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adobe-deploy-integration

Deploy an Adobe-backed service or App Builder application with isolated environments, immutable artifacts, canaries, observability, and rollback

Install / Use

npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-deploy-integration

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

83/100

Category

Operations

Supported Platforms

Universal

Tags

Our assessment of adobe-deploy-integration

adobe-deploy-integration scores 83/100 on our quality scale, 390th of 526 Operations skills we index.

Its SKILL.md is 4.0 KB long, well organised into 13 sections and no code examples: a solid amount of guidance for an agent.

With 2,785 GitHub stars, it is one of the more widely adopted skills in the catalogue.

Substance
26/30
Structure
13/20
Description
15/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 5 days ago, so adobe-deploy-integration is actively maintained.
  • It is released under the MIT license, a permissive license that allows use, modification and commercial use with attribution.
  • Its trust signals score 100/100, with no cautions. These come from repository metadata, not a code audit — read the skill file before letting an agent act on it.

adobe-deploy-integration compared with similar skills

All 4 of these similar skills score higher than adobe-deploy-integration; compare them before choosing.

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Frequently asked questions

How do I install adobe-deploy-integration?
Run npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-deploy-integration. The install tabs above show the steps for each supported agent.
Which AI agents does adobe-deploy-integration work with?
It is written for Universal, as a SKILL.md file. Other agents that read the same format can often use it too.
Is adobe-deploy-integration safe to use?
It is MIT-licensed and scores 100/100 on trust signals. Skills are instructions an agent will follow, so read the file before installing it and do not approve commands you do not understand.
Is adobe-deploy-integration still maintained?
The repository was last updated 5 days ago, so adobe-deploy-integration is actively maintained.

name: adobe-deploy-integration description: >- Deploy an Adobe-backed service or App Builder application with isolated environments, immutable artifacts, canaries, observability, and rollback. Use when the task requires adobe integration deployment. Trigger with "deploy Adobe integration", "aio app deploy", or "promote Adobe app". allowed-tools: Read,Glob,Grep,Write,Edit argument-hint: "<artifact> <target-environment> <rollout-scope>" version: 1.8.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags: [saas, adobe, deployment] model: inherit effort: high compatibility: "Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval"

Adobe Integration Deployment

Overview

Deploy an Adobe-backed service or App Builder application with isolated environments, immutable artifacts, canaries, observability, and rollback. This workflow produces a reviewable artifact and evidence before any live side effect.

Prerequisites

  • Current first-party Adobe documentation for every selected service, API version, auth flow, limit, and lifecycle.
  • Named product, identity, security, data, budget, release, and operations owners appropriate to the scope.
  • Synthetic or approved non-production fixtures with secret and content canaries.

Current Contract

AIO CLI v11 and later require Adobe IMS authentication for App Builder deploys: interactive aio login locally or OAuth Server-to-Server in CI. Runtime namespace auth is not a current deploy mechanism. Stage and Production workspaces are isolated. Recheck the dated evidence map before relying on mutable product behavior.

Authentication

Bind deploy credentials and product credentials to the target environment. app.config.yaml is reviewed source; .env and .aio are local state and must not be committed.

Instructions

  1. Verify the artifact digest, dependency locks, configuration schema, tests, migration, and rollback artifact.
  2. Resolve organization, project, workspace, service credentials, product profiles, storage, and event registrations.
  3. Confirm the AIO CLI/auth path or external platform identity and fail closed on environment mismatch.
  4. Deploy dark, verify configuration and logs, then run one approved read-only or synthetic smoke path.
  5. Canary bounded traffic while watching auth, 429, jobs, queue age, spend, activations, and content-safe errors.
  6. Promote or roll back from declared thresholds and preserve deployment, activity-log, cleanup, and owner receipts.

Tool Discipline

Use Read, Glob, and Grep to inspect current documentation, configuration, code, fixtures, and evidence. Use Write and Edit only for approved repository artifacts. Skill invocation alone does not authorize network access, credentials, Adobe content, consent, uploads, generation, spend, deployment, registration changes, replay, cancellation, or deletion.

Approval Boundaries

Release owner approves production deployment; security approves credentials; data/budget owners approve live product calls; webhook or asset deletion needs separate approval.

Error Handling

  • Stop if the selected workspace differs from the review target.
  • Do not commit .env or .aio.
  • Rollback if artifact, auth, entitlement, storage, or observability evidence is missing.

Output

Return artifact and environment identity, auth path, preflight, smoke/canary metrics, decision, rollback, cleanup, and owners. Mark assumptions, observed environment behavior, owners, evidence dates, and unresolved gaps explicitly.

Examples

  • Deploy to Stage and prove Production is unchanged.
  • Exercise rollback after a synthetic entitlement failure.

Validation

Exercise and record expected and observed results for:

  • artifact mismatch
  • workspace mismatch
  • missing entitlement
  • 429
  • rollback
  • cleanup

Resources

  • Current first-party evidence map — recheck dated Adobe sources before execution.
  • Treat observed tenant or product behavior as environment-specific evidence, never a universal Adobe guarantee.

Related Skills

View on GitHub
GitHub Stars2.8k
CategoryOperations
Updated5d ago
Forks404

Languages

Python

Trust signals

100/100

From repository metadata: license, adoption, age and documentation. Not a code audit — see the Safety scan above for what the skill file itself contains.

No cautions