agentleFS
mandarzopemandarzope/fullstack-swarm/skills/next/SKILL.md

next

Skill4 starsChanged 4 months agoMITView on GitHub

Run the pipeline autonomously: repeatedly apply CLAUDE.md dispatch rules (track-aware, including UX design and visual QA stages), dispatch eligible stories in parallel (cap 7), update _queue.json after each batch, and keep going until BLOCKED, full completion, or no dispatchable work. Use when the user types /next, or says "advance the pipeline", "run the swarm", "autonomous pipeline", or wants all ready stages drained without repeated /next.

40 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use quick, project and 8 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • codebycoreySkill

    quick

    Quick start a change with minimal interaction. Use when fast-tracking a straightforward change that needs proposal, design, and tasks in one step.

    Also in 3 projects that use this

  • BugRogerSkill

    project

    Project lifecycle management. Dispatches to Ada.

    Also in 3 projects that use this

  • MicrosoftSkill

    cleanup

    Also in 4 projects that use this

  • ArvorCoSkill

    clarify

    Identify and resolve ambiguities in feature specifications. Use when spec has unclear requirements. Triggers on: clarify spec, resolve ambiguities, clarify requirements.

    Also in 3 projects that use this

  • genomewalkerSkill

    explore

    RLM-style recursive memory exploration - dynamically navigate the memory graph

    Also in 3 projects that use this

  • GoogleSkill

    critique

    Expertise in auditing and fixing repository scripts and GitHub Actions workflows to ensure technical robustness and security.

    Also in 3 projects that use this

The file

Show its rules and text

We split this skill into the rules it gives an agent

13 rules. 0 are common, 5 are distinctive, and 8 are very specific to this project.

  • 0

    Common

    Most of the 36 edited versions we read keep these.

  • 5

    Distinctive

    This author's own choices. Worth a look.

  • 8

    Very specific

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

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

    Read CLAUDE.md and stories/_queue.json.

    line 13
  2. Very specific:

    If any story is BLOCKED -> tell the human, summarize queue, exit the loop (do not dispatch).

    line 25
  3. Very specific:

    Only consider stories whose deps are all DONE.

    line 33
  4. Very specific:

    Use the first rule that matches at least one eligible story.

    line 34
  5. Distinctive:

    If no story matches rules 3–10:

    line 39
  6. Very specific:

    If every story is DONE -> short success summary, exit.

    line 41
  7. Very specific:

    If prd/current.md exists and the queue has no stories (empty array) -> dispatch project-manager once (same prompt as /ship-prd), parse …

    line 42
  8. Distinctive:

    If the batch has multiple slugs mapping to the same subagent role (after track routing), dispatch them in parallel with concurrent Task …

    line 49
  9. Very specific:

    When the batch finishes, parse every returned <status> block.

    line 68
  10. Very specific:

    Immediately: start the next iteration at step 1.

    line 73
  11. Distinctive:

    No eligible batch and not the "empty queue + PRD present" special case

    line 80
  12. Distinctive:

    No-progress guard: if an iteration performed no successful dispatch and the queue is unchanged, exit and explain — avoids infinite loops

    line 81
  13. Distinctive:

    Keep a short running log of batches dispatched so the final user summary lists what ran and ends with the queue snapshot.

    line 84

“Common” is measured: kept by at least 6 in 10 of the 36 edited versions of this file we could read. “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

Read CLAUDE.md and stories/_queue.json.

Autonomous loop

Repeat one iteration until a stop condition fires:

1. Reload state

Re-read stories/_queue.json (and CLAUDE.md if needed) so each iteration uses fresh statuses.

2. Hard stop: BLOCKED

If any story is BLOCKED -> tell the human, summarize queue, exit the loop (do not dispatch).

3. Choose the next batch (priority order)

Apply dispatch rules 3–10 from CLAUDE.md, in order: FAILING_VISUAL_QA -> FAILING_QA -> READY_FOR_VISUAL_QA -> READY_FOR_QA -> READY_FOR_BUILD -> READY_FOR_UX_DESIGN -> READY_FOR_LLD -> READY_FOR_ARCH.

Only consider stories whose deps are all DONE. Never dispatch a story with unmet deps. Use the first rule that matches at least one eligible story; collect all stories matching that rule (with met deps) as one batch. Route by track per CLAUDE.md's track routing table (e.g. READY_FOR_BUILD dispatches developer for track=backend and frontend-developer for track=ui/fullstack).

If no story matches rules 3–10:

  • If every story is DONE -> short success summary, exit.
  • If prd/current.md exists and the queue has no stories (empty array) -> dispatch project-manager once (same prompt as /ship-prd), parse <status>, update _queue.json, then continue the loop.
  • Otherwise -> report queue state (e.g. DRAFT, waiting on deps, or stuck), exit — do not spin.

4. Parallel dispatch

If the batch has multiple slugs mapping to the same subagent role (after track routing), dispatch them in parallel with concurrent Task tool calls (cap 7 per iteration). If the batch is a single story, one Task is enough.

Maker ≠ checker: qa-engineer and visual-qa must always be fresh Task dispatches — never grade in the implementer's context.

Include in every subagent prompt:

  • slug, track, absolute paths to inputs, expected outputs, target next_status on success
  • prior QA/visual-QA report path when re-dispatching on FAILING_QA/FAILING_VISUAL_QA
  • Identity reinjection: one line with the role's role_id, identity_marker, and non_negotiables from that agent's Identity block
  • Effort / model: set Task model from CLAUDE.md effort routing (xhigh for project-manager / solution-architect / tech-lead / qa-engineer / visual-qa; high for ux-designer / developer / frontend-developer)

5. Apply results

When the batch finishes, parse every returned <status> block; for each story append a history entry and set status to next_status.

6. Continue

Immediately start the next iteration at step 1. Do not stop after one batch to wait for another /next unless a stop condition fired.

Stop conditions (summary)

  • Any BLOCKED
  • All stories DONE
  • No eligible batch and not the "empty queue + PRD present" special case
  • No-progress guard: if an iteration performed no successful dispatch and the queue is unchanged, exit and explain — avoids infinite loops

Keep a short running log of batches dispatched so the final user summary lists what ran and ends with the queue snapshot.

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.