auto-doctor

auto-doctor is a skill for Claude Code from easingthemes/dx-aem-flow. It costs 35 tokens per session (2,960 once invoked), scanned A, original, MIT.

A health-check skill for an AI automation project that examines local configuration, deployment pipelines, and serverless functions. A serverless function is a cloud function that runs without managing a server directly.

In plain words
What is it for?
Use it to inspect automation settings, validate configuration files, check active pipelines and regions, and verify the expected cloud functions and related resources.
Why use it?
It finds missing or invalid configuration, leftover placeholders, and deployment or function problems before they cause failures. It also identifies older configuration profiles that need migration.

Skill for Claude Code

Written for Claude Code: argument-hint in frontmatter.

Part of the dx-automation plugin — 11 skills shipped together

Good fit Use it to inspect automation settings, validate configuration files, check active pipelines and regions, and verify the expected cloud functions and related resources.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/easingthemes/dx-aem-flow/auto-doctor
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 easingthemes/dx-aem-flow --skill auto-doctor
Clone the repo
git clone --depth 1 https://github.com/easingthemes/dx-aem-flow

Made for: Claude Code.

Or install dx-automation, the plugin that ships this one along with the rest of its 11 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 auto-doctor

README.md
[![agentmods](https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-doctor/github.svg)](https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-doctor)
Your own site
<a href="https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-doctor"><img src="https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-doctor/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 auto-doctor

Your own site · 80×15
<a href="https://agentmods.dev/skills/easingthemes/dx-aem-flow/auto-doctor"><img src="https://agentmods.dev/badge/skills/easingthemes/dx-aem-flow/auto-doctor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 35 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,960 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 $0.00035 $0.02960
Opus 5 $0.00017 $0.01480
Sonnet 5 $0.00007 $0.00592
Haiku 4.5 $0.00003 $0.00296

Measured 8d ago against content hash 19b54982d1b1, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

auto-doctor 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 8d ago.

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/dx-automation/skills/auto-doctor/SKILL.md · 229 lines

How it starts

The opening of the file, as written. The whole thing — 229 lines — stays where its author put it; the contents beside it link to each section on GitHub.

You run a health check on the AI automation setup. Each project is self-contained — it owns its own Lambda and pipelines. Legacy profiles consumer, pr-only, and pr-delegation are treated as per-project (warn to re-run /auto-init if found).

0. Read Config

Read .ai/automation/infra.json. If missing: "Run /auto-init first." STOP.

Extract automationProfile. If value is consumer, pr-only, or pr-delegation: warn ⚠ Legacy profile '${profile}' — re-run /auto-init to migrate to per-project model. and treat as per-project for the remainder of this check.

Also extract: pipeline entries (only those without "disabled": true), region, prefix, Lambda function names.

1. Local File Integrity

Config files:

  • infra.json — no remaining {{PLACEHOLDER}} values (check for {{)
  • repos.jsonoptional; validate only if present. No pipeline, Lambda, or skill reads repos.json at runtime — it is documentation-only intent (future cross-repo discovery), so its absence is expected and harmless, especially for CLI-pipeline-only consumers (it was deliberately removed from some).
    • present + valid JSON →
    • present + invalid JSON → ✗ invalid JSON (the only failing case — a hand-edited file that won't parse)
    • absent → — optional (unused — not read by any pipeline or agent) — NOT an issue; do NOT report , and do NOT let it affect the Overall verdict.

Check infra.json for unfilled placeholders:

python3 -c "
import json, re
with open('.ai/automation/infra.json') as f:
    content = f.read()
placeholders = re.findall(r'\{\{[^}]+\}\}', content)
if placeholders:
    print('UNFILLED PLACEHOLDERS:', list(set(placeholders)))
else:
    print('OK — no unfilled placeholders')
"

Pipeline YAMLs (all profiles):

For each enabled pipeline entry in infra.json, check that the YAML file referenced in pipelines.<agent>.yaml exists on disk:

  • Exists →
  • Missing → ✗ MISSING

Lambda handlers (when Lambda agents are enabled):

Skip Lambda file checks if no Lambda-based agents are enabled (i.e., only PR Review, PR Answer, and Eval are in the enabled list — those run as ADO pipelines without Lambda).

Read the full file on GitHub · 229 lines

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. 8d ago First seen · 229 lines · 35 tokens per session scan A 19b54982d1b1

Subscribe to this mod's changes

auto-doctor is a skill published in the GitHub repository easingthemes/dx-aem-flow (6 stars, last pushed 7d ago), licensed MIT. It adds 35 tokens to every session and 2,960 once invoked, about $0.0002 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.

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