AD stock-price-query
Query current A/HK/US-share stock prices using natural language stock names. Invoke when user asks about stock prices, market data, or mentions Chinese stock names like '贵州茅台', '中国平安', etc.
As a process D 49/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
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 · 0
✓ No critical or high findings
Files scanned: 3. 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 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 (stock-price-query) differs from the folder (stock-price-check)
- 100Tools and files. No external tools needed
- 100Steps. 7 steps
- 100Execution cost. Instruction body is 117 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)
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +3Description length 189: enough signal without eating the budget
- +4Structure: 7 headings
- +3Step-by-step instructions: 7 items
- +4Has examples (2 code blocks)
- +3All 1 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 87.
External checks
ClawHub: clean
This skill coherently performs stock-price lookup and does not show hidden credential access, persistence, destructive behavior, or unrelated data collection.
LLM: benign (high) · VirusTotal: · 29 May 2026