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Agent skill

Adobe Policy Guardrails

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules.

MITAuto-check passedAI & LLM Engineering

Install Adobe Policy Guardrails

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-policy-guardrails -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace adobe-policy-guardrails --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/adobe-policy-guardrails .claude/skills/adobe-policy-guardrails && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
adobe-policy-guardrails
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
429 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules.

  • Works in 6 steps: Inventory all Adobe calls, credentials,… → Create allowlists for current… → Validate configuration/request/response… → …
  • The task requires adobe policy and execution guardrails
  • SKILL.md covers Overview, Prerequisites, Current Contract and Authentication, plus 8 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Adobe Policy Guardrails is an agent skill from jeremylongshore/tons-of-skills-marketplace. Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules. Use when the task requires adobe policy and execution guardrails. Trigger with "Adobe guardrails", "block unsafe Adobe calls", or "Adobe policy checks".

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval

It sits in AI & LLM Engineering, covering LLM guardrails. The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • The task requires adobe policy and execution guardrails
  • With Adobe guardrails
  • Block unsafe Adobe calls
  • Adobe policy checks

Example prompts

  • “Adobe guardrails”
  • “block unsafe Adobe calls”
  • “Adobe policy checks”
  • “/adobe-policy-guardrails”

Requirements

  • Compatibility (from SKILL.md): Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Write, Edit

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Inventory all Adobe calls, credentials, endpoints, versions, payload classes, storage URLs, retries, jobs, events, and destructive…
  2. Create allowlists for current hosts/versions/services and denylists for JWT, /sensei/cutout, and retired Lightroom Firefly Services.
  3. Validate configuration/request/response schemas and redact tokens, signed URLs, prompts, and customer content.
  4. Enforce data-purpose, owner, budget, concurrency, idempotency, and approval tokens before side effects.
  5. Route Adobe policy outcomes to a human-readable denial path; never silently rewrite prompts or broaden scopes.
  6. Test bypasses, stale docs, false positives, emergency disablement, exception expiry, and audit receipts.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval

    From compatibility in the SKILL.md frontmatter.

Context cost

Adobe Policy Guardrails loads about 1.1k tokens when it runs, and up to ~1.9k if it reads all its reference files. Until then it costs about 80 tokens; SKILL.md has 429 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~80
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 429 words, ~1,069 tokens.

Download SKILL.mdSave it as .claude/skills/adobe-policy-guardrails/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
adobe-policy-guardrails
description
Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules. Use when the task requires adobe policy and execution guardrails. Trigger with "Adobe guardrails", "block unsafe Adobe calls", or "Adobe policy checks".
allowed-tools
Read, Glob, Grep, Write, Edit
compatibility
Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval
argument-hint
<repository-or-service> <operations> <policy-owners>
version
1.8.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, adobe, guardrails
model
inherit
effort
high

Adobe Policy and Execution Guardrails

Overview

Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules. 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

Guardrails derive from current service docs and local policy: approved auth flows, hosts/versions, scopes/profiles, schemas, storage domains, budgets, data classes, and approval boundaries. Secret prefixes and prompt regexes are not authoritative security or content-policy controls. Recheck the dated evidence map before relying on mutable product behavior.

Authentication

Use mature secret scanners plus entropy/context rules and provider revocation procedures. Runtime authorization evaluates credential binding, entitlement, resource, operation, and approval.

Instructions

  1. Inventory all Adobe calls, credentials, endpoints, versions, payload classes, storage URLs, retries, jobs, events, and destructive operations.
  2. Create allowlists for current hosts/versions/services and denylists for JWT, /sensei/cutout, and retired Lightroom Firefly Services.
  3. Validate configuration/request/response schemas and redact tokens, signed URLs, prompts, and customer content.
  4. Enforce data-purpose, owner, budget, concurrency, idempotency, and approval tokens before side effects.
  5. Route Adobe policy outcomes to a human-readable denial path; never silently rewrite prompts or broaden scopes.
  6. Test bypasses, stale docs, false positives, emergency disablement, exception expiry, and audit receipts.
Show full SKILL.md (190 more words)Show less

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

Security/product/data/budget owners approve policy and exceptions. Generation, upload, deploy, webhook change, cancellation, replay, and deletion remain independently approved actions.

Error Handling

  • Do not claim Adobe secrets always have a specific prefix.
  • Do not claim local regexes predict Firefly policy decisions.
  • Fail closed when endpoint/version or approval evidence is unknown.

Output

Return policy sources, allow/deny rules, enforcement points, test corpus, exceptions, receipts, drift monitor, and owners. Mark assumptions, observed environment behavior, owners, evidence dates, and unresolved gaps explicitly.

Examples

  • Block /sensei/cutout before network execution.
  • Detect a signed URL in a log fixture and fail the gate.

Validation

Exercise and record expected and observed results for:

  • obsolete route
  • unknown host
  • secret leak
  • policy outcome
  • budget ceiling
  • expired exception

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.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/adobe-policy-guardrails of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Adobe Policy Guardrails next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Adobe Policy Guardrails compared with similar skills
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Adobe Policy Guardrails this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
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ObliteratusRedWoodOG/Hermes-Desktop1775 repos~3.8kAutomated safety check: PassMIT
Lemonade Router Builderamd/skills408—~4kAutomated safety check: PassMIT
Writing Eval Scenariosopen-bias/open-bias143—~1.5kAutomated safety check: PassApache-2.0
Wp Project Triagegambitph/Stackable3513 repos~371Automated safety check: PassGPL-3.0

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Categories

Questions about Adobe Policy Guardrails

What does Adobe Policy Guardrails do?

Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules. Adobe Policy Guardrails is an agent skill from jeremylongshore/tons-of-skills-marketplace. Analyze and enforce repository, runtime, data, spend, endpoint, and approval guardrails without guessing secret formats or content-policy rules.

When should I use Adobe Policy Guardrails?

Adobe Policy Guardrails fits situations like: the task requires adobe policy and execution guardrails; with Adobe guardrails; block unsafe Adobe calls; adobe policy checks.

How do I install Adobe Policy Guardrails in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-policy-guardrails -a claude-code`. Or copy the skill folder (skills/.curated/adobe-policy-guardrails in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/adobe-policy-guardrails in your project. Claude Code loads it when a task matches its description.

How do I install Adobe Policy Guardrails in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-policy-guardrails -a codex`. Or copy the skill folder (skills/.curated/adobe-policy-guardrails in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/adobe-policy-guardrails in your project. Codex loads it when a task matches its description.

Can I use Adobe Policy Guardrails in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill adobe-policy-guardrails -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/adobe-policy-guardrails, .gemini/skills/adobe-policy-guardrails, .github/skills/adobe-policy-guardrails and .opencode/skills/adobe-policy-guardrails in your project.

What does Adobe Policy Guardrails need to run?

SKILL.md names no scripts, command-line tools or credentials: Adobe Policy Guardrails is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Glob, Grep, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; live Adobe actions require network access, appropriate entitlement and authentication, and explicit approval.

Does Adobe Policy Guardrails access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Adobe Policy Guardrails safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Adobe Policy Guardrails use?

Adobe Policy Guardrails is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Adobe Policy Guardrails use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 823 tokens, read only when the agent opens those files.

What are the alternatives to Adobe Policy Guardrails?

Skills that share tags, products or a category with Adobe Policy Guardrails: Aisafetyhot (wuyoscar/AISafetyHot-Hub, 827 stars), Obliteratus (RedWoodOG/Hermes-Desktop, 177 stars), Lemonade Router Builder (amd/skills, 408 stars) and Writing Eval Scenarios (open-bias/open-bias, 143 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Adobe Policy Guardrails?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.