smarttune-mcp

A read-only interface for analysing aircraft flight logs through connected tools. It supports ArduPilot, Betaflight, and PX4 logs, including checks for control tuning, vibration, filters, and magnetometers.

In plain words
What is it for?
Reading .bin, .log, .bbl, .bfl, and .ulg logs, checking their quality, generating charts, and reviewing validated tuning results.
Why use it?
It lets agents analyse flight data when they cannot run shell commands or modify files, while keeping the original logs and aircraft settings unchanged.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/raylanlin/smarttune-cli/skill-mcp
Any agent
npx skills add raylanlin/smarttune-cli --skill skill-mcp
Clone the repo
git clone --depth 1 https://github.com/raylanlin/smarttune-cli

Made for: Claude Code, Codex.

Per session 86 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,050 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00086 $0.03050
Opus 5 $0.00043 $0.01525
Sonnet 5 $0.00017 $0.00610
Haiku 4.5 $0.00009 $0.00305

Measured 3d ago against content hash 759f18547eba, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

smarttune-mcp 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 3d 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.

skill-mcp/SKILL.md · 172 lines

How it starts

The opening of the file, as written. The whole thing — 172 lines — stays where its author put it; the contents beside it link to each section on GitHub.

SmartTune MCP

Use this skill when SmartTune is connected through MCP and the agent does not have shell, exec, or write permission.

This is the MCP-only variant of the SmartTune skill. If the agent has normal CLI access, use the smarttune skill instead.

Hard Rules

  • Do not call exec, shell commands, Python subprocesses, or the stune CLI.
  • Do not ask for write, edit, or process execution permissions to analyze a log.
  • Do not create report files or choose arbitrary output paths.
  • Do not modify logs, parameters, firmware, local files, or aircraft configuration.
  • Use only the SmartTune MCP tools listed below.
  • If these tools are unavailable, say SmartTune MCP is not connected and ask the operator to enable the MCP server.
  • Analysis results arrive pre-validated (v3.2.1). Every recommendation returned by smarttune_analyze_log and the per-module analysis tools carries validated / validation_status. Only recommendations with validated: true may be presented as-is; a false entry must be dropped or corrected using the options from smarttune_get_param.
  • MANDATORY: Validate every value YOU adjusted. Before suggesting any parameter change, call smarttune_validate_param with the exact parameter name, proposed value, and platform. Never recommend a parameter that fails validation — search for alternatives with smarttune_search_params. A verdict of unverifiable is not approval. For a whole set of adjusted values, use smarttune_validate_params (one call instead of N).
  • Every tool returns one shape: {ok: true, ...} on success, {ok: false, error_code, message, hint, retryable} on failure. A rejected parameter value is a successful call with valid: false.
  • Firmware-version tables (v3.3). All six parameter tools accept fw_version (e.g. "copter-4.5"); omit it for the platform default (ArduPilot default = Copter-4.1). An unknown version returns error_code: "E4011" with the available list. Ranges can differ between versions — validate against the version the user actually flies.
  • Never list a whole parameter table. Browse with smarttune_list_param_groupssmarttune_list_params(group=...)smarttune_get_param(name) for full detail. ArduPilot alone is ~2,800 parameters.

Read the full file on GitHub · 172 lines

Changes

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.

  1. 3d ago First seen · 172 lines · 86 tokens per session scan A 759f18547eba

Subscribe to this mod's changes

smarttune-mcp is a skill published in the GitHub repository raylanlin/smarttune-cli (28 stars, last pushed 20d ago), licensed MIT. It adds 86 tokens to every session and 3,050 once invoked, about $0.0004 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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