AC net-detective
Run structured network diagnostics and produce a plain-English diagnosis explaining what's wrong and why. Goes beyond simple ping: tests DNS resolution across multiple providers, runs traceroute, detects MTU fragmentation, measures speed, and compares results against historical baselines. Use when the user reports "network slow", "internet problems", "diagnose network", "why is my internet slow", "DNS issues", "packet loss", "network diagnostic", connection issues, or wants to understand what's wrong with their network.
As a process C 50/100 · Has gaps — weak spots: result and completion, inputs and preconditions, consistency
The same skill appears in 1 more place: ClawHub
How to improve
- 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 · 0
✓ No critical or high findings
Files scanned: 9. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: Run structured network diagnostics and produce a plain-English dia… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 50/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 30Running it twice. 1 mutating operations with no state check
- 40Consistency. Frontmatter name (net-detective) differs from the folder (nai-net-detective)
- 55Failures and branches. 1 branches
- 60Tools and files. Uses tools (web, python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Steps. 15 steps
- 100Execution cost. Instruction body is 757 tokens
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
- +4Description does not say when NOT to use the skill (false activations)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +5Description quotes 7 example trigger phrases
- +3Description length 525: enough signal without eating the budget
- +4Structure: 10 headings
- +3Step-by-step instructions: 15 items
- +4Has examples (7 code blocks)
- +4Reference files are cited in the instructions (1 of 1)
- +3All 5 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 86.