agentleFS
TeamHelix-AITeamHelix-AI/helix/skills/helix-start/SKILL.md

start

Skill1 starsChanged 2 months agoApache-2.0View on GitHub

Route a job to the right Helix surface, or to no surface at all, then launch it. Spark diverges on ideas, Canvas decides together, Loop builds against a ratified bar, Arena judges candidates at a one-way door, Swarm sweeps work too wide for one context, Stream watches autonomous work. Use when the user says "/helix-start", describes a job and asks which mode fits, asks "canvas or loop for this?", "how should we run this", or wants a session set up without naming a surface. Not for jobs already underway on a surface.

130 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use setup-engine, team-audio and 10 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.
  • CoralGameSkill

    setup-engine

    Configure the project's game engine and version. Pins the engine in CLAUDE.md, detects knowledge gaps, and populates engine reference docs via WebSearch when the version is beyond the LLM's training data.

    Also in 13 projects that use this

  • CoralGameSkill

    team-audio

    Orchestrate audio team: audio-director + sound-designer + technical-artist + gameplay-programmer for full audio pipeline from direction to implementation.

    Also in 13 projects that use this

  • lilangMaxSkill

    create-stories

    Break a single epic into implementable story files. Reads the epic, its GDD, governing ADRs, and control manifest. Each story embeds its GDD requirement TR-ID, ADR guidance, acceptance criteria, story type, and test evidence path. Run after /create-epics for each epic.

    Also in 11 projects that use this

  • lilangMaxSkill

    story-done

    End-of-story completion review. Reads the story file, verifies each acceptance criterion against the implementation, checks for GDD/ADR deviations, prompts code review, updates story status to Complete, and surfaces the next ready story from the sprint.

    Also in 11 projects that use this

  • +5 more from CoralGame
  • +3 more from lilangMax

The file

We split this skill into the rules it gives an agent

7 rules. 0 are common, 4 are distinctive, and 3 are very specific to this project.

  • 0

    Common

    Most of the 117 edited versions we read keep these.

  • 4

    Distinctive

    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:

    If HELIX_ORCHESTRATOR_RUN_ID or HELIX_SKILL_CREDENTIAL_FILE is set, this skill runs in Helix Console.

    line 10
  2. Very specific:

    Use the normal helix <surface> up, push, state, and wait commands.

    line 12
  3. Very specific:

    Do not start local servers or Fleet, open a browser, curl localhost, use --local, log in, or change profiles/projects.

    line 13
  4. Distinctive:

    Read the job description and commit.

    line 41
  5. Distinctive:

    If it holds at least one thing worth finding again — a decision and its reason, a finding that changed the approach, a constraint …

    line 84
  6. Distinctive:

    Do not offer it when the session was only a lookup, a one-line fix, a question answered from the code, or work with no decision in it.

    line 95
  7. Distinctive:

    If the user overrides your pick, the correction is signal: note in memory what kind of job it was and where they wanted it, so the next …

    line 102

“Common” is measured: kept by at least 6 in 10 of the 117 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

Helix Start

Orchestrator cloud context (check before setup)

If HELIX_ORCHESTRATOR_RUN_ID or HELIX_SKILL_CREDENTIAL_FILE is set, this skill runs in Helix Console. This section takes precedence over local setup and browser instructions below.

  • First call the plugin's bin/helix orchestrator-protocol (Windows: bin/helix.cmd orchestrator-protocol). It must print 1. Otherwise stop with an actionable request to update the Helix plugin/CLI; never run an older binary's setup commands.
  • Use the normal helix <surface> up, push, state, and wait commands. The CLI selects cloud transport and the assigned project automatically. Keep the same slug within this task.
  • Do not start local servers or Fleet, open a browser, curl localhost, use --local, log in, or change profiles/projects. Do not read or print the credential file. Do not remove the injected environment variables.
  • up returns the Console session URL. Use that URL wherever the local instructions request Board/Fleet links. Events go to Console; human responses and gate approvals still come from the person through the normal wait protocol.
  • On cloud or compatibility errors, report the error. Never fall back to local mode. Outside this context, follow the local behavior below unchanged.

The front door. The user describes a job; you pick the surface it deserves, say why in one sentence, and launch it. The suite is only as good as the routing into it, and the honest answer is sometimes "no surface at all".

The seven answers

PickWhenThe tell
sparkThe job is diverging: early ideation, naming storms, "what could this even be". Nothing is scoped yet and nothing should be ratifiedThe user wants to riff, not decide; producing options matters more than picking one
canvasThe job is shaping: requirements, design, naming, trade-offs, a review full of judgment callsThe user will make many decisions as the work unfolds
loopThe job is building to a bar: a deliverable whose definition of done can be written down and ratified, then iterated against by builders and critics"Done" is crisp; the user wants distance but control at the gates
arenaThe job is a one-way door: a shape every downstream thing inherits, where one attempt would lock in the wrong answer and revising later is expensiveSeveral structurally different answers are possible and you cannot tell which is right by arguing
swarmThe job is too wide for one context: a sweep, an audit, a survey across many independent partsThe work splits into slices that need nothing from each other, and you want findings rather than a build
streamThe job is long and autonomous: refactors, test marathons, migrations, incident watch. The user watches, steers with notes, holds the brakeThe user intends to walk away and check in
noneThe job is small: one file, one question, minutes of workOpening a surface would be ceremony. Do it in the terminal

Fleet is not an answer here. It is the overview of many sessions, not a way to run one. Archive is not one either; it records a session after the fact rather than running it. If the job is "write up / archive / snapshot what happened", skip routing and invoke helix-archive directly.

Infer first; ask only what the description doesn't say

Read the job description and commit. When the pick is clear, state it with its one-sentence why and launch. No interview. Ask only when the description genuinely underdetermines the pick, at most three questions, in a single round, drawn from the three axes that decide it:

  1. Who drives. Will this need your calls as we go, or mostly my work after an initial brief?
  2. Is there a bar. Can we write a crisp definition of done before starting?
  3. Will you stay. At the keyboard throughout, checking in occasionally, or back at the end?

Riffing with no decisions yet is spark; deciding together is canvas; a crisp bar to iterate against is loop; a one-way door with several possible shapes is arena; work too wide for one context is swarm; walking away is stream; minutes of work is none.

Arena and swarm both cost real money before they return anything, so both earn a fourth question when the pick is close: is this worth several agents at once? An arena over a settled shape, or a swarm over work one agent could read in a single pass, is an expensive way to reach the answer you already had.

Jobs that span phases

Shaping and building are often the same job. Recommend the sequence: spark to diverge if nothing is scoped, canvas to ratify the brief or the quality bar, then loop or stream to build against it. Launch only the first surface. The hand-off to the next one is that session's closing decision, not something scheduled here.

Launch

Invoke the chosen skill with the job as its topic: helix-spark, helix-canvas, helix-loop, helix-arena, helix-swarm, or helix-stream. Follow that skill's own rules from there, slug confirmation included; never guess a slug here. For none, just do the work; mention the routing only if the user asked about it.

When the answer was none: offer the archive at the end

A session that ran in the terminal leaves nothing behind but the transcript and the diff. When the work is done, look at what it produced. If it holds at least one thing worth finding again — a decision and its reason, a finding that changed the approach, a constraint discovered the hard way, an artifact someone else will need — ask, once, in one line:

Worth keeping? I can archive this session to Helix Archive — decisions, findings, artifacts — so it can be found later.

On yes, invoke helix-archive and follow its rules (it asks for a level, then curates). On no, or no answer, drop it; do not ask again in the same session.

Do not offer it when the session was only a lookup, a one-line fix, a question answered from the code, or work with no decision in it. An archive of nothing teaches the user to say no to the next one. The test is not how long the session ran but whether a future reader would open it: if you cannot name the one card that reader would want, there is nothing to offer.

If the user overrides your pick, the correction is signal: note in memory what kind of job it was and where they wanted it, so the next routing is better.

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.