digitalocean-app-platform

digitalocean-app-platform is a skill for Claude Code from Goodsmileduck/claude-registry. It costs 123 tokens per session (866 once invoked), scanned A, original, MIT.

A checker for DigitalOcean App Platform deployment specifications, such as app.yaml files and Terraform resources. It looks for configuration problems involving secrets, health checks, scaling, databases, ports, and routing.

In plain words
What is it for?
Reviewing or authoring App Platform specifications before deployment and explaining each detected problem with its severity and a suggested fix.
Why use it?
It helps catch settings that could expose credentials, cause downtime, break deployment, or send traffic to the wrong service.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the digitalocean-skills plugin — 3 skills shipped together

Good fit Reviewing or authoring App Platform specifications before deployment and explaining each detected problem with its severity and a suggested fix.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/goodsmileduck/claude-registry/digitalocean-app-platform
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Goodsmileduck/claude-registry --skill digitalocean-app-platform
Clone the repo
git clone --depth 1 https://github.com/Goodsmileduck/claude-registry

Made for: Claude Code.

Or install digitalocean-skills, the plugin that ships this one along with the rest of its 3 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for digitalocean-app-platform

README.md
[![agentmods](https://agentmods.dev/badge/skills/goodsmileduck/claude-registry/digitalocean-app-platform/github.svg)](https://agentmods.dev/skills/goodsmileduck/claude-registry/digitalocean-app-platform)
Your own site
<a href="https://agentmods.dev/skills/goodsmileduck/claude-registry/digitalocean-app-platform"><img src="https://agentmods.dev/badge/skills/goodsmileduck/claude-registry/digitalocean-app-platform/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for digitalocean-app-platform

Your own site · 80×15
<a href="https://agentmods.dev/skills/goodsmileduck/claude-registry/digitalocean-app-platform"><img src="https://agentmods.dev/badge/skills/goodsmileduck/claude-registry/digitalocean-app-platform.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 123 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 866 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00123 $0.00866
Opus 5 $0.00062 $0.00433
Sonnet 5 $0.00025 $0.00173
Haiku 4.5 $0.00012 $0.00087

Measured 10d ago against content hash 6c4317059be0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

digitalocean-app-platform scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.

The scan reads SKILL.md. This mod also ships 2 executable files (scripts/do_app_spec_lint.py, scripts/test_do_app_spec_lint.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/digitalocean-skills/skills/digitalocean-app-platform/SKILL.md · 72 lines

How it starts

The opening of the file, as written. The whole thing — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DigitalOcean App Platform

Reviews App Platform app specs for the mistakes that cause downtime, leaked secrets, and broken routing. Ships a stdlib-only validator, do_app_spec_lint.py, that ingests the spec as JSON (recommended), the block-YAML DO emits, or the digitalocean_app Terraform resource, and reports findings with a rule id, severity, and a one-line fix.

When to invoke

  • Reviewing or authoring an app.yaml / .do/app.yaml / digitalocean_app.
  • A service has downtime on deploy or flaps with no warning (health check / HA).
  • DigitalOcean warns that routes is deprecated.
  • A credential may be sitting in an env value in plaintext.
  • Ingress routing behaves unexpectedly (overlapping prefixes).

Cross-cutting rules

  1. Prefer JSON input. doctl apps spec get <app-id> --format json is the most reliable input; the YAML path is a subset parser and rejects anchors, flow collections, and folded/literal scalars.
  2. Never put a literal secret in an env value. Use type: SECRET and a ${VAR} substitution. Values containing ${...} (GitHub secrets, ${db.X} bindable refs, ${APP_URL} app-wide vars) are references, not literals.
  3. The app spec is the source of truth. App Platform reconciles to the spec on every deploy; fix the spec, not the running app.

Running the validator

# JSON (recommended)
doctl apps spec get <app-id> --format json > spec.json
python3 scripts/do_app_spec_lint.py spec.json

# YAML subset, or Terraform — format auto-detected by extension/content
python3 scripts/do_app_spec_lint.py .do/app.yaml
python3 scripts/do_app_spec_lint.py main.tf

# machine-readable
python3 scripts/do_app_spec_lint.py spec.json --format json

Exit 0 = clean or warnings only; 1 = at least one error-severity finding; 2 = unreadable/unparseable input.

Checks

  • Secretssecret-not-encrypted (literal secret with type != SECRET), secret-build-scope (SECRET scoped RUN_AND_BUILD_TIME leaks into the build).
  • Reliabilityno-health-check, single-instance (one instance, no autoscaling), dev-db-as-prod (database with production: false).
  • Correctnessport-mismatch, route-overlap, source-conflict (both git and image), deprecated-routes.
  • Sizingunknown-instance-slug, db-region-mismatch.

Read the full file on GitHub · 72 lines

Files

What ships with it

5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 10d ago First seen · 72 lines · 123 tokens per session scan A 6c4317059be0

Subscribe to this mod's changes

digitalocean-app-platform is a skill published in the GitHub repository Goodsmileduck/claude-registry (1 stars, last pushed 1mo ago), licensed MIT. It adds 123 tokens to every session and 866 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.