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Incident Response

Organization
adobe
incident-response

Investigate and triage runtime incidents involving the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service environments only, using runtime-backed MCP evidence.

Overview

Publisheradobe
Repositoryskills
Skill nameincident-response
Stars
298
Forks
92
Bundled files
16
LicenseApache-2.0
Links
Skill sourceRepositoryHomepage
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 16 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by adobe on GitHub. Read the source before you install it.

Installation

Install the Incident Response AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/incident-response
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/adobe/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/plugins/aem/cloud-service/skills/dispatcher/incident-response .claude/skills/incident-response
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Incident Response in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Incident Response on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Incident Response is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Dispatcher Runtime Incident Response (Cloud)

Investigate cloud runtime incidents involving the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration with an evidence-first workflow.

Variant Scope

  • This skill is cloud-service-only.
  • Scope is fixed by this skill directory; do not ask the user to choose deployment variant.

MCP Tool Contract

Use only these Dispatcher MCP tools:

  • monitor_metrics
  • tail_logs
  • trace_request
  • inspect_cache
  • validate
  • lint
  • sdk

Workflow

  1. Quantify impact (monitor_metrics).
  2. Classify whether issue belongs to Dispatcher layer or CDN/edge layer using cloud guardrails, including reserved probe-path behavior.
  3. Gather logs and traces (tail_logs, trace_request). To get the full log sequence for a specific request: use tail_logs to obtain entries (some include pid and tid from dispatcher debug lines), then call trace_request(pid=..., tid=...) to retrieve all log lines for that request. See mcp-tool-orchestration.md § Trace by pid:tid.
  4. Inspect cache behavior (inspect_cache).
  5. Correlate with static checks (validate, lint, sdk).
  6. Return containment + remediation + rollback.

Verification Scope Selection

Use shared references to select incident evidence depth:

Output Contract

Always return:

  • incident summary (symptom, impact window, blast radius)
  • evidence table (tool, input, finding)
  • selected test IDs and outcomes
  • probable cause + confidence level
  • containment, durable remediation, and rollback
  • open risks and missing evidence

Guardrails

  • Distinguish observations from inference.
  • Do not claim root-cause certainty without corroborating evidence.
  • Do not claim runtime verification if container/runtime prerequisites were missing.
  • Keep fixes reversible unless user explicitly requests high-risk change.
  • For cloud incidents, explicitly state when root cause is outside Dispatcher config scope (CDN/WAF/edge policy).

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Incident Response AI skill do?

Investigate and triage runtime incidents involving the Adobe Dispatcher Apache HTTP Server module and related HTTPD configuration in AEM as a Cloud Service environments only, using runtime-backed MCP evidence.

Why use Incident Response on TypingMind?

Because you install it once and use it with any model. Incident Response is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Incident Response in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/adobe/skills/tree/main/plugins/aem/cloud-service/skills/dispatcher/incident-response. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Incident Response?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Incident Response?

As many as you like. As long as a model supports skills, you can use Incident Response with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Incident Response AI skill free?

Yes. It is published on GitHub by adobe under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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