agentleFS
npownpow/claude-skills/team/SKILL.md

team-temporal

Skill4 starsChanged 6 months agoApache-2.0View on GitHub

Use when coordinating multiple agents on a staged pipeline — plan → PRD → exec → verify → fix — via a durable Temporal-backed workflow that survives session crashes. Trigger phrases include "team temporal", "sagaflow team", "durable team", "temporal-backed agent team". File-based state, independent critic/verifier gates, two-stage review on every source modification, honest termination labels. Fire-and-forget while you do other work.

The file

Files
SKILL.md

team-temporal (deprecation shim)

This skill has been absorbed into autopilot (staged topology). See autopilot's ## Execution routing section for the sagaflow launch recipe.

The -temporal directory is preserved because sagaflow's worker discovers skill packages by directory name (see _DIR_TO_LEGACY in sagaflow/worker.py). Do not rename or move __init__.py, workflow.py, state.py, or prompts/ in this directory without a coordinated worker-restart + code update.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.