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Anomaly Alert

CommunityPopular
hoangsonww
anomaly-alert

Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).

Overview

Publisherhoangsonww
RepositoryClaude-Code-Agent-Monitor
Skill nameanomaly-alert
Stars
1.1K
Forks
260
Bundled files
1
LicenseMIT
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.

  • 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 Anomaly Alert 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-insights/skills/anomaly-alert
  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-insights/skills/anomaly-alert .claude/skills/anomaly-alert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Anomaly Alert 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 Anomaly Alert 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 Anomaly Alert 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.

Anomaly Alert

Detect anomalous sessions in Claude Code Agent Monitor data.

Input

The user provides: $ARGUMENTS

This may be:

  • "all" or empty (default: check all anomaly types)
  • "cost" for cost anomalies only
  • "duration" for duration anomalies only
  • "errors" for error rate anomalies only
  • A sensitivity level: "strict" (1σ), "normal" (2σ), "relaxed" (3σ)

Procedure

  1. Fetch baseline data from http://localhost:4820:

    • GET /api/sessions?limit=500 — historical sessions for baseline
    • GET /api/analytics — aggregated metrics
    • GET /api/pricing/cost — cost data per session

  2. Compute baselines for each metric:

    • Mean, median, standard deviation
    • P25, P75, P90, P95, P99 percentiles
    • Interquartile range (IQR) for robust outlier detection

  3. Detect anomalies using statistical thresholds:

    Cost Anomalies

    • Sessions costing >2σ above mean
    • Single sessions exceeding daily average
    • Sudden cost spikes (session-over-session increase >200%)

    Duration Anomalies

    • Sessions lasting >2σ above mean duration
    • Extremely short sessions (<1 minute) that still incur cost
    • Sessions with unusual active-vs-idle ratios

    Error Rate Anomalies

    • Sessions with error rates >2σ above baseline
    • New error types not seen in previous sessions
    • Sessions with >3 consecutive tool failures

    Behavioral Anomalies

    • Unusual tool combinations not seen before
    • Sessions with abnormally high compaction counts
    • Model switches mid-session (if unexpected)
    • Sessions with no tool usage (pure conversation)

    Token Anomalies

    • Input/output token ratio far from historical norm
    • Cache miss rate significantly higher than average
    • Token usage growing faster than session count

  4. Classify each anomaly:

    • 🔴 Critical: Likely indicates a real problem requiring attention
    • 🟡 Warning: Unusual but may be expected for certain tasks
    • 🔵 Info: Interesting deviation worth noting

Output Format

Present as an Anomaly Report:

═══════════════════════════════════════════════
  ANOMALY DETECTION REPORT
  Analyzed: N sessions | Baseline: last 30 days
  Anomalies found: N (🔴 N critical, 🟡 N warn, 🔵 N info)
═══════════════════════════════════════════════

For each anomaly:

  • Session ID and timestamp
  • Anomaly type and severity
  • Observed value vs expected range
  • Possible explanation
  • Recommended action (if any)

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 Anomaly Alert AI skill do?

Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).

Why use Anomaly Alert on TypingMind?

Because you install it once and use it with any model. Anomaly Alert 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 Anomaly Alert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/hoangsonww/Claude-Code-Agent-Monitor/tree/master/plugins/ccam-insights/skills/anomaly-alert. 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 Anomaly Alert?

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 Anomaly Alert?

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

Is the Anomaly Alert 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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