playbook/antigravity-awesome-skills/skills/yao-meta-skill/references/operating-modes.md

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Operating Modes

This playbook expands the compact mode routing in SKILL.md.

Scaffold

Use when:

  • the skill is exploratory
  • the workflow is personal or short-lived
  • eval and packaging cost would exceed reuse value

Default deliverables:

  • SKILL.md
  • agents/interface.yaml
  • references/ only when a small amount of deferred reading is clearly helpful

Avoid:

  • automatic scripts/, evals/, or manifest.json
  • packaging targets the user did not ask for

Production

Use when:

  • the skill will be reused by a team
  • routing mistakes would waste time
  • a small amount of deterministic automation improves reliability

Default deliverables:

  • lean SKILL.md
  • agents/interface.yaml
  • references/ for policies, checklists, or examples
  • scripts/ only when deterministic logic is real
  • evals/ when trigger or output quality should be checked
  • manifest.json when lifecycle metadata matters

Minimum gates:

  • resource_boundary_check.py
  • validate_skill.py
  • trigger_eval.py when route confusion is plausible

Library

Use when:

  • the skill is organizationally important
  • the package will be shared broadly
  • maintenance and portability matter
  • the skill itself shapes how other skills are created or governed

Default deliverables:

  • trigger positives, negatives, and near neighbors
  • packaging expectations
  • maintenance metadata
  • visible regression evidence
  • governance review readiness

Minimum gates:

  • resource_boundary_check.py
  • governance_check.py
  • trigger_eval.py
  • cross_packager.py for requested targets

Governed

Use when:

  • the skill affects incident, release, compliance, security, or organizational standards
  • external distribution, public claims, or high-permission scripts require reviewable evidence
  • wrong output or wrong activation can cause operational, legal, trust, or reputational harm

Default deliverables:

  • everything required for Library
  • explicit owner, lifecycle, review cadence, and expiry-aware approvals
  • trust/security reports for scripts, dependencies, permissions, secrets, and package hash
  • output eval evidence with blind review status and reviewer-visible boundaries
  • world-class or public-claim evidence ledger when public readiness is claimed

Minimum gates:

  • Library gates
  • trust_check.py
  • runtime permission probes for packaged adapters
  • review waiver ledger for accepted warning-level risk
  • Review Studio before release
  • claim guard before public world-class language

Escalation Rules

  • stay in Scaffold unless reuse is clearly real
  • move to Production when team reuse or route confusion matters
  • move to Library when the skill becomes shared infrastructure
  • move to Governed when the skill needs explicit risk ownership, high-permission review, or public-claim evidence

Context Discipline

  • a mode upgrade does not justify a larger SKILL.md
  • higher rigor should mostly add better references, reports, evals, and metadata
  • if a mode upgrade bloats the initial load, move detail out before adding more checks