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docs: define Maya E2E consumer contract - #12

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docs/maya-e2e-consumer-contract
Jul 29, 2026
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docs: define Maya E2E consumer contract#12
BramVR merged 1 commit into
mainfrom
docs/maya-e2e-consumer-contract

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@BramVR

@BramVR BramVR commented Jul 29, 2026

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Summary

  • define the consuming-repository contract for the Maya plug-in E2E skill
  • keep deterministic scenarios in product repositories
  • keep private host and trust configuration operator-owned

Copilot AI review requested due to automatic review settings July 29, 2026 13:01
@BramVR
BramVR merged commit ae4aad5 into main Jul 29, 2026
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BramVR deleted the docs/maya-e2e-consumer-contract branch July 29, 2026 13:02

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Pull request overview

Defines a clear “consuming repo contract” for using the maya-plugin-e2e skill, separating deterministic scenario/test inputs (kept in product repos) from operator-owned/private host and trust configuration (kept outside repos).

Changes:

  • Add a “Consuming Repo Contract” section describing what each consuming repository must own (scenario YAML, scripts, docs, routing).
  • Document guidance to keep host/trust configuration outside the consuming repo.
Comments suppressed due to low confidence (1)

skills/maya-plugin-e2e/SKILL.md:38

  • This section introduces “Host Config” (title case) and a hard requirement on MAYA_STALL_HOST_CONFIG, but elsewhere the skill uses “host config” and the --host-config flag. To avoid confusion, keep casing consistent and document selection in a way that matches the commands shown (with env var usage as an optional setup detail).
Keep Host Config outside the repo. Prefer a stable operator-owned path such as
`~/.config/maya-stall/hosts.yaml`, selected through `MAYA_STALL_HOST_CONFIG`.
The skill owns the workflow; the consuming repo owns product assertions; the
host config owns private infrastructure and trust policy.

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Comment on lines +27 to +30
- `.maya-stall.yaml` with named Scenario, `pluginArtifacts`, Maya scripts,
expected outputs, Visual Evidence, and Validators;
- a checked-in Maya script that drives real product controls and writes the
Scenario Result;
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2 participants