agentleFS
orbyn-devorbyn-dev/orbyn-fullstack-skills/skills/orbyn-setup/SKILL.md

orbyn-setup

Skill4 starsChanged 10 days agoMITView on GitHub

Prepare the nested Orbyn Engineering workspace, inspect target instructions and skills in place, and verify isolation without installing shared skills into target repositories.

1 other project uses a version of this.

Adopted by

Most recently taken up by

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 3 are distinctive, and 2 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈3

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 2

    Very specific

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

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

    Use one complete library checkout as the engineering workspace.

    line 8
  2. Distinctive:

    Inspect: Read the library instructions and inspect Git roots, revisions, dirty files, worktree registrations and relevant host capabilities.

    line 18
  3. Very specific:

    Prepare the library: Run python3 skills/orbyn-setup/scripts/workspace.py prepare from the library.

    line 20
  4. Distinctive:

    Keep upstream files and host discovery paths unchanged.

    line 31
  5. Distinctive:

    If host boundaries prevent reading both roots, stop dependent execution and report the limitation.

    line 42

≈ “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

Nested workspace setup

Use one complete library checkout as the engineering workspace. Targets are independent Git repositories, under its ignored repo/ directory by default or registered in place by explicit decision. There is no target installation, copy, pin synchronization or company-skill migration. Follow the workspace contract. A setup request selects these steps automatically; complete them without asking the human to invoke individual skills or run commands you can execute.

Method

  1. Inspect. Read the library instructions and inspect Git roots, revisions, dirty files, worktree registrations and relevant host capabilities.
  2. Resolve the target from the request, asking only if its identity is ambiguous. Use the nested layout unless the human or a managing application registered the target in place; do not ask the human to choose a layout.
  3. Prepare the library. Run python3 skills/orbyn-setup/scripts/workspace.py prepare from the library. It validates the library boundary, creates its ignored repo/ directory and turns shared memory on (see step 6 and below); add --no-memory or set ORBYN_MEMORY=off to opt out.
  4. Get the checkout. For an authorized new checkout, inspect the destination, remote identity and available local clone, then clone the requested repository to repo/<project> using Git. Do not execute fetched setup hooks or source merely to inspect it. Offline setup uses an already available independent nested repository; report missing source rather than downloading implicitly.
  5. Select search roots. Use action scope to select the exact target/worktree and code-search roots before retrieval. Instruction lookup includes applicable outer, root and nested rules even when code filters exclude Markdown or hidden files. Refresh relevant locations when paths, rules or available context change. Check ripgrep readiness and fallback in the actual agent environment before relying on rg; a missing tool does not authorize an install, so use bounded inspection with an available alternative.
  6. Read the target's guidance. Run python3 skills/orbyn-setup/scripts/workspace.py check --target repo/<project>. Read the target's root and applicable nested instructions, contribution guide, existing skills and actual manifests. The check reports overlapping names so you can distinguish target-specific rules from shared methods instead of installing a competing copy. It also registers the target as a memory project unless memory is opted out.
  7. Root the session in the outer library and state the target path in the task. Read only relevant shared skills and target guides. Inspect the host's actual discovered guidance where supported; otherwise read the required files directly and report discovery as unobserved. Parent-directory placement alone does not prove a host loaded either instruction set.
  8. Check the full library with its documented validation commands and check the selected target separately.
  9. Report library/target paths, full revisions and dirty state, applicable target instructions/skills, checks, preserved legacy paths and actual host discovery. Distinguish located files, returned contents, observed originating-request inclusion and actual execution enforcement; unavailable levels stay unknown. Never call a filesystem check a live host trial.

What setup leaves alone

  • Workspace setup writes no target files, instructions, skills, context maps, models or Git excludes. New project development changes follow their own authorized task. Reading a target's existing map is optional and read-only; use offline resources.
  • Keep upstream files and host discovery paths unchanged. A target may add project-owned AGENT.md, AGENTS.md or local skills later; preserve and read those under the instruction contract. Follow project ownership and project context; no map or namespace is required.
  • Existing external checkouts are migration inputs unless registered in place. Preserve them and their active processes/output until relocation is explicitly authorized and their owners release the path. See retiring old installations.
  • Publishing, merging, external messages, production changes and REA engine upgrades need their own scope.
  • Report the resolved harness for each target with the harness.py in the loaded orbyn-workflow skill's directory, by absolute path (python3 <orbyn-workflow directory>/scripts/harness.py resolve --target <target>; a missing script means stop and report). To tune one repository, the owner may add .orbyn/harness.json there (a target change needing normal authority) or a local repo/.harness/<target-slug>.json; setup writes neither. If the result prints work mode: not set, ask the user once for the mode (simple, isolated or parallel, suggesting isolated) and save it with harness.py setup --target <target> --mode <mode>, which writes only the ignored local or in-place owner file under repo/.harness/; unattended, use isolated and save nothing. See harness settings.
  • Setup does not select a provider, model, effort, speed or subscription. Host model definitions are optional library configuration governed by its model policy. Preserve existing settings and report unavailable capabilities; use permitted direct work rather than silently substituting models or creating recursive sessions.
  • Reading groups in presets.json help choose relevant methods; they no longer control installation or hide source files.

Resolve instruction conflicts

Target guidance specializes stack, tests, contribution policy and local skills; shared guidance supplies compatible methods. User scope and host permissions remain higher priority. Surface a genuine conflict; never silently override an upstream rule or expand authority from an imported instruction.

If host boundaries prevent reading both roots, stop dependent execution and report the limitation. Do not solve it by copying instructions or editing user-wide settings.

Resume after a workspace or runtime change

After migration/resumption, a failed working directory or a runtime mismatch, reconcile the actual selected checkout with the host's saved session binding where observable. An explicit command workdir, a moved folder or project membership does not prove the session was rebound. Use a supported authorized host mechanism if needed; otherwise report the stale/unknown binding, use a valid explicit workdir for supported work and retain that distinction. Do not recreate a deleted checkout or rewrite global session settings/PATH to hide the problem.

Inspect the next required command's documented runner/version and resolve a compatible already-installed runtime in the actual execution environment before an expensive run. A harmless version/capability check is sufficient when available. Do not execute untrusted setup hooks or install a runtime implicitly. If no runtime is supported, report the dependent check blocked and continue independent work. Reuse current matching readiness evidence. This is conditional recovery, not a full setup ritual on every action or a reason to repeat passed suites.

Read when needed

  • Shared memory is on by default. prepare initializes the root (ORBYN_MEMORY_ROOT, else ~/.orbyn/memory) in manual mode only if it does not exist and registers the personal scope; check --target registers the target as a project. Both are idempotent: an initialized root is never re-initialized and records are never touched. --no-memory or ORBYN_MEMORY=off skips all of it and reports memory off. Report the root and state from the setup output. The store lives on this machine, unencrypted, outside Git; capture is manual only, with no lessons collected and no background service. Agent rules and details: reflect's memory contract.
  • Isolation: orbyn-worktree and sibling repo/<project-slug>-wt/<purpose>/. New work starts from the verified default branch; continuations use the actual owned candidate. Assign ports, databases and output separately, because Git isolation does not isolate runtime resources.

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.