Nav Pilot logo

Nav Pilot

Organization
qf-studio
nav-pilot

Dispatch a Navigator task doc to Pilot as a labeled GitHub issue. Use when user says "dispatch TASK-XX to Pilot", "hand off to Pilot", "send to Pilot", or "queue for Pilot". One-way handoff (Navigator authors the spec, Pilot executes autonomously).

Overview

Publisherqf-studio
Repositorynavigator
Skill namenav-pilot
Stars
232
Forks
12
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 qf-studio on GitHub. Read the source before you install it.

Installation

Install the Nav Pilot 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/qf-studio/navigator.git /tmp/navigator
mkdir -p .claude/skills
cp -r /tmp/navigator/skills/nav-pilot .claude/skills/nav-pilot
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Nav Pilot 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 Nav Pilot 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 Nav Pilot 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.

Navigator → Pilot Dispatch Skill

Hand a finished Navigator task doc off to Pilot by creating the pilot-labeled GitHub issue Pilot polls, then record the issue back into the doc.

This skill does NOT validate the doc. Spec checking is Pilot's job (its spec_validator). nav-pilot only resolves the doc, creates the labeled issue, and records the result. It consumes what nav-task authored — it does not author or archive docs itself.

When to Invoke

Invoke when the user says:

  • "Dispatch TASK-XX to Pilot"
  • "Hand this off to Pilot" / "send to Pilot"
  • "Queue TASK-XX for Pilot" / "create the Pilot issue"

DO NOT invoke when:

  • User is authoring/archiving a task doc (that's nav-task)
  • User wants Pilot worker status (out of scope — this skill is one-way)
  • No task doc exists yet (tell them to create one with nav-task first)

Execution Steps

Step 1: Resolve the Target Task Doc

  • Explicit ID ("TASK-07"): use .agent/tasks/TASK-07-*.md.
  • No ID: pick the active/in-progress task. If ambiguous, list candidates (ls .agent/tasks/*.md) and ask which one.
  • If the file does not exist, stop and tell the user to author it first.

Read the doc and extract:

  • Title = the first H1 (# TASK-XX: <name>), stripped of the TASK-XX: prefix if present (or keep the full H1 — match what Pilot expects).
  • Body file path = the doc itself (passed via --body-file, never inlined).

Step 2: Load Pilot Config

Read pilot from .agent/.nav-config.json:

json
"pilot": {
  "enabled": true,
  "label": "pilot",
  "repo": null
}
  • label (default "pilot"): the label Pilot polls for.
  • repo (default null): target owner/name. When null, gh uses the current git repository's origin — do NOT pass --repo.

If pilot.enabled is false, stop and tell the user to enable it.

Step 3: Build the Command

bash
gh issue create \
  --title "<H1 title>" \
  --label "<pilot.label>" \
  --body-file ".agent/tasks/TASK-XX-<slug>.md" \
  [--repo "<pilot.repo>"]   # only when pilot.repo is set

Step 4: Pre-flight Confirmation (ToM Checkpoint — high-stakes)

Creating a GitHub issue is an outward-facing action. ALWAYS confirm first:

About to dispatch to Pilot:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Repo:  <pilot.repo or "current origin (gh default)">
Title: <H1 title>
Label: <pilot.label>
Body:  .agent/tasks/TASK-XX-<slug>.md (<N> lines)

Command:
  gh issue create --title "..." --label "pilot" --body-file "..."
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Create this issue? [Enter to dispatch / "dry-run" / corrections]

--dry-run mode: if the user asked for a dry run (or says "dry-run" here), print the exact gh command and STOP. Do not execute.

Step 5: Dispatch

Run the gh issue create command. Capture the returned issue URL from stdout (gh issue create prints the URL on success).

If gh fails:

  • not authenticated → tell the user to run gh auth login
  • label missing on the repo → offer gh label create pilot
  • no git remote / repo not found → ask for pilot.repo in config

Step 6: Record Back Into the Doc

Edit the task doc:

  • Add the issue URL under ## Refs: - Pilot issue: <url>
  • Update the status line to **Status**: 🚀 Dispatched to Pilot.
  • Update **Last Updated**: to today.

Step 7: Confirm

✅ Dispatched to Pilot

Issue:  <url>
Label:  pilot
Task:   TASK-XX — <title>

Recorded back into .agent/tasks/TASK-XX-<slug>.md (status → 🚀 Dispatched).
Pilot will pick it up on its next poll of `pilot`-labeled issues.

If the knowledge graph is enabled, the Edit will sync via the normal PostToolUse hook — no extra action needed.

Error Handling

SituationResponse
No task doc foundAsk which task; suggest nav-task to create one
pilot.enabled: falseStop; tell user to enable in .nav-config.json
gh not authenticatedPrompt gh auth login
pilot label missingOffer gh label create pilot
No remote / repo unknownAsk user to set pilot.repo

Success Criteria

  • Correct task doc resolved and H1 used as the issue title
  • Pre-flight confirmation shown before any network call
  • --dry-run prints the command without executing
  • Issue created with the pilot label
  • Issue URL recorded back into the doc; status → 🚀 Dispatched

Notes

  • One-way by design: monitoring Pilot workers and pulling results back are out of scope (see .agent/tasks/TASK-54-nav-pilot-dispatch-skill.md).
  • Validation is intentionally absent — Pilot's spec_validator owns that.
  • Pairs with nav-task (authors the doc) → nav-pilot (dispatches it).

Frequently asked questions

What does the Nav Pilot AI skill do?

Dispatch a Navigator task doc to Pilot as a labeled GitHub issue. Use when user says "dispatch TASK-XX to Pilot", "hand off to Pilot", "send to Pilot", or "queue for Pilot". One-way handoff (Navigator authors the spec, Pilot executes autonomously).

Why use Nav Pilot on TypingMind?

Because you install it once and use it with any model. Nav Pilot 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 Nav Pilot in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/qf-studio/navigator/tree/main/skills/nav-pilot. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Nav Pilot?

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 Nav Pilot?

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

Is the Nav Pilot AI skill free?

Yes. It is published on GitHub by qf-studio 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇