AD network-toolbox
Network diagnostics and analysis toolkit using Python standard library. Check connectivity, resolve DNS, inspect HTTP headers, scan ports, trace routes, and look up WHOIS/SSL info. Use when the user wants to: (1) Ping a host to check connectivity, (2) Resolve DNS records (A, AAAA, MX, NS, TXT), (3) Inspect HTTP response headers and status codes, (4) Scan open ports on a host, (5) Trace route to a destination, (6) Look up WHOIS domain registration info, (7) Check SSL certificate details, (8) Get your public IP address, (9) Measure network latency.
As a process D 37/100 · Unfinished process — weak spots: steps, result and completion, inputs and preconditions
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: Network diagnostics and analysis toolkit using Python standard lib… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value
Process rating: all ten parameters 37/100
- 0Steps. Prose only: no discrete steps
- 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
- 60Tools and files. Uses tools (python) that frontmatter does not declare
- 70When it triggers. States when to use, but not when not to
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 447 tokens
- 100Running it twice. No mutating operations
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)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 552: enough signal without eating the budget
- +4Structure: 10 headings
- +4Has examples (7 code blocks)
- +3All 7 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 74.