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Error Propagation

CommunityPopular
hoangsonww
error-propagation

Trace error propagation through a multi-agent session by agent depth — where failures originated, the depth at which they appeared, and how they cascaded up to parent agents — using the Agent Monitor workflow intelligence API and the session event stream. Use when a multi-agent run failed and you need to find the origin and blast radius of the failure.

Overview

Publisherhoangsonww
RepositoryClaude-Code-Agent-Monitor
Skill nameerror-propagation
Stars
1.1K
Forks
260
Bundled files
1
LicenseMIT
Links
  • 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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Error Propagation 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/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-workflows/skills/error-propagation
  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/hoangsonww/Claude-Code-Agent-Monitor.git /tmp/Claude-Code-Agent-Monitor
mkdir -p .claude/skills
cp -r /tmp/Claude-Code-Agent-Monitor/plugins/ccam-workflows/skills/error-propagation .claude/skills/error-propagation
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Error Propagation 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 Error Propagation 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 Error Propagation 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.

Error Propagation

Trace where a multi-agent session's failures started and how far they spread.

Input

The user provides: $ARGUMENTS

A session ID. If empty, fetch GET /api/sessions?limit=1, but prefer the most recent session whose status is error or abandoned; state which one you picked.

Data Sources

EndpointReturns
GET /api/workflows/{sessionId}The errorPropagation dataset: failures grouped by agent depth, with originating depth and cascade paths to parents
GET /api/events?session_id={sessionId}The event stream — corroborate with APIError, SubagentStop, and failing PostToolUse events (event_type, tool_name, summary, timestamp)

Report Sections

1. Failure Summary

From errorPropagation: total errors, the depth where the first error originated, and how many distinct agents were affected. Origin depth: d · Errors: N · Agents affected: M

2. Errors by Depth

DepthErrors originatedErrors inherited from childrenNet failing agents
Show whether failures concentrate deep in the tree (leaf subagents) or shallow (orchestrator).

3. Cascade Paths

For each originating failure, the path it propagated along: debugger (depth 2, tool failure) → code-review (depth 1, marked error) → root (depth 0, aborted) Tie each step to a concrete event from /api/events (event_type + tool_name + timestamp) where available.

4. Error Taxonomy

Break errors down by type from the event stream: APIError vs failing tool calls vs SubagentStop with error status. Note the most frequent tool involved in failures.

5. Containment Assessment

Whether failures were contained at the depth where they originated or leaked to parents. Name any parent that aborted solely because a child failed — a candidate for better error handling / isolation.

Output

  • Markdown tables for the depth breakdown; a fenced list for cascade paths.
  • Timestamps for the first and last error.
  • Cite only errors present in errorPropagation and the event stream; never invent failures or causes.
  • If the session has no errors, say so plainly and stop.
  • If the dashboard is unreachable, tell the user to start it with npm start from the repo root.

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 Error Propagation AI skill do?

Trace error propagation through a multi-agent session by agent depth — where failures originated, the depth at which they appeared, and how they cascaded up to parent agents — using the Agent Monitor workflow intelligence API and the session event stream. Use when a multi-agent run failed and you need to find the origin and blast radius of the failure.

Why use Error Propagation on TypingMind?

Because you install it once and use it with any model. Error Propagation 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 Error Propagation in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-workflows/skills/error-propagation. 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 Error Propagation?

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 Error Propagation?

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

Is the Error Propagation AI skill free?

Yes. It is published on GitHub by hoangsonww under the MIT 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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