SKILLEMALL.ai
GitHub ↗ RU Sign in

AB fritzbox

Control AVM FRITZ!Box routers and Smarthome devices via TR-064 and Web API. Use when the user wants to manage their FRITZ!Box router (WLAN, connected devices, reconnect) or control FRITZ!DECT smarthome devices (smart plugs, thermostats). Triggers on phrases like "fritzbox", "fritz box", "router", "wlan", "wifi", "smarthome", "dect", "smart plug", "steckdose".

ClawHub Agent Skills author: HW v1.0.5 MIT-0 12 files · 2 scripts body ≈ 874 tokens Open the sourceclawhub.ai↗ analyzed 3 d ago

As a process B 66/100 · Nearly there — weak spots: result and completion, running it twice, progress reporting

IntegrationInfrastructuretype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
A
95/100
safety, quality, tests
Safety 60%
98
Quality 40%
90
Run on models
none yet
Process rating
B
66/100
Nearly there
Result and completion w 14
0
Progress reporting w 2
0
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
    • A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.

    Guard findings · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Exfiltration read-dotenv INSTALL.md:23
      Reads a .env file (documentation of a security skill)
      cp .env.example .env
      security skill
    • low Exfiltration read-dotenv README.md:24
      Reads a .env file (documentation of a security skill)
      cp .env.example .env
      security skill

    Files scanned: 12. Evidence is masked. Grey chips explain why severity was lowered.

    Against the Agent Skills spec

    ✓ No remarks against the Agent Skills spec

    Process rating: all ten parameters 66/100

    • 0Result and completion. Does not say what the result is
    • 0Progress reporting. Says nothing while it works
    • 30Running it twice. 2 mutating operations with no state check
    • 50Failures and branches. 0 branches, has a failure section
    • 60Tools and files. Uses tools (bash) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 25 steps
    • 100When it triggers. States when to use and when not to
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 874 tokens
    • medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
    • low 10 top-level sections: this looks like several domains in one skill

    Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.

    Quality signals

    • +3Output format is not stated: the model decides each time
    • -31 of 1 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +5Description quotes 6 example trigger phrases
    • +4Description says when NOT to use the skill
    • +3Description length 361: enough signal without eating the budget
    • +4Structure: 15 headings
    • +3Step-by-step instructions: 25 items
    • +4Has examples (6 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.

    External checks

    ClawHub: clean
    This skill controls a local FRITZ!Box router and smart-home devices as advertised, with sensitive capabilities disclosed and scoped to a private/local host.
    LLM: benign (high) · VirusTotal: benign · 28 May 2026