BF apocdata
Use when users ask for A-share stock quotes, financials, capital flows, technical factors, news, announcements, sectors, convertible bonds, macro data, or comprehensive stock analysis through the ApocData public API. Trigger keywords: 股票, 行情, 估值, 财务, 资金流, 涨停, 跌停, 炸板, 打板, 连板, 板块, 概念, 可转债, 宏观, 公告, 调研, 龙虎榜, 游资, 北向资金, 两融, 排行, 人气榜, 指数, 筹码, 获利盘, ST, 分红, 回购, 大宗交易, 量化因子, 技术面, 交易日历, 下修, 转股价, 业绩快报, 股东户数, 解禁, profile, ApocData, A股数据. Do NOT trigger for: cryptocurrency, crypto, Bitcoin, US stocks, US market, futures, options, forex, Hong Kong stocks, 加密货币, 比特币, 美股, 期货, 外汇, or any non-A-share market.
Use when users ask for A-share stock quotes, financials, capital flows, technical factors, news, announcements, sectors, convertible bonds, macro data, or…
As a process F 31/100 · Will not run — References files that are not bundled: references/group-*.md
The same skill appears in 1 more place: ClawHub
What is at stake
Medium-severity findings: the skill is probably honest, but read what alarmed the scanner.
Below is the worst case for this category. The finding here is medium: the guard saw a sign, not a proof.
The skill contains commands that delete files, rewrite disks or execute code fetched from the network. The agent may run them without asking if it believes the instructions require it.
Replace destructive commands with safe equivalents that ask for confirmation, scope them to one folder, and stop piping curl into a shell: pin a version and a checksum.
How to improve
- The text references files that are not there: add them or drop the references.
- 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 · 2
✓ No critical or high findings
Medium and low: 2
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medium Dangerous commands
cmd-pipe-to-shell-known-hostREADME.md:67Pipe-to-shell installer from a well-known host (still executes remote code)curl -sL https://raw.githubusercontent.com/ApocData/ApocData-skill/v2.0.0/scripts/install.sh | bash
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low Dangerous commands
cmd-pipe-to-shell-known-hostscripts/install.sh:3Pipe-to-shell installer from a well-known host (still executes remote code) (code comment)# Usage: curl -sL https://raw.githubusercontent.com/ApocData/ApocData-skill/v2.0.0/scripts/install.sh | bash
comment
Files scanned: 21. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/group-*.md
Process rating: all ten parameters 31/100
- 0Tools and files. 1 referenced file(s) missing: references/group-*.md
- 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 (apocdata) differs from the folder (apoc-data-skill)
- 100Steps. 24 steps
- 100Execution cost. Instruction body is 1455 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
- -32 of 2 scripts are never mentioned in SKILL.md
- +1No license
- +2Single-language instructions
- +3Description length 594: enough signal without eating the budget
- +4Structure: 16 headings
- +3Step-by-step instructions: 24 items
- +4Has examples (2 code blocks)
- +4Reference files are cited in the instructions (14 of 14)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 79.