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srekit task

Generate an investigation log — a structured artifact for tracking the hypothesis-and-evidence trail when you're hunting a tail-latency spike, a flaky test, or any open-ended SRE puzzle. Hidden alias: srekit sretask (kept for migration from gch sretask).

Synopsis

srekit task --title TITLE [flags]

Flags

Flag Required Description
--title yes Subject of the investigation; used in the H1 and the default filename
--path DIR no Directory to write into (default: current dir)

Plus the shared output flags: --out, --stdout, --force, --dry-run, --json.

Default filename

If you pass neither --out nor --stdout, srekit writes to <path>/investigation-<slug>.md (lowercased, slug-cleaned).

Examples

Quick scratch into stdout:

srekit task --title "Tail latency on api-gw" --stdout

Write into a specific directory:

srekit task --title "Tail latency on api-gw" --path ./tasks
# → ./tasks/investigation-tail-latency-on-api-gw.md

Pipe into jq to grab the generated UUID:

srekit task --title "Tail latency on api-gw" --json | jq -r '.id'

Template shape

task ships as a v1 YAML artifact (internal/tmpl/templates/task.yaml) — frontmatter (id, title, creation_date, tags), H1, meta_bullets, and the section list (Контекст / Context, Гипотеза / Hypothesis, Доказательства / Evidence, Выводы / Findings, Дальнейшие действия / Action items, Ссылки / References). The data passed in is {Meta: {ID, Title, Now string}}; template expressions inside the YAML reference .Meta.<Field>.

See also

  • Custom templates workflow — override the embedded artifact with your own task.yaml.
  • JSON output — pipe --json into other tools (per-section access via jq '.sections[] | select(.id=="…").body').