SkillAgentSearch skills...

adobe-local-dev-loop

Build a repeatable local loop for Adobe adapters using synthetic contracts before any remote Runtime or product call

Install / Use

npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-local-dev-loop

Installs into whichever agent you are using.

About this skill
📄

SKILL.md

Installable skill definition

Quality Score

80/100

Category

Legal

Supported Platforms

Claude Code

Our assessment of adobe-local-dev-loop

adobe-local-dev-loop scores 80/100 on our quality scale, 134th of 163 Legal 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
12/15
Adoption
15/20
Freshness
15/15

Maintenance, license and trust

  • The repository was last updated 6 days ago, so adobe-local-dev-loop 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-local-dev-loop compared with similar skills

All 4 of these similar skills score higher than adobe-local-dev-loop; compare them before choosing.

SkillScoreStarsUpdatedFormat
adobe-local-dev-loop (this skill)by jeremylongshore802.8k6d agoSKILL.md
Agent-Reachby Panniantong10086.3k14d agoCLAUDE.md
headroomby headroomlabs-ai10074.1ktodayCLAUDE.md
Scraplingby D4Vinci10084.6ktodayMCP Server
crawl4aiby unclecode10084.5k5d agoMCP Server

Frequently asked questions

How do I install adobe-local-dev-loop?
Run npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-local-dev-loop. The install tabs above show the steps for each supported agent.
Which AI agents does adobe-local-dev-loop work with?
It is written for Claude Code, as a SKILL.md file. Other agents that read the same format can often use it too.
Is adobe-local-dev-loop 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-local-dev-loop still maintained?
The repository was last updated 6 days ago, so adobe-local-dev-loop is actively maintained.

name: adobe-local-dev-loop description: >- Build a repeatable local loop for Adobe adapters using synthetic contracts before any remote Runtime or product call. Use when implementing or debugging locally. Trigger with "develop Adobe integration locally", "mock Adobe API", or "aio app dev". allowed-tools: Read,Glob,Grep,Write,Edit argument-hint: "<repository> <service> <feature>" version: 1.8.0 license: MIT author: Jeremy Longshore jeremy@intentsolutions.io tags: [saas, adobe, development] model: inherit effort: high compatibility: "Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval"

Adobe Isolated Development Loop

Overview

Build a repeatable local loop for Adobe adapters using synthetic contracts before any remote Runtime or product call. 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

App Builder local modes differ: aio app dev runs actions locally and lacks activation records and some Runtime-only storage capabilities; aio app run uses remote Runtime actions with local UI. Offline fixtures must cover both product responses and those environment differences. Recheck the dated evidence map before relying on mutable product behavior.

Authentication

Use synthetic data and non-production aliases. Keep .env and .aio out of version control; pass configured values to actions rather than assuming local environment variables exist in deployed Runtime.

Instructions

  1. Inventory the adapter, SDK locks, App Builder configuration, fixtures, and current local-mode assumptions.
  2. Define typed request, response, async-status, error, throttling, and redaction contracts from current docs.
  3. Create synthetic fixtures for success, additive fields, malformed data, 401/403, 429, 5xx, and ambiguous completion.
  4. Run unit and contract tests with network access disabled and secret canaries enabled.
  5. If App Builder is used, exercise aio app dev and a separately approved aio app run path where Runtime fidelity matters.
  6. Record mode differences, cleanup remote test artifacts, and keep only sanitized deterministic fixtures.

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

Require sandbox-owner approval for remote Runtime or Adobe API calls and separate approval for uploads, generation, writes, or deletion.

Error Handling

  • Fail if a production hostname, organization, credential, or asset enters a fixture.
  • Do not snapshot signed URLs or document/image bytes into source control.
  • Treat locally unsupported State or Files behavior as unknown until remote testing.

Output

Return the client seam, fixture manifest, commands, secret scan, local/remote matrix, cleanup, and remaining unknowns. Mark assumptions, observed environment behavior, owners, evidence dates, and unresolved gaps explicitly.

Examples

  • Replay a 429 with and without Retry-After.
  • Prove aio app dev limitations are not represented as production behavior.

Validation

Exercise and record expected and observed results for:

  • offline success
  • additive field
  • auth denial
  • 429
  • Runtime-only feature
  • secret canary

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
CategoryLegal
Updated6d 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