claudegoodies
Skill

pod-sales

From ruvnet

Run one tick of the sales business-pod (ADR-164 §4.1, Phase 2). Loads templates/sales.json, validates it against the pod-schema, resolves agents against ruflo's agent registry, reserves budget via the Phase-2 file-based stub ledger (atomic SQLite tracker is Phase 3 per ADR-164.1), constructs per-agent dry-run prompts, posts a summary envelope to room "sales" via the federation_bbs_publish JSONL backing store, and emits a structured {podName, tickId, agentsRan, totalUsd, envelopeId, status} line for /loop ingestion. Dry-run by default; --live is reserved for Phase 3.

Facts

Repository
ruvnet/ruflo
Status
Actively maintained
Last commit
Declared tools
Bash
Source file
plugins/ruflo-business-pods/skills/pod-sales/SKILL.md

Source preview

The instructions Claude Code reads when this skill runs.

Surfaces `pod-tick.mjs` as a single-shot skill for the sales pod. Use when
Claude Code needs to demonstrate, smoke-test, or schedule one iteration of
the sales autopilot without spawning real LLM workers.

## Algorithm

Implementation: [`scripts/pod-tick.mjs`](../../scripts/pod-tick.mjs).

1. Parse args (`--pod-template`, `--base-path`, `--dry-run` / `--live`,
   `--budget-cap-usd`, `--tick-id`). `--live` is refused with exit code 3
   in Phase 2.
2. Load the pod template JSON (default: `templates/sales.json`).
3. Validate via `validatePodTemplate(json)` — schema in
   `v3/@claude-flow/cli/src/business-pods/pod-schema.ts` and inlined in
   `pod-tick.mjs` so the script runs without a built CLI. Throws with a
   JSON-pointer path on the first violation.
4. Resolve every `agent.agentType` against `KNOWN_AGENT_TYPES`. Unknown
   types abort with exit code 2 and an actionable error.
5. Reserve `min(budgetUsdPerRun, --budget-cap-usd)` USD against the
   file-based ledger at `<base-path>/budget/<roomId>.json`. Honors
   `reservationExpiryMs` (default 60_000 ms, bounded to [5000, 300000]
   per ADR-164.1 §3.2). `TODO(adr-164.1)`: swap the file ledger for the
   atomic SQLite tracker in Phase 3.
6. Build per-agent prompts (kickoff scoped to the bench description +
   pod's PII policy). In `--dry-run` they are logged to stderr and the
   model is never invoked.
7. Commit the reservation.
View full source on GitHub →

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