Api Error Report

CommunityPopular

hoangsonww

api-error-report

Produce a detailed report on APIError events from Agent Monitor data — counts over time, which sessions and models are affected, and the likely root cause (rate limits, overload/529, or context-window pressure) inferred from each event's summary and data payload. Use when API errors spike or when you need to explain why requests are failing.

Overview

Publisher	hoangsonww
Repository	`Claude-Code-Agent-Monitor`
Skill name	`api-error-report`
Stars	1.1K
Forks	260
Bundled files	1
License	MIT
Links	Skill source Repository Homepage

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 Api Error Report AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-quality/skills/api-error-report
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-quality/skills/api-error-report

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

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-quality/skills/api-error-report .claude/skills/api-error-report

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Api Error Report 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 Api Error Report 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 Api Error Report 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.

API Error Report

Drill into APIError events: how many, when, where, and most likely why.

Input

The user provides: $ARGUMENTS

This may be:

empty or "all" — report on every APIError in the recent window (default)
a session ID — report APIErrors for that one session only
a window like "today" or "last 7d" — restrict the time range
a cause filter: "rate-limit", "overload", or "context"

Data Sources

Endpoint	Returns
`GET /api/analytics`	`event_types` (total `APIError` count), `daily_events` (365d) — APIError volume and trend over time
`GET /api/events?session_id=X`	Per-session event stream — each `APIError` carries `summary`, `data`, and `timestamp` used to classify the cause
`GET /api/sessions?limit=N`	Sessions with `id`, `model`, `started_at` — attribute each error to a model and place it on the timeline

Report Sections

1. Volume & Trend

From GET /api/analytics: total APIError count and its share of total_events. Use daily_events to chart APIErrors over the requested window and flag any day that spikes above the window mean.

2. Affected Sessions & Models

For each session in scope, pull GET /api/events?session_id=X and collect APIError events. Group by session_id and, via GET /api/sessions, by model. Report the top affected sessions and which model accounts for the most errors.

3. Likely Cause Classification

Inspect each error's summary/data and bucket it:

Rate limit — mentions 429, "rate limit", "quota", or retry-after.
Overload — mentions 529, "overloaded", or capacity.
Context — mentions context length, token limit, or "too long" (correlate with nearby Compaction events).
Other — anything else; quote the summary. Report the count and percentage in each bucket.

4. Timeline

List the most recent APIErrors with timestamp, session_id, model, classified cause, and a one-line summary excerpt.

Output

A Markdown table per section (volume, by model, by cause).
Rates as percentages to 2 decimals; any currency in USD to 4 decimals.
Cite exact session_id, model, timestamp, and summary values — never invent a cause not supported by the payload; bucket as "Other" when unclear.
End with the dominant cause and a concrete mitigation (e.g., back off and retry on 529, reduce context to cut context errors, slow request rate on 429).
Read-only: only report what the API returns. If curl cannot reach http://localhost:4820, tell the user to start the dashboard 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.

agents/openai.yaml1 KB

Frequently asked questions

What does the Api Error Report AI skill do?

Why use Api Error Report on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-quality/skills/api-error-report. 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 Api Error Report?

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 Api Error Report?

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

Is the Api Error Report 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

API Error Report

Input

Data Sources

Report Sections

1. Volume & Trend

2. Affected Sessions & Models

3. Likely Cause Classification

4. Timeline

Output

Bundled files

Frequently asked questions

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