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GoogleKnown publishergoogle/lightflow/skills/run_lightflows/SKILL.md

run_lightflows

Skill14 starsChanged 27 days agoApache-2.0View on GitHub

Executes, inspects, and resumes existing Lightflow DAG workflows via CLI (`lightflow`, or the equivalent `python3 -m lightflow`). Use when asked to run, dry-run, check status, visualize, resolve an `operator_action` human-in-the-loop checkpoint (`EXIT_CODE=2`), or recover a failed Lightflow run without authoring a new workflow. Run `start` directly without pre-reading the manifest or `actions.py`.

The file

We split this skill into the rules it gives an agent

3 rules. About 0 are common, 0 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈0

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Read only SKILL.md, then run start directly: do not read lightflow.yaml, actions.py, or README.md first.

    line 12
  2. Very specific:

    Skip redundant status calls & chain cleanup: when start or resume exits 0 (Lightflow completed successfully!), do not run status.

    line 17
  3. Very specific:

    2 SUSPENDED at an operator_action: follow the printed Instructions, then resume with a payload matching the Payload Schema.

    line 49

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Running & Resuming Lightflow Workflows (run_lightflows)

Authoring new workflows? Read create_lightflows instead.

Fast-Path Rules

  1. Read only SKILL.md, then run start directly: do not read lightflow.yaml, actions.py, or README.md first. The CLI compiles the manifest and prints any gate's Instructions, Payload Schema, and the exact Resume with: command. --lightflow=<path> accepts a manifest file or its directory.
  2. Skip redundant status calls & chain cleanup: when start or resume exits 0 (Lightflow completed successfully!), do not run status. If asked to clean up afterwards, chain start ... && cleanup ... (&& stops naturally at an EXIT_CODE=2 gate).

1. Commands

python3 -m lightflow is equivalent to lightflow when the console script is not on PATH. Runs remember their manifest, so status, resume, visualize, and cleanup need only --log_id; if the manifest file moved, pass --lightflow=<new path> once and it is re-recorded.

lightflow start --lightflow=<dir_or_manifest> --log_id=<run_id> [--payload='{...}' | --payload=@file.json]
lightflow start ... --dry_run      # only when asked to preview; ends with a Summary: line and a 💡 --payload seed hint

# Resolve a paused gate once its Instructions are satisfied (APPROVE sets approved=true itself)
lightflow resume --log_id=<id> --stage=<gate_stage> --resolution=APPROVE --payload='{...}'
lightflow resume --log_id=<id> --stage=<gate_stage> --resolution=REJECT --comment="..."   # runs rollback_action; dependents are blocked

# After fixing a failed stage: re-arms only failed stages, keeps completed work
lightflow resume --log_id=<id> [--payload='{...}']

lightflow status --log_id=<id>     # one line per stage + any paused gate's Instructions, Schema, resume command; --verbose adds payload + stamp log
lightflow list                     # every saved run: log ID, lightflow, state, last activity, manifest
lightflow visualize --log_id=<id> --output=/tmp/viz.html
lightflow cleanup --log_id=<id>    # deletes the run's state only; workflow artifacts on disk are untouched

2. Exit Codes & Governance

  • 0 COMPLETED: done; report the stage outputs printed to stdout.
  • 2 SUSPENDED at an operator_action: follow the printed Instructions, then resume with a payload matching the Payload Schema. --resolution=APPROVE validates --payload against the gate's json_schema; on a validation error the gate stays paused, so fix the payload and re-run (status reprints the schema in a new conversation).
  • 1 FAILED or REJECTED: the footer names the root cause and the exact resume command. Fix the cause, then resume — never start --force, which discards completed stages and is only for rerunning a completed run from scratch. A rejected gate (🛑) is terminal unless deliberately re-opened: resume --stage=<gate> --resolution=APPROVE --payload='{...}' decides again in one call; a bare resume --stage=<gate> only re-opens it.
  • status exits like the run: 0 completed · 1 failed, rejected, or interrupted · 2 paused · 3 no saved state · 4 running in another process (wait; don't resume) · 5 waiting: a polling_policy stage yielded before its condition was met, nothing is broken, resume once it holds. Use --verbose only when you need the payload, stamp log, or Mermaid diagram.

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