# Case 01767

> workflow-runner

- Skill: `knownasnaffy/case-01767` (Agent Skill, multi-file: 9 files)
- Install (CLI): `npx skillmds@latest add knownasnaffy/case-01767`
- Raw SKILL.md: https://api.skillmd.com/api/skills/knownasnaffy/case-01767/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: knownasnaffy (https://skillmd.com/u/knownasnaffy)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/knownasnaffy/case-01767

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# workflow-runner

Purpose

- Automate a small dev workflow inside the platform: main agent parses requirements, creates two persistent subagents (coding + testing), coordinates work and retries until tests pass, then makes a local git commit and writes artifacts to results/.

When to use

- Use when you want an end-to-end implement+test loop for a small feature or task and want persistent worker sessions for iterative work.

Core behavior (summary)

1. Main agent parses the requirement and splits into a coding task and a testing task.
2. Spawn two persistent subagents (role=coding and role=testing) with isolated contexts (128k). Subagent sessions are kept for a configurable TTL (default 24h).
3. Coding subagent implements code, produces patches and a short report.
4. Testing subagent designs and runs tests; if tests fail it returns structured failures to main agent.
5. Main agent reroutes failures to the coding subagent and repeats until tests pass or max retries reached.
6. On success: produce results/<wf-id>/, create a local git commit (no push by default).

Configurable parameters

- default_ttl_days: 1
- max_retries: 10
- auto_git_commit: true (local only)
- results_path: ./results/

Bundled resources

- scripts/ — orchestrator and helper scripts
- examples/ — a minimal sample workflow for smoke tests

How to trigger

- Natural language like: "Run workflow: implement <short spec>"
- Or explicit: `run workflow-runner: <spec>`


Notes

- The skill favors local, auditable actions (commits are local). It logs all artifacts to results/ and keeps subagent sessions available for reuse.