📦 deps(thirdparty): update snapshots
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# Operating Modes
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This playbook expands the compact mode routing in `SKILL.md`.
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## Scaffold
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Use when:
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- the skill is exploratory
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- the workflow is personal or short-lived
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- eval and packaging cost would exceed reuse value
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Default deliverables:
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- `SKILL.md`
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- `agents/interface.yaml`
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- `references/` only when a small amount of deferred reading is clearly helpful
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Avoid:
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- automatic `scripts/`, `evals/`, or `manifest.json`
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- packaging targets the user did not ask for
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## Production
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Use when:
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- the skill will be reused by a team
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- routing mistakes would waste time
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- a small amount of deterministic automation improves reliability
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Default deliverables:
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- lean `SKILL.md`
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- `agents/interface.yaml`
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- `references/` for policies, checklists, or examples
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- `scripts/` only when deterministic logic is real
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- `evals/` when trigger or output quality should be checked
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- `manifest.json` when lifecycle metadata matters
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Minimum gates:
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- `resource_boundary_check.py`
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- `validate_skill.py`
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- `trigger_eval.py` when route confusion is plausible
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## Library
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Use when:
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- the skill is organizationally important
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- the package will be shared broadly
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- maintenance and portability matter
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- the skill itself shapes how other skills are created or governed
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Default deliverables:
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- trigger positives, negatives, and near neighbors
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- packaging expectations
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- maintenance metadata
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- visible regression evidence
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- governance review readiness
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Minimum gates:
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- `resource_boundary_check.py`
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- `governance_check.py`
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- `trigger_eval.py`
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- `cross_packager.py` for requested targets
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## Governed
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Use when:
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- the skill affects incident, release, compliance, security, or organizational standards
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- external distribution, public claims, or high-permission scripts require reviewable evidence
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- wrong output or wrong activation can cause operational, legal, trust, or reputational harm
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Default deliverables:
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- everything required for Library
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- explicit owner, lifecycle, review cadence, and expiry-aware approvals
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- trust/security reports for scripts, dependencies, permissions, secrets, and package hash
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- output eval evidence with blind review status and reviewer-visible boundaries
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- world-class or public-claim evidence ledger when public readiness is claimed
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Minimum gates:
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- Library gates
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- `trust_check.py`
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- runtime permission probes for packaged adapters
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- review waiver ledger for accepted warning-level risk
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- Review Studio before release
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- claim guard before public world-class language
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## Escalation Rules
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- stay in Scaffold unless reuse is clearly real
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- move to Production when team reuse or route confusion matters
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- move to Library when the skill becomes shared infrastructure
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- move to Governed when the skill needs explicit risk ownership, high-permission review, or public-claim evidence
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## Context Discipline
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- a mode upgrade does not justify a larger `SKILL.md`
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- higher rigor should mostly add better references, reports, evals, and metadata
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- if a mode upgrade bloats the initial load, move detail out before adding more checks
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