block as the starting decisions: show the derived kebab-case name, purpose, audience, mock tools, and skills, and ask the user to confirm or adjust them (the name and the eventual data system are the two most common edits; scenario.eventual_system is a suggestion, not a requirement).
  • Only for Custom agent, ask the open questions in plain text: what the agent does, who uses it, and which business system or API eventually supplies real data — then derive and confirm a kebab-case name and a comparable tool/skill set.
  • Default to mock tools for the first conversation unless the user explicitly wants a live backend now. Never request backend secrets in chat.

2. Account

  • Probe the session before asking anything: run ./cookbookctl accounts --json first. It is read-only, needs no manifest, and doubles as the login check — when no BTP CLI session exists it exits 1 with that finding; when one exists it reports the session's global account and every visible subaccount. When a manifest exists, it also assesses that manifest's own subdomain as available (free to create) or already-exists (the subdomain is taken).
  • Only when the probe reports no session, ask the user to authenticate themselves with btp login --sso, then rerun the discovery. Never ask an already-logged-in user to log in, and never accept passwords, tokens, service keys, certificates, or API keys in chat or pilot.yaml.
  • The visible subaccount list is raw BTP inventory, not a list of pilots this workspace owns. Resume applies only to workspace-managed pilots surfaced by ./cookbookctl pilots --json (see Start or resume). Never present an existing BTP subaccount as a pilot to resume — the account list proves only that a subdomain exists, not that this workspace created or manages it.
  • When a session exists, open with one targeting chooser built from the discovery output — "You are targeting (subdomain <x>). Create a new subaccount, or resume a workspace-managed pilot?" — with structured options:
    • Create a new subaccount (recommended default): collect display name, subdomain, BTP region, administrators, and production relevance; propose a subdomain that does not collide with any visible subaccount.
    • Resume a workspace-managed pilot — offer this only for the active or parked pilots reported by pilots --json, never for a bare subaccount row.
    • If the targeted global account is wrong, ask the user to rerun btp login --sso, select the intended account during login, and rerun the discovery; a CLI session is bound to one global account at a time. Prefill account.global_account_subdomain from the session.
  • Treat every visible subaccount as a collision to avoid: when a chosen new subdomain matches one — the probe reports already-exists for the manifest subdomain — report it and pick a non-colliding subdomain. Do not reuse or adopt an existing subaccount; the public flow has no adoption path.

3. Runtime

  • Cloud Foundry: recommend for the simplest application deployment. Ask for runtime memory, at least one space, and its developers. Leave api_url, bootstrap_user, and user_origin unset unless the user has independently verified them; do not guess a shard-specific CF API URL or carry a bootstrap identity from another subaccount.
  • Kyma: use for Kubernetes, containers, or cluster-level controls. Ask for required versus if_available, hyperscaler plan, cluster region, machine type, autoscaler bounds, and later the expected kube context.
  • Never enable both runtimes. if_available pauses when quota is absent; it does not silently fall back to Cloud Foundry. Ask explicitly before changing the selected runtime.

4. Task state and application stack

  • In memory: recommend for MVPs. Explain that state is lost on restart and not shared across replicas.
  • HANA: use when tasks must survive restarts or scale-out. Explain that it requires TypeScript + CAP and adds the hana / hdi-shared entitlement. Ask the user to confirm that constrained stack; do not offer Python or Express with HANA.
  • With in-memory state, explicitly ask: Which application stack does your team prefer?
    • TypeScript + Express — recommended for the smallest pilot.
    • TypeScript + CAP — for CAP teams or an MTA-oriented application shape.
    • Python — the Python A2A SDK / Uvicorn shape; do not call it Express.
    • No preference — record TypeScript + Express only after the user accepts the recommendation.
  • Never infer the stack from an existing manifest, installed local runtime, example agent, or "use a sensible placeholder" answer.

5. Model

  • SAP AI Core: add aicore / extended; verify regional availability and remaining entitlement before selecting it. Run the region preflight (scripts/region-preflight/region-preflight.sh <region>) for sovereign or unfamiliar regions first.
  • OpenAI-compatible: omit AI Core. Collect only non-secret endpoint metadata; credentials remain environment variables or runtime secrets.
  • If the target region does not expose AI Core, require an approved OpenAI-compatible endpoint. Do not select an unavailable provider.

6. Joule

  • Ask whether Joule integration is required, and capture the answer as a manifest choice.
  • If no, omit Joule, Destination, and XSUAA.
  • If yes, verify regional availability; collect developer users or groups, identity-provider origin, tenant type, and whether Process Automation is included. Enabling Joule automatically adds destination / lite and xsuaa / application. Treat Destination Lite and XSUAA as required dependencies, not automatically as paid services.

7. Confirm

Show one compact summary before writing anything:

Subaccount:     <new name> (<region>)
Runtime:        <Cloud Foundry memory | Kyma plan/cluster region>
Application:    <language + framework>
Task store:     <memory | HANA>
LLM:            <AI Core | OpenAI-compatible>
Joule:          <disabled | enabled>
Data:           <mock | named system/API>

Mark every material choice as user-selected, required by another choice, or recommended default accepted. Ask for confirmation of this architecture. Confirmation is permission to write pilot.yaml and run local validation and rendering — nothing else.

Materialize the decisions

  1. Copy the structure of pilot.yaml.example into the gitignored pilot.yaml and remove examples not selected by the user.
  2. Populate agent.spec with at least one realistic tool and one skill. Use a backend: mock marker until live connectivity is explicitly selected.
  3. Keep services.entitlements for user-added services only. cookbookctl automatically closes these dependencies:
    • AI Core provider -> aicore / extended
    • HANA task store -> hana / hdi-shared
    • Joule -> destination / lite and xsuaa / application
    • CF memory, Kyma, and Joule use their dedicated manifest sections.
  4. Run ./cookbookctl validate for a state-free schema and dependency check. Then run ./cookbookctl render to materialize and inspect .cookbook/generated.tfvars.json.
  5. Run the region preflight for sovereign or unfamiliar regions before selecting AI Core or Joule.

Validate, render, and resume

  1. ./cookbookctl validate is state-free: it checks the manifest's schema and dependency closure without contacting BTP. Run it after every edit.
  2. ./cookbookctl render writes .cookbook/generated.tfvars.json from the validated manifest. It contains no secrets and no agent.spec fields.
  3. Use ./cookbookctl status and ./cookbookctl pilots to confirm the current pilot's stage or to resume one later.
  4. Editing pilot.yaml changes its content hash, so re-run render after any change.
  5. Use ./cookbookctl park and ./cookbookctl unpark <dir> to switch between pilots without losing local state.