Impossible Travel Tuning logo

Impossible Travel Tuning

Organization
CDESpace
impossible-travel-tuning

Tune impossible-travel detections from closed-case outcomes. Reads the triage report, the investigation report, and the analyst's verdict, then proposes exactly one detection change — an egress exclusion, a threshold modification, or a fork for a high-risk population — for human review.

Overview

PublisherCDESpace
RepositoryDetection-Skills
Skill nameimpossible-travel-tuning
Stars
57
Forks
5
Bundled files
Instructions only
LicenseApache-2.0
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

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

Installation

Install the Impossible Travel Tuning 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/CDESpace/Detection-Skills/tree/main/skills/tuning/impossible-travel-tuning
  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/CDESpace/Detection-Skills.git /tmp/Detection-Skills
mkdir -p .claude/skills
cp -r /tmp/Detection-Skills/skills/tuning/impossible-travel-tuning .claude/skills/impossible-travel-tuning
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Impossible Travel Tuning 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 Impossible Travel Tuning 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 Impossible Travel Tuning 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.

Impossible Travel Tuning

Runs after a case is closed. The goal is not to judge the alert again — it is to decide whether the detection itself should change so the next occurrence of this pattern is either suppressed earlier or caught with more context. Every proposal is a suggestion for human review; nothing is auto-applied.

Inputs

  • Triage report — the gate that resolved, the dismissal reason code or escalation evidence, and the egress/device/MFA facts gathered.
  • Investigation report — the verdict, the evidence chain, and any infrastructure indicators (ASNs, IP ranges, device fingerprints).
  • Analyst verdict — the human's final disposition and any notes on why it differed (or not) from the automated verdict.

Tuning procedure

Work through these in order and stop at the first that applies.

1. Recurring benign egress

If the case was dismissed (or investigated to benign) because of egress infrastructure that is not yet in the known-egress inventory — a new corporate VPN range, a SASE point of presence, a carrier NAT block seen repeatedly for this population — propose exclude with the specific range or ASN as the value. Cite every prior case that hit the same range.

2. Over-broad exclusion

If a true positive was suppressed or delayed by an existing exclusion — or the investigation shows an inventoried egress range now also covering attacker infrastructure — propose include: remove or narrow that exclusion, citing the case it hid and any others that would resurface.

3. Threshold friction

If the last 30 days show three or more benign cases whose computed travel velocity sits just above the current threshold (within 20%), propose modify on the velocity threshold or the minimum-distance floor. Include the velocity distribution of recent true and false positives so the reviewer can see what the new threshold would have suppressed.

4. Population mismatch

If the case shows the detection performing well generally but poorly for an identifiable population — executives who travel weekly, a region with known GeoIP drift, service accounts that should never travel at all — propose fork: a copy of the detection scoped to that population with tightened or loosened gates, leaving the base detection untouched.

5. No change

If the alert worked as designed — escalated a true positive or dismissed an explained anomaly with an inventoried reason — return the action none with no target or value. A tuning skill that always suggests something trains reviewers to ignore it.

Output

Action

One of exclude | include | modify | fork | none. none is the explicit no-change result — return it with reasoning rather than omitting a proposal.

Target

The detection ID or inventory list the change applies to (empty for none).

Value

The specific range, ASN, threshold, or fork scope to apply (empty for none).

Evidence

Prior-case references, hit counts, and the expected alert-volume impact. One proposal per run — if several gates apply, return the one with the largest false-positive reduction and note the runners-up here.

Reasoning

Which gate applied, the case facts that satisfied it, and why the proposed change (or none) follows from them.

Frequently asked questions

What does the Impossible Travel Tuning AI skill do?

Tune impossible-travel detections from closed-case outcomes. Reads the triage report, the investigation report, and the analyst's verdict, then proposes exactly one detection change — an egress exclusion, a threshold modification, or a fork for a high-risk population — for human review.

Why use Impossible Travel Tuning on TypingMind?

Because you install it once and use it with any model. Impossible Travel Tuning 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 Impossible Travel Tuning in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/CDESpace/Detection-Skills/tree/main/skills/tuning/impossible-travel-tuning. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Impossible Travel Tuning?

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 Impossible Travel Tuning?

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

Is the Impossible Travel Tuning AI skill free?

Yes. It is published on GitHub by CDESpace 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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