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Intent Detection

Community
oliver-kriska
intent-detection

Route ambiguous or mixed Phoenix/LiveView/Ecto requests before choosing a workflow. Use when user is unsure where to start/how to approach work, asks for the right workflow, or combines intents such as fixing and refactoring. NOT for a clear task.

Overview

Publisheroliver-kriska
Repositoryclaude-elixir-phoenix
Skill nameintent-detection
Stars
555
Forks
40
Bundled files
Instructions only
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.

  • Self-contained

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

  • Open source

    Published by oliver-kriska on GitHub. Read the source before you install it.

Installation

Install the Intent Detection 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.
  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/oliver-kriska/claude-elixir-phoenix.git /tmp/claude-elixir-phoenix
mkdir -p .claude/skills
cp -r /tmp/claude-elixir-phoenix/plugins/elixir-phoenix/skills/intent-detection .claude/skills/intent-detection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Intent Detection 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 Intent Detection 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 Intent Detection 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.

Intent Detection — Workflow Routing

When user describes work WITHOUT specifying a /phx: command, analyze their intent and suggest the appropriate workflow BEFORE starting work.

Hard guard — check FIRST: if the message starts with any slash command (/phx:, /ecto:, /lv:, or any other /command), this skill does not apply. Follow the invoked command directly — no routing analysis, no suggestion, zero output from this skill.

Routing Table

SignalDetected IntentSuggest
"bug", "error", "crash", "failing", "broken", stack traceBug investigation/phx:investigate
"brainstorm", "explore idea", "not sure what I need", "vague idea", "let's discuss", "how to approach"Ideation/requirements/phx:brainstorm
"add", "implement", "build", "create" + multi-stepNew feature/phx:plan
"review", "check", "audit" codeCode review/phx:review
"fix" + small/specific scopeQuick fixhandle directly or /phx:quick
"refactor", "clean up", "improve"Refactoring/phx:plan (needs scope)
"research", "how to", "what's the best"Research/phx:research
"evaluate", "compare", "adopt", "library", "should we use"Library evaluation/phx:research --library
"test", "spec", "coverage"Testinghandle directly or /phx:plan
Describes 1-2 file changes, < 50 linesSmall taskhandle directly
"deploy", "release", "production"Deployment/phx:verify then deploy
"performance", "slow", "N+1", "memory"Performance/phx:perf
"PR review", "review comments", "address feedback", "respond to PR"PR response/phx:pr-review
"that worked", "fixed it", "problem solved"Knowledge capture/phx:compound
"enhance plan", "more detail", "deepen"Plan enhancement/phx:plan --existing
"triage", "which findings", "prioritize fixes"Finding triage/phx:triage

Behavior

  1. Read user's first message
  2. Match against routing table (use keyword + context signals, not exact match)
  3. If match found with multi-step workflow: "This looks like [intent]. I'd suggest [command] — want me to run it, or should I just dive in?"
  4. If trivial task (typo, single-line fix, config change): skip suggestion, just do it
  5. If user already specified a /phx: command: follow it, don't re-suggest
  6. NEVER block the user — suggestion only, not mandatory

Confidence Signals

High confidence (suggest immediately):

  • Stack trace or error message pasted → /phx:investigate
  • "Add [feature] with [multiple components]" → /phx:plan
  • "Review my changes" or "check this PR" → /phx:review

Medium confidence (suggest with caveat):

  • "Fix [thing]" — could be quick or complex, suggest based on scope description
  • "Update [thing]" — could be small edit or refactor

Low confidence (just do it):

  • Single file mentioned, clear change
  • "Change X to Y"
  • Configuration or dependency updates

Complexity Signals

When a task matches a workflow command, check complexity before suggesting:

Trivial signals (suggest /phx:quick or handle directly):

  • Single file mentioned explicitly
  • "exclude X from Y", "add X to config", "rename", "change X to Y"
  • Problem + solution both stated ("X is wrong, change to Y")
  • One-line fix described

Complex signals (suggest /phx:plan or /phx:investigate):

  • 3+ modules or files mentioned
  • "intermittent", "race condition", "sometimes", "random"
  • Stack trace with 5+ frames
  • "across", "all", "every" (scope indicators)

Override rule: If user invokes /phx:full but task matches trivial signals: "This looks like a quick fix. Want /phx:quick instead, or stick with the full cycle?"

Iron Laws

  1. NEVER block on suggestion — If user starts explaining, just do the work
  2. One suggestion max — Don't re-suggest if user ignores first suggestion
  3. Commands are shortcuts, not gates — All work can be done without commands

Routing Logic Example

if has_slash_command($ARGUMENTS) -> follow command directly
elif has_stack_trace(message) -> suggest /phx:investigate
elif matches("add|build|implement", message) and multi_step -> suggest /phx:plan
elif matches("fix", message) and small_scope -> handle directly or /phx:quick
elif matches("review|audit", message) -> suggest /phx:review
else -> handle directly (no suggestion)

Integration

This skill is consulted at session start. It works alongside:

  • SessionStart hook (shows plugin loaded message)
  • CLAUDE.md routing instructions (passive reference)
  • Individual workflow skills (activated by commands)

Frequently asked questions

What does the Intent Detection AI skill do?

Route ambiguous or mixed Phoenix/LiveView/Ecto requests before choosing a workflow. Use when user is unsure where to start/how to approach work, asks for the right workflow, or combines intents such as fixing and refactoring. NOT for a clear task.

Why use Intent Detection on TypingMind?

Because you install it once and use it with any model. Intent Detection 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 Intent Detection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/oliver-kriska/claude-elixir-phoenix/tree/main/plugins/elixir-phoenix/skills/intent-detection. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Intent Detection?

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 Intent Detection?

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

Is the Intent Detection AI skill free?

Yes. It is published on GitHub by oliver-kriska 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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