QGroundControl is a cross-platform ground control station for unmanned aircraft, allowing operators to control MAVLink-enabled drones and plan their missions. Drone users work with it to monitor flights, configure vehicles, tune parameters, stream video, and manage autonomous missions, while the catalogue contains skills and instructions for using the application.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mavlink/qgroundcontrol --skill qt-qml-reviewgit clone --depth 1 https://github.com/mavlink/qgroundcontrolWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mavlink/qgroundcontrol/qt-qml-review)<a href="https://agentmods.dev/skills/mavlink/qgroundcontrol/qt-qml-review"><img src="https://agentmods.dev/badge/skills/mavlink/qgroundcontrol/qt-qml-review/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/mavlink/qgroundcontrol/qt-qml-review"><img src="https://agentmods.dev/badge/skills/mavlink/qgroundcontrol/qt-qml-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00095 | $0.03488 |
| Opus 5 | $0.00048 | $0.01744 |
| Sonnet 5 | $0.00019 | $0.00698 |
| Haiku 4.5 | $0.00010 | $0.00349 |
Grade A, and why
qt-qml-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 413 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Qt QML Code Review
A structured, read-only code review skill for Qt6 QML code that combines deterministic linting with parallel agent-driven deep analysis across six focused domains.
When to use this skill
- When the user mentions review-related tasks: "review", "check", "audit", "look over", "code review", "sanity check"
- Suggest running this skill before committing QML code
- When the user asks to validate Qt6 QML code quality
Scope detection
Detect the user's intended scope from their language:
Diff/commit scope (narrow)
Triggered by language like: "this commit", "these changes", "the diff", "what I changed", "my changes", "staged changes", "outstanding changes", "before I commit"
Action: Run git diff (unstaged) and git diff --cached
(staged) to obtain the changeset. If the user says "this commit",
use git diff HEAD~1..HEAD. Review only the changed lines plus
sufficient surrounding context (±50 lines) for understanding.
Only report issues found in the changed lines -- do not report
issues in unchanged surrounding context.
Codebase scope (wide)
Triggered by language like: "review the codebase", "audit the project", "check the repository", "review src/", or when a specific file/directory path is given without commit language.
Action: Glob for *.qml files in the specified scope. Review
all matched files.
Execution order
The review proceeds in three phases. Never skip a phase.
Phase 1: Deterministic linting (Python script)
Run the unified Python linter against the target files. Requires Python 3.6+ (no external dependencies). If Python is not available, warn the user and skip to Phase 1b.
python3 references/lint-scripts/qt_qml_lint.py <files...>
# If python3 is not found, fall back to:
python references/lint-scripts/qt_qml_lint.py <files...>
This single-pass scanner encodes all mechanically-checkable rules from the QML review checklist. It reads each file once and evaluates all rules per line, plus block-level structural checks. Output is deterministic and repeatable. The linter is authoritative -- do not second-guess its output.
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 413 lines · 95 tokens per session scan A fe4af707669a
qt-qml-review is a skill published in the GitHub repository mavlink/qgroundcontrol (4,913 stars, last pushed yesterday), licensed Apache-2.0. It adds 95 tokens to every session and 3,488 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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