06d0ab5e2d
The reactive half of the agent. It consumes product.stock_changed from the catalog topic and reports only a crossing of the threshold — every further order line on an already-low reference would otherwise raise the same alarm, and an agent that repeats itself is one a human learns to ignore. A stock-out is treated as its own fact even when the reference was already low. The detection lands on a watchlist readable over a webhook, because a proposal that reached only an execution log would be lost between two nightly runs. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
202 lines
8.9 KiB
Markdown
202 lines
8.9 KiB
Markdown
# Flows — the autonomous agents
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**Runtime:** n8n · **Mode:** autonomous · Two agents in one repo.
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| Agent | Client id | Trigger |
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| Approvisionnement | `classic-models-agent-approvisionnement` | event-driven, plus a periodic ordering run |
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| Recouvrement | `classic-models-agent-recouvrement` | weekly, Monday |
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They share a repo because they are not code: n8n workflow exports, same tool,
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same owner. Splitting them would buy nothing.
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## Why low-code for these two
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Their work is rules, thresholds and due dates — a sequence of conditions and
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calls, which a visual editor expresses better than code. The LLM is optional on
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their critical path, which makes them cheaper and more predictable than the
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conversational agents.
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They remain full A2A agents: they publish an Agent Card, accept tasks, answer.
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## Approvisionnement
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| MCP | catalog, sales |
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| Scopes | `catalog:read`, `catalog:write`, `sales:read` |
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Detect coming stock-outs, propose reorders — **two jobs with two different
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triggers**, which an earlier revision of this file collapsed into one nightly
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run.
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*Detection is reactive.* It depends on something happening: an order placed, a
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stock level crossing a threshold. Finding that out up to a day later is latency
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chosen for nothing, and a nightly sweep re-reads the whole catalog to rediscover
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what the domain already knew at the moment it changed.
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*Proposing a purchase order is periodic.* Nobody reorders on every unit sold;
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orders are grouped by supplier lead time and buying cycle. A clock is the right
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trigger there, and that run is periodic on purpose rather than a batch standing
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in for events.
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Worth naming, because it changes what has to be built: **the autonomous mandate
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is a cost of the trigger, not of the business need.** `offline_access`, a
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refresh token stored encrypted and an exchange at trigger time are required only
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because nobody is present at 3am. An agent woken by a domain event runs moments
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after a human acted.
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**Exposes** `check_availability` — called by Ventes before promising a delivery
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date, and by Catalogue before discontinuing a reference. Returns a decision and a
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date, never the stock table.
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## Recouvrement
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| MCP | customers, payments |
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| Scopes | `customers:read`, `payments:read`, `payments:write` |
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Weekly: unpaid invoices past 30 days, dunning, escalation.
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**Exposes** `check_creditworthiness` — called by Ventes before accepting a large
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order.
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**Dunning is prepared automatically and sent only after human validation.**
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Sending a letter to a customer is an outward-facing action; a rule bug would
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otherwise write to the entire customer base in one run.
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## The A2A server gap
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The available n8n community nodes ([n8n-nodes-a2a](https://github.com/agentic-layer/n8n-nodes-a2a),
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[n8n-nodes-agent2agent](https://github.com/pjawz/n8n-nodes-agent2agent)) make n8n
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an A2A **client**: `Discover Agent`, `Send Task`.
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But both agents here must be **servers** — Ventes calls them. That needs an
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Agent Card on `/.well-known/agent.json` and a JSON-RPC endpoint with the task
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lifecycle. n8n webhooks can do it by hand, at which point it stops being no-code.
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Preferred approach: **Kong in front of n8n**, exactly as it fronts every other
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resource. Kong serves the Agent Card statically and routes JSON-RPC to the
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webhook, and token verification lands where it already lives. No new component.
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Alternative: a small FastA2A adapter, written once for both — see
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`classic-models-agent-catalogue`, which uses FastA2A already.
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## An autonomous run is a machine identity
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**Superseded, 2026-08-29.** An earlier revision had these agents act under an
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`offline_access` mandate: a user authorises the agent, their refresh token is
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stored encrypted, and it is redeemed at trigger time so `sub` stays the person
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who mandated.
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That was built and then withdrawn, because it is not true. **An agent running on
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its own account acts for itself.** Nobody asked for the 06:00 run; naming a
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person as its principal is a fiction, and choosing which person is arbitrary —
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the first implementation picked whichever test user was to hand.
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It also cost more than it was worth. An offline token has no `exp`; it dies only
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after 30 days unused, is not rotated on use (`revokeRefreshToken: false`), and
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is revocable only by killing that user's offline session. A permanent bearer
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credential, standing in for a consent nobody gave.
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So: `client_credentials`, and the service account carries the realm role the job
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needs. For the periodic reorder run that is **`read_only`** — so `create-product`
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is not merely unused, it is **invisible** to that identity. Least privilege
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enforced by the realm and the gateway rather than by the workflow behaving
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itself. Verified: `tools/list` under the machine identity returns `get-product`
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and `list-products`, nothing more.
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What does *not* change: `azp` still names the agent, the audiences are still
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per-server, and the MCP server still derives the consumer group from the token's
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roles. Downstream policy still needs no knowledge of the trigger mode — it reads
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roles, and a service account has roles like anyone else.
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**Where a mandate would still be right:** when a person's own authority is
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genuinely in play — an action they are accountable for, or data scoped to them.
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Recouvrement's dunning is the candidate, and it is a human-validated step
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already. The `classic-models-mandate` client is left in the realm, unused, for
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that case.
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## Backlog
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**Events over Kafka, emitted by `classic-models-api`.** The target for the
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reactive half. The estate emits no domain event today — the API has no signals
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and no outbound webhook, and there is no bus in the cluster — which is what made
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a nightly sweep look like the only option.
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The emission belongs **in the API**, not in a database CDC and not in a gateway
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plugin. Only the API knows which change is a business event rather than a row
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update, and only it holds the identity that made it — `sub` and `azp` from the
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caller's token, which the event has to carry if a downstream agent is to act
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under the same authority as the person who triggered it.
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Two facts about that codebase shape the work:
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- Every write goes through one `BaseModelViewSet` in
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`api/v1/classicmodels/views.py`. One hook there covers products, orders,
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payments and the rest — Django signals scattered across models would be the
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harder version of the same thing.
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- **The models are `managed = False`.** The tables are the pre-existing
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classicmodels schema and Django owns no migrations for them. A transactional
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outbox means introducing the estate's first managed table beside unmanaged
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ones — which works, and is worth deciding deliberately rather than
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discovering.
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An outbox is the part that matters: emitting from a viewset after `save()` drops
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the event if the process dies between the two, and an agent that never hears
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about a stock movement is worse than one that hears late.
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Until this exists, detection stays unbuilt rather than being approximated by a
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periodic scan: a batch that pretends to be reactive is worse than an absent
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feature, because it looks finished.
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The periodic ordering run does not wait on any of it.
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## Two controls that become mandatory here
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They were deferrable with a human in the loop. They are not, once an agent
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loops on its own.
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- **Read volume caps per `(azp, sub)`**, enforced on Kong. An agent reads a
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thousand records in seconds where a human clicks ten; a scope authorises the
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read but says nothing about volume.
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- **Authorisation on tool-call parameters**, not just the tool name. `write`
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authorises writing, not "this €40k transfer".
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An autonomous agent hitting a rule that requires approval must **fail cleanly
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and escalate**, never decide. And any approval screen must be rendered from the
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structured tool-call parameters — never from a sentence the model produced, or a
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prompt injection writes what the human validates.
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## Before writing workflows
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Read `classic-models-agent-platform/CLAUDE.md` for the identity model, the
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endpoints and the known blockers.
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Deliverables in English. Export workflows as JSON and commit them; do not rely
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on the n8n instance as the source of truth.
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## The Kafka credential is created by hand
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`kafka-classic-models` in n8n holds the SCRAM password of the
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`classic-models-agent-approvisionnement` KafkaUser and the Strimzi cluster CA.
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It is not in this repo and must not be: n8n encrypts stored credentials with
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`N8N_ENCRYPTION_KEY`, and the committed workflow JSON references it by id only.
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To recreate it after a rebuild:
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```
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kubectl -n kafka get secret classic-models-agent-approvisionnement \
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-o jsonpath='{.data.password}' | base64 -d
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kubectl -n kafka get secret kafka-cluster-ca-cert \
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-o jsonpath='{.data.ca\.crt}' | base64 -d
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```
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then POST to `/rest/credentials` with type `kafka`, `ssl: true`, the CA in the
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`ca` field, `saslMechanism: scram-sha-512`, brokers
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`kafka-kafka-bootstrap.kafka.svc.cluster.local:9093`. The workflow's
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`credentials.kafka.id` then needs the new id.
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The KafkaUser itself lives in `infra-kafka/kafka-users.yaml`.
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