zeekay
1b367e2b62
The tree was a debranded snapshot of upstream taken around 2026-02-20, and upstream has moved about five months since. This replaces it with upstream master, mechanically re-derived: bin/debrand does the rename, and the pipeline and squashed migrations are restored from the shipped tree. Not a merge. The previous import replaced the tree wholesale in a single commit, so there is no shared content history to merge against. Reproducing the rename on the new tree is what actually converges. What survives: .hanzo/workflows, the Dockerfiles and bin/docker* entrypoints, compose files, LLM.md, and insights/migrations. The squashed initial migration is load-bearing — the live database records it by name, so upstream's ~918 individual migrations cannot come back. Nine products are dropped as unreferenced. Twenty-one more that we do not run are kept anyway because the core app still imports them; unpicking those is a refactor and does not belong in a rebase. This base does not build yet, and the reasons are not in the rename: upstream now wants Python 3.13.13 against our 3.12.12 and Django 5.2 against our 4.2, and the dependency manifests still name upstream packages that we republish under our own names. Those are decisions, not renames.
2.1 KiB
Return a scalar count of log entries matching a filter set. Use this as a cheap pre-flight before query-logs — if the count exceeds query-logs's max limit of 1000, narrow the filters before pulling rows.
All parameters must be nested inside a query object.
When to use
- Before
query-logs, to confirm the filter set returns a tractable number of rows. If the count is abovequery-logs's maxlimitof 1000, narrow the filters. - When the user asks "how many X logs are there?" and you don't need to see individual rows.
- To check whether a filter combination matches anything at all before committing to a full query.
To find when the volume is concentrated within the window (rather than just the total), follow up with logs-count-ranges — it returns time-bucketed counts with explicit date_from/date_to per bucket so you can drill into a sub-range without reasoning about interval width.
Parameters
query.dateRange
Date range for the count. Defaults to the last hour (-1h).
date_from: Start of the range. Accepts ISO 8601 timestamps or relative formats:-1h,-6h,-1d,-7d.date_to: End of the range. Same format. Omit or null for "now".
query.serviceNames
Filter by service names. Unlike query-logs, this tool does NOT require serviceNames — an unfiltered count is cheap and often useful for sizing up a filter before narrowing.
query.severityLevels
Filter by log severity: trace, debug, info, warn, error, fatal. Omit to include all levels.
query.searchTerm
Full-text search across log bodies.
query.filterGroup
Property filters to narrow results. Same format as query-logs filters.
Examples
Count errors in a service over the last day
{
"query": {
"serviceNames": ["api-gateway"],
"severityLevels": ["error", "fatal"],
"dateRange": { "date_from": "-1d" }
}
}
Confirm a k8s namespace is producing logs at all
{
"query": {
"dateRange": { "date_from": "-1h" },
"filterGroup": [
{ "key": "k8s.namespace.name", "operator": "exact", "type": "log_resource_attribute", "value": "payments" }
]
}
}