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A model-agnostic agent-skills platform.
用 Codex 或 Claude 安装复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它先审查 Skill 页面再帮你安装。
复制前请先查看来源、License 和安全提示。
来源文件:README.md
A model-agnostic agent-skills platform. The canonical layer is harness-free by construction; Claude Code is currently the verified-native harness. Other harnesses remain engineering candidates until their native-path integration is verified; source research alone is never presented as public support.
Inside Claude Code, one command installs the whole marketplace:
/plugin marketplace add jeremylongshore/claude-code-plugins
Or use the CLI:
pnpm add -g @intentsolutionsio/ccpi
ccpi install devops-automation-pack
Browse the marketplace · Explore plugins · Download bundles
Killer Skill of the Week — no-ai-slop by Peter Yang
Strip AI slop from any draft — named-pattern edits that keep the writer's real voice
no-ai-slop does two jobs and refuses to fake a third. In Edit mode it makes the minimum effective edit — cutting throat-clearing, weak verbs, and abstract nouns while deliberately preserving the writer's cadence, bluntness, humor, and honest admissions, so a rough draft still sounds like the same person afterward. In Detect mode it names each AI-slop pattern it finds, quotes the offending line, and gives the fix in a few words — and pointedly does NOT score the draft or guess whether an AI wrote it. That restraint is the whole point: AI detectors guess; named patterns are evidence the reader can check. MIT-licensed, single focused skill, actively maintained by Peter Yang.
"AI detectors guess. Named patterns are evidence the user can check." — Peter Yang
Grade: A | Week of July 22, 2026 (W30) | View on GitHub
Previous picks: tonone, mnemos, databricks-pack, kobiton-automate, skyvern, code-cleanup, web-analytics, token-optimizer, executive-assistant-skills, skill-creator, cursor-pack, crypto-portfolio-tracker. See all at tonsofskills.com.
Every number below names the cohort it counts and the command that reproduces it — an unlabeled count is how a corpus ends up with five contradictory answers to "how many skills."
| Count | Cohort | Reproduce with |
|---|---|---|
| 442 | catalog plugins (catalog-entry cohort) | node scripts/generate-readme-toc.mjs over marketplace.extended.json |
| 3,067 | marketplace-visible skills (distinct) | node -e "import('./scripts/corpus-resolver.mjs').then(m=>console.log(m.resolveCorpus('marketplace-visible').length))" |
| 347 | agent definitions in plugins | git ls-files 'plugins/**' | grep '/agents/.*\.md' |
| 19 | plugin categories | ls -d plugins/*/ |
Across 396 published packages in the claude-code-plugins namespace. Updated daily by GitHub Actions.
| Window | All packages | Established (>30d) |
|---|---|---|
| Last 24 hours | 962 | 962 |
| Last 7 days | 2,920 | 2,916 |
| Last 30 days | 12,868 | 12,779 |
"Established" excludes packages first published within the last 30 days, so a bulk-publish event doesn't dominate the headline.
Top 10 by last 30 days:
Last refreshed 2026-08-19T03:03:05.709Z.
Five real questions, five doors — each resolves to a live, generated surface, never a hand-maintained list:
The 19 categories below link into the live marketplace. Plugin counts are the catalog-entry cohort — regenerated from marketplace.extended.json by this generator; the catalog itself lives on tonsofskills.com, never in this file (§ 6A of the platform blueprint).
| Category | Plugins | |
|---|---|---|
| 🤖 | AI & Machine Learning | 36 |
| 🎭 | AI Agents & Agency | 10 |
| 🔌 | API Development | 26 |
| 💼 | Business Tools | 6 |
| 👥 | Community | 21 |
| ₿ | Crypto & Web3 | 27 |
| 💾 | Database | 26 |
| 🎨 | Design | 2 |
| 🔧 | DevOps & Infrastructure | 36 |
| 📚 | Examples & Templates | 5 |
| 🧩 | MCP Servers | 16 |
| 📦 | Packages | 5 |
| ⚡ | Performance | 25 |
| ✅ | Productivity | 30 |
| 🎁 | SaaS Skill Packs | 106 |
| 🔐 | Security | 27 |
| ✨ | Skill Enhancers | 9 |
| 🧪 | Testing | 28 |
| 📁 | Analytics | 1 |
Four artifact classes live in this repository, distinguished on sight and never blurred — provenance is a truth requirement here, not a UX nicety:
| Class | What it is | How the reader can tell |
|---|---|---|
| Canonical skill | First-party, harness-free, the source of truth | No .source.json in its plugin directory |
| Generated adapter | A thin, machine-produced harness projection | Lives under a generated path with a "generated — do not edit" header |
| First-party package | An Intent Solutions distribution (npm, cowork zip) | @intentsolutionsio scope, IS-authored license |
| Upstream mirror | Somebody else's work, hosted mirror-by-default | .source.json present — upstream author, license, and pinned commit recorded |
Not yet certified. The certification program (tiers T0–T4 with retained, hash-matched evidence) is a later epic of the platform blueprint; until its report exists, no artifact on this surface claims a tier. This line is rendered from the absence of certification-report.json — honestly, not cosmetically.
Start with the contribution guide, then the intake and review standards every submission passes through:
External plugins are hosted mirror-by-default: the contributor's repository stays the source of truth, every mirrored source is pinned in a content lockfile, and upstream credit — author, license, resolved commit — is recorded in the mirror itself. Improvements flow by upstreaming to the author's repository, never by silently editing the mirror. The full decision record is the external-sync model.
MIT for the repository scaffolding and first-party tooling; each plugin carries its own license in its manifest, and mirrored plugins keep their upstream license verbatim.
name: adobe-multi-env-setup
description: 'Configure Adobe OAuth credentials and API access across development,
staging, and production environments with separate Developer Console
projects, secret managers, and environment-specific scoping.
Trigger with phrases like "adobe environments", "adobe staging",
"adobe dev prod", "adobe environment setup", "adobe config by env".
'
allowed-tools: Read, Write, Edit, Bash(aws:*), Bash(gcloud:*), Bash(vault:*)
version: 1.7.0
license: MIT
author: Jeremy Longshore <jeremy@intentsolutions.io>
tags:
- saas
- design
- adobe
compatibility: Designed for Claude CodeConfigure Adobe APIs across development, staging, and production environments using separate Developer Console projects, environment-specific OAuth credentials, and cloud-native secret management.
Adobe best practice: one Developer Console project per environment with separate OAuth credentials.
| Environment | Console Project | Scopes | Product Profile |
|---|---|---|---|
| Development | my-app-dev | openid,AdobeID | Dev sandbox |
| Staging | my-app-staging | openid,AdobeID,firefly_api | Staging profile |
| Production | my-app-prod | openid,AdobeID,firefly_api,ff_apis | Production profile |
// src/config/adobe.ts
interface AdobeEnvConfig {
imsEndpoint: string; // Same across all envs
fireflyEndpoint: string; // Same across all envs
photoshopEndpoint: string; // Same across all envs
scopes: string; // Different per env (least privilege)
retries: number;
timeoutMs: number;
cache: { enabled: boolean; ttlMs: number };
}
const configs: Record<string, AdobeEnvConfig> = {
development: {
imsEndpoint: 'https://ims-na1.adobelogin.com',
fireflyEndpoint: 'https://firefly-api.adobe.io',
photoshopEndpoint: 'https://image.adobe.io',
scopes: 'openid,AdobeID', // Minimal scopes for dev
retries: 1, // Fast failure in dev
timeoutMs: 15_000,
cache: { enabled: false, ttlMs: 0 }, // No cache in dev
},
staging: {
imsEndpoint: 'https://ims-na1.adobelogin.com',
fireflyEndpoint: 'https://firefly-api.adobe.io',
photoshopEndpoint: 'https://image.adobe.io',
scopes: 'openid,AdobeID,firefly_api',
retries: 3,
timeoutMs: 30_000,
cache: { enabled: true, ttlMs: 60_000 },
},
production: {
imsEndpoint: 'https://ims-na1.adobelogin.com',
fireflyEndpoint: 'https://firefly-api.adobe.io',
photoshopEndpoint: 'https://image.adobe.io',
scopes: 'openid,AdobeID,firefly_api,ff_apis',
retries: 5,
timeoutMs: 60_000,
cache: { enabled: true, ttlMs: 300_000 },
},
};
export function getAdobeConfig(): AdobeEnvConfig & { clientId: string; clientSecret: string } {
const env = process.env.NODE_ENV || 'development';
const config = configs[env] || configs.development;
return {
...config,
clientId: process.env.ADOBE_CLIENT_ID!,
clientSecret: process.env.ADOBE_CLIENT_SECRET!,
};
}
# --- Local Development ---
# .env.local (git-ignored)
ADOBE_CLIENT_ID=dev-client-id-from-console
ADOBE_CLIENT_SECRET=p8_dev_secret
ADOBE_SCOPES=openid,AdobeID
# --- GCP Secret Manager ---
# Create secrets for staging and production
gcloud secrets create adobe-client-id-staging --data-file=- <<< "staging-client-id"
gcloud secrets create adobe-client-secret-staging --data-file=- <<< "p8_staging_secret"
gcloud secrets create adobe-client-id-prod --data-file=- <<< "prod-client-id"
gcloud secrets create adobe-client-secret-prod --data-file=- <<< "p8_prod_secret"
# Grant service account access
gcloud secrets add-iam-policy-binding adobe-client-secret-prod \
--member="serviceAccount:my-app@project.iam.gserviceaccount.com" \
--role="roles/secretmanager.secretAccessor"
# --- AWS Secrets Manager ---
aws secretsmanager create-secret \
--name adobe/staging/credentials \
--secret-string '{"client_id":"...","client_secret":"p8_staging_..."}'
aws secretsmanager create-secret \
--name adobe/production/credentials \
--secret-string '{"client_id":"...","client_secret":"p8_prod_..."}'
# --- HashiCorp Vault ---
vault kv put secret/adobe/staging client_id="..." client_secret="p8_staging_..."
vault kv put secret/adobe/production client_id="..." client_secret="p8_prod_..."
# .github/workflows/deploy.yml
jobs:
deploy:
strategy:
matrix:
environment: [staging, production]
environment: ${{ matrix.environment }}
runs-on: ubuntu-latest
env:
NODE_ENV: ${{ matrix.environment }}
ADOBE_CLIENT_ID: ${{ secrets[format('ADOBE_CLIENT_ID_{0}', matrix.environment)] }}
ADOBE_CLIENT_SECRET: ${{ secrets[format('ADOBE_CLIENT_SECRET_{0}', matrix.environment)] }}
steps:
- uses: actions/checkout@v4
- run: npm ci && npm test
- name: Verify Adobe credentials for ${{ matrix.environment }}
run: |
HTTP_CODE=$(curl -s -o /dev/null -w "%{http_code}" -X POST \
'https://ims-na1.adobelogin.com/ims/token/v3' \
-d "client_id=${ADOBE_CLIENT_ID}&client_secret=${ADOBE_CLIENT_SECRET}&grant_type=client_credentials&scope=openid,AdobeID")
if [ "$HTTP_CODE" != "200" ]; then
echo "::error::Adobe credential validation failed for ${{ matrix.environment }}"
exit 1
fi
- run: npm run deploy:${{ matrix.environment }}
// Prevent accidental production operations in non-prod
function requireEnvironment(required: string): void {
const current = process.env.NODE_ENV || 'development';
if (current !== required) {
throw new Error(
`Operation requires ${required} environment, currently running in ${current}`
);
}
}
// Usage: guard dangerous operations
async function deleteAllCachedAssets() {
requireEnvironment('production');
// ... actual deletion logic
}
| Issue | Cause | Solution |
|---|---|---|
invalid_scope in staging | Scope not in staging project | Add API to staging Console project |
| Wrong credentials deployed | Environment mismatch | Verify NODE_ENV matches secret path |
| Secret access denied | Missing IAM binding | Grant secretAccessor role |
| Config merge fails | Missing env config file | Ensure all environments defined |
Start with the smallest applicable command or code example already provided in this guide, using a non-production Adobe environment and credentials. Confirm the documented response or validation result before applying the pattern to production.
For observability setup, see adobe-observability.
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