BF give-me-a-stock (Public)
全面的A股股票分析工具，提供7大核心模块（核心财务、技术指标、估值分析、股东持股、市场热度、券商盈利预测、K线图表）+ 财报、公告、新闻资讯和交易所互动问答的多维度分析。
As a process F 34/100 · Will not run — 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.
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: 8. 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 34/100
- 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 (give-me-a-stock (Public)) differs from the folder (getmeastock)
- 50Steps. 2 steps
- 60Tools and files. Uses tools (python, node) that frontmatter does not declare
- 100Execution cost. Instruction body is 127 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)
- +3Description length 85: 120–800 characters recommended
- +4Structure: 1 headings, hard to scan
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 56.
External checks
ClawHub: clean
This is a disclosed remote stock-analysis wrapper that sends requests to Prana/Claw and may store its own API credentials locally.
LLM: benign (high) · VirusTotal: · 29 May 2026