BD Fritz Connection
Dieser Skill ermöglicht die Abfrage von Statusinformationen und die Steuerung einer AVM FRITZ!Box über die TR-064 Schnittstelle. Er bietet Funktionen für Status (Modell, Uptime), Traffic (Bandbreite, Volumen), Host-Listen, WLAN-Steuerung, Anruflisten sowie Reconnect und Reboot.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- Say in the description WHEN to use the skill ("use when…", example requests): that is the agent's main cue.
- 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 · 1
✓ No critical or high findings
Medium and low: 1
-
low Secrets in code
secret-high-entropy-tokenscripts/fritz_status.py:92High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)downstream = common_config.get("NewL…ate", 0) / 1_000_000quoted
Files scanned: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
name-formatname should be kebab-case (lowercase letters, digits, hyphens) - warning
description-no-whendescription does not say WHEN to use the skill (no "use when")
Process rating: all ten parameters 49/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Consistency. Frontmatter name (Fritz Connection) differs from the folder (fritz-connection)
- 100Tools and files. No external tools needed
- 100Steps. 26 steps
- 100Execution cost. Instruction body is 2444 tokens
- 100Running it twice. No mutating operations
- 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- -220 emoji in the instructions: noise for the model
- +1No license
- +2Single-language instructions
- +3Description length 278: enough signal without eating the budget
- +4Structure: 29 headings
- +3Step-by-step instructions: 26 items
- +4Has examples (22 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 68.