pixee system-status
PREREQUISITE: Read
../pixee-shared/SKILL.mdfor global flags, exit codes, and error handling. See../pixee-auth/SKILL.mdif authentication needs to be configured.
pixee system-status reports the health of the connected Pixee deployment itself, distinct from
any repository, scan, or finding: platform components, license state, and which AI models are
currently available for fix generation. Reach for it when a command that should work is failing
in a way that looks like a deployment problem rather than a request problem — an expired license
or an unavailable model can produce errors that otherwise look like ordinary API failures.
pixee system-status list
pixee system-status list
No flags beyond the global ones. Pagination is transparent — the CLI walks every page in one call.
Text output is tab-separated with columns type, name, status, description, id. The
type discriminator distinguishes platform components (version), license entries (license),
and AI model entries (ai-model) in a single flat listing. A healthy entry reports
status: "up". Use --output json (or --json) for the full HAL record per entry, which adds
type-specific fields not shown in text mode: version on version entries, expires_at and
features_enabled on license entries, and model (the underlying model identifier, distinct
from the human-readable name) on ai-model entries.
Examples
# Full status listing
pixee system-status list
# Machine-readable, filtered to entries that are not up
pixee system-status list --json | jq '.[] | select(.status != "up")'
# Check whether a specific AI model is currently available
pixee system-status list --json | jq '.[] | select(.type == "ai-model" and .model == "gpt-5.4-mini")'
Best practices
- Check
pixee system-status listbefore escalating an otherwise-unexplained failure across many repositories or scans — a single unhealthy component or expired license can present as scattered per-request errors. - Filter on
typeandstatusinjqrather than assuming a fixed row order; the set of reported components and models can grow between releases. - To key on the underlying AI model, filter
--jsonoutput on.model, not.name—nameis a human-readable label (e.g."Analysis Service - Fast Model") and does not contain the model identifier.