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PicsArt avatar

Enterprise Pinned Registry

PicsArt/gen-ai-skills
210 installs4 starsMIT
Summary

If you're running AI generation at enterprise scale and need to recreate the exact same output six months or three years later, this is your lockfile. It pins model versions, prompt templates, brand tokens, and seeds to a git-committed manifest so that legal holds, annual campaigns, and regulatory audits don't turn into archaeology. Picsart built this for multi-team deployments where 20+ people need identical output and model drift is a compliance risk, not just an inconvenience. The workflow is straightforward: designers use aliases like "flux" instead of raw version strings, you run a regression corpus before bumping, and everything traces back to a tagged registry version. Not for exploration or drafts, but if reproducibility is a requirement and not a nice-to-have, this is the right shape.

Install to Claude Code

npx -y skills add PicsArt/gen-ai-skills --skill enterprise-pinned-registry --agent claude-code

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Files
SKILL.mdView on GitHub

Enterprise Pinned Registry

A lockfile concept for AI generation. Model versions, prompts, brand tokens, and seeds are pinned to a manifest that regenerates the same campaign identically six months, a year, or three years later. Built for enterprises that need reproducibility for legal holds, brand-campaign continuity, regulatory defense, and year-over-year comparability.


When to Use

  • Multi-team deployment: 20+ designers / PMs / agencies generating on the same brand, need identical output across all of them
  • Year-over-year campaign (annual report, quarterly earnings graphics) must match the prior year's look exactly
  • Regulated industry where "reproducible" is a compliance requirement, not a preference
  • Legal hold — a specific asset may need to be regenerated identically for litigation support
  • Model-provider change management — new versions ship weekly; you want explicit, reviewed upgrades, not drift
  • Audit trail: every shipped asset must trace back to a specific model version + prompt + brand token set

Do not use for: one-off exploration, draft/ideation phases, consumer projects.


Prerequisites

Before authoring the registry:

  1. Scope — which models, prompts, and brand tokens are in scope? Start narrow (heroes only) then expand.
  2. Bump cadence — quarterly? On-demand only? Who approves a bump?
  3. Regression-test corpus — what's the set of prompts that must be re-run before a bump is approved? (Typically 10–20 representative prompts.)
  4. Storage — registry in the campaign repo, a dedicated brand-registry repo, or a central governance repo?
  5. Rollback plan — if a bump produces unacceptable drift, how do we revert? (Git revert is usually enough if the registry is in git.)
  6. Audit retention — how long must the registry + generated outputs be retained? 7 years for SOX-adjacent, 10 for pharma, indefinite for trademark defense.

How to Run

Five steps. The registry is the contract; everything generates against it.

  1. Author registry.json — model aliases, prompt templates, brand tokens, default params. Each alias pins to an explicit model@version.
  2. Fingerprint prompts — every prompt template gets a SHA256 hash stored alongside it. If the prompt string changes, the fingerprint changes, and that's a versioned bump.
  3. Configure the CLI — gen-ai config set registry <path> points every call on this machine at the registry. Teams commit the registry to git and sync via clone/pull.
  4. Generate against aliases — designers use flux (alias), never flux-2-pro@2.1.3 (raw). Alias resolution is the registry's job.
  5. Bump quarterly — run the regression corpus against a candidate new version, diff the outputs, get approval, bump the registry, tag the release (brand-registry-v2026.2).

Quick Reference

The registry itself is the manifest. Commit it. Tag it. Diff it on every bump.

{
  "registry_version": "2026.2.0",
  "locked_at": "2026-04-01T00:00:00Z",
  "locked_by": "brand-governance@company.com",
  "previous_version": "2026.1.0",
  "regression_run_id": "REG-2026Q2-APPROVED",
  "models": {
    "flux":     { "id": "flux-2-pro@2.1.3",          "commercial_use": true,  "notes": "Hero, editorial" },
    "kontext":  { "id": "flux-kontext-pro@1.4.0",    "commercial_use": true,  "notes": "Product edit-mode" },
    "upscale":  { "id": "topaz-upscale-image@2.0.0", "commercial_use": true,  "notes": "Print prep" },
    "kling":    { "id": "kling-v3-pro@3.0.1",       "commercial_use": true,  "notes": "I2V broadcast" },
    "portrait": { "id": "gemini-3-pro-image@1.2.0",  "commercial_use": true,  "notes": "Portrait, verify license" }
  },
  "prompt_templates": {
    "hero_launch": {
      "text": "Editorial hero, {subject}, {environment}, brand palette, natural light",
      "fingerprint": "sha256:7b4f2a...c8e1"
    }
  },
  "brand_tokens": {
    "palette": { "primary": "#FF006E", "ink": "#0D0A1F", "accent": "#FFBE0B" },
    "aspect_ratios_allowed": ["16:9", "9:16", "1:1", "3:2"],
    "seed_default": 42
  },
  "audit_id": "REGISTRY-2026.2"
}

Every generated asset's results.json entry should carry registry_version so reproduction is one command away.


Quick Reference

The registry pins them; it doesn't choose them. For picking, see the per-workflow skills. Typical enterprise registry contents:

AliasPins toRole
fluxflux-2-pro@x.yPrimary photoreal hero
kontextflux-kontext-pro@x.yEdit-mode, product-accuracy preserve
portraitgemini-3-pro-image@x.yFaces, commercial-safe (verify license)
upscaletopaz-upscale-image@x.yPrint / wire prep
remove-bgpicsart-remove-bg@x.yTransparent PNG derivatives
change-bgpicsart-change-bg@x.yCatalog background replace
klingkling-v3-pro@x.yImage-to-video for broadcast

Confirm commercial-use + regional availability at bump time with gen-ai models info <id>. Provider terms change; pin is not a license.


Procedure

  • Aliases everywhere, raw IDs nowhere. Designers should never see flux-2-pro@2.1.3 in a prompt — only flux.
  • The registry lives in git. Commit, tag, diff, review, revert. Full audit trail for free.
  • Regression corpus before every bump. 10–20 canonical prompts, run against old and new, visual diff approved by brand lead.
  • Pin seeds for reproducibility where the model supports it. --seed 42 reruns the same output deterministically.
  • Fingerprint prompt templates. Any string change to a template is a versioned bump, not a silent edit.
  • Tag registry versions semver-like (2026.2.0 = year-quarter-patch). Patch for typo fixes; minor for new aliases; major for model swaps.
  • Deprecate, don't delete. Removing an alias breaks historical reruns. Mark as deprecated, keep the pin, flag in CLI output.
  • Document the bump. Every version bump ships with a changelog: which model, why, regression results, approver.
  • Re-run a prior campaign from its registry version quarterly to verify reproducibility still works. If it breaks, the provider deprecated the version — plan migration.

Pitfalls

  • Aliases + raw IDs mixed in manifests — teams drift off the registry unintentionally. Lint for raw IDs in PRs.
  • No regression corpus — bumps ship, drift is invisible until a comms leader notices a year later.
  • Provider deprecates a pinned version — eventually happens. Run your registry's prior versions quarterly to catch this before a legal reroll is needed.
  • Prompt edits without fingerprint bump — someone "fixes a typo" in a template, now the output differs. Fingerprint + bump.
  • Seed not pinned — reproducibility is partial without it. Set a registry default seed.
  • Registry in a personal repo — loses institutional access. Must live in a governance-owned repo.

Verification

Run gen-ai whoami to confirm authentication, then re-run the failed command with --debug.

Commands

# Point the CLI at the registry
gen-ai config set registry.path ./brand-registry/registry.json

# Pin a model alias
gen-ai config set registry.flux flux-2-pro@2.1.3
gen-ai config set registry.kontext flux-kontext-pro@1.4.0
gen-ai config set registry.kling kling-v3-pro@3.0.1
gen-ai config set registry.upscale topaz-upscale-image@2.0.0

# Verify a given alias resolves to the pinned version
gen-ai config get registry.flux
# → flux-2-pro@2.1.3

# Generate using the alias (reproducible)
gen-ai generate --model flux --prompt-file prompts/hero-launch.txt \
  --seed 42

# Batch resolves all aliases against the registry
gen-ai batch run campaign.json

Every manifest references aliases, never raw model IDs. The registry is the one place that maps alias → version.


Cost & time

Registry operations are cheap. The value is in what they prevent.

ActivityCostTime
Author initial registry01 engineer-day
Quarterly regression corpus (20 prompts)~200 credits~1 h generation + ~2 h review
Version bump + tag0~30 min
Reproduce a 1-year-old campaignSame credits as originalSame wall time
Provider-deprecation migration~500 credits1–2 engineer-days

Cost savings scale with team size: a 20-person design team bumping incidentally costs far more in drift than one quarterly reviewed bump.


See also

  • enterprise-brand-governor — brand.md gating; pairs with the registry for full policy-as-code
  • product-photo-studio — batch catalog runs (reshoot mode); use registry aliases
  • enterprise-press-batch — embargo-aware pipeline, pin for year-over-year consistency
  • gen-ai-use — CLI reference
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Categories
AI & Agent Building
First SeenJul 6, 2026
View on GitHub

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