durable agent runtime

# Zeta

Author agents as files. Run them as durable events. Inspect every model call, tool result, queue claim, and prompt boundary.

Deploy an agent Inspect the runtime
01 authored specs become explicit event routes
02 queues, leases, and locks are durable tables
03 prompt provenance is replayable by construction
agents/ valid
release-manager.md
support-triage.md
skills/
code-review.md
release-notes.md
events/
github.pr.opened.json
release.ready.json
tools/
read.py
grep.py
github.pr.opened

accepted by release-manager, projected into one queue item

runtime.attempt.running

lease token fenced, heartbeat active, locks acquired

release.ready

returned event is schema-checked before it composes

zeta run --forever live
$ zeta run --project-root .
accepted github.pr.opened
queued qi_evt_421_release-manager
claimed worker=local-runtime
lock repo:release acquired
model local-model streamed 822 tokens
tool grep returned 12 grounded lines
completed att_qi_evt_421_1
emitted release.ready
queueavailable
attemptcompleted
tracereplayable
schemavalid
runtime

## Agents that behave like software.

Zeta treats every transition as a durable boundary: incoming events, queue lifecycle, model calls, tool results, prompt components, and returned events all land in an inspectable log.

01 / authored

### An agent is a contract.

Frontmatter declares what an agent accepts, what it may return, which tools it can reach, and whether it can resume state.

02 / durable

### The queue is visible.

Claim tokens, attempt rows, locks, heartbeats, and terminal writes are explicit runtime facts instead of hidden control flow.

03 / bounded

### Capabilities stay fenced.

Tools are registered as contracts. Staged effects remain inspectable before they touch the outside world.

trace graph

## Prompt provenance without folklore.

Every answer can be traced back to its prompt components, tool calls, model output, and durable event chain.

Replay the prompt.

Reconstruct the exact model request from stored components, selected tools, token budgets, and current timeline.

Diff the answer.

Compare two runs by prompt object, tool result, model output, and returned event instead of guessing from logs.

Trust the boundary.

Durable event schemas make runtime behavior inspectable before agents compose into larger systems.

authoring

## Markdown for policy. Events for motion.

Zeta keeps the agent surface small: a Markdown file, explicit event schemas, reusable skills, and a runtime that records what happened.

    ---
    name: Release Manager
    description: Prepare release summaries.
    accepts:
      - github.pr.opened
    returns:
      - release.ready
    tools:
      - read
      - grep
    skills:
      - code-review
    schedules:
      - cron: "0 9 * * 1"
        timezone: Europe/Paris
    resumable: true
    ---
    Review {{ event.payload.title }} and emit a release summary.

event schema
queue lease
prompt trace
result contract
No
Bad
Runs
start

## Ship the agent loop you can audit.

$ mkdir -p agents/events agents/skills
$ edit agents/release-manager.md
$ zeta events publish github.pr.opened --json payload.json
$ zeta run --forever