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CD stock-analyst

A股股票分析专家 + 自选股定时推送系统。 分析功能：使用段永平价值投资框架+技术面+资金面进行多维度分析，提供明确的买卖建议（含股票代码/买入价/止损价/理由）。 推送功能：盘前推荐（09:20）、收盘复盘（15:05）、次日关注（20:00）三个定时推送任务，每交易日晚自动发送持仓股行情。 触发条件：用户提到"分析股票"、"选股"、"买卖建议"、"看盘"、"自选股"、"股票推送"、"持仓监控"、"盯盘推送"、"定时提醒"、"A股行情"。 输出风格犀利直接（YC Founder Agent风格），拒绝模糊表述。

Not recommendedcritical or high security findings
ClawHub Agent Skills author: perrykono-debug v4.0.0 MIT-0 13 files body ≈ 1 320 tokens Open the sourceclawhub.ai↗ analyzed 9 h ago

A股股票分析专家 + 自选股定时推送系统。 分析功能：使用段永平价值投资框架+技术面+资金面进行多维度分析，提供明确的买卖建议（含股票代码/买入价/止损价/理由）。 推送功能：盘前推荐（09:20）、收盘复盘（15:05）、次日关注（20:00）三个定时推送任务，每交易日晚自动发送持仓股行情。…

As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions

AnalyzerAI and agentsSoftware developmenttype and topics are labelled automatically from the skill text
Runs in: OpenClaw Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) Goose OpenCode
JSON
Technical rating
C
69/100
safety, quality, tests
Safety 60%
68
Quality 40%
71
Run on models
none yet
Process rating
D
48/100
Unfinished process
Result and completion w 14
0
Inputs and preconditions w 11
0
Failures and branches w 10
0
the three weakest of ten parameters · all ten

What is at stake

The skill contains fragments that, in the wrong hands, cost money or data. Below: what the installer risks and what the author should do.

Dangerous commands
If you install

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.

For the author

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

  1. Address the high-severity findings: each costs 18 safety points. If one is a false positive, add the rule id to guard.allow in spec.yaml.
  2. 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 · 7

  • high Dangerous commands cmd-persistence references/push/troubleshooting.md:55
    Persistence mechanism (cron / launchd / scheduled task / autorun registry)
    cat /etc/cron.d/stock-monitor
Medium and low: 6
  • medium Dangerous commands cmd-persistence scripts/install.py:12
    Persistence mechanism (cron / launchd / scheduled task / autorun registry) (string literal in code, not executed)
    CRON_CONF = "/etc/cron.d/stock-monitor"
    code literal
  • medium Dangerous commands cmd-eval-dynamic scripts/install.py:87
    Dynamic code execution from decoded/untrusted input
    r = os.system(f"python3 -m py_compile {path}")
  • low Secrets in code secret-high-entropy-token scripts/stock_after.py:7
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USER_ID = "o9…@….wechat"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/stock_next.py:7
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USER_ID = "o9…@….wechat"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/stock_pre.py:7
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USER_ID = "o9…@….wechat"
    quoted
  • low Secrets in code secret-high-entropy-token scripts/stock_push.py:9
    High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
    USER_ID = "o9…@….wechat"
    quoted

Files scanned: 13. Evidence is masked. Grey chips explain why severity was lowered.

Against the Agent Skills spec

  • warning description-no-when description does not say WHEN to use the skill (no "use when")

Process rating: all ten parameters 48/100

  • 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
  • 20When it triggers. No condition that starts the skill
  • 30Running it twice. 6 mutating operations with no state check
  • 40Consistency. Frontmatter name (stock-analyst) differs from the folder (stock-watcher-v2)
  • 100Tools and files. No external tools needed
  • 100Steps. 86 steps
  • 100Execution cost. Instruction body is 1320 tokens
  • 100Progress reporting. Reports progress
  • low 11 top-level sections: this looks like several domains in one skill

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
  • -212 emoji in the instructions: noise for the model
  • -32 of 5 scripts are never mentioned in SKILL.md
  • +1No license
  • +2Single-language instructions
  • +3Description length 259: enough signal without eating the budget
  • +4Structure: 29 headings
  • +3Step-by-step instructions: 86 items
  • +4Has examples (6 code blocks)
  • +4Reference files are cited in the instructions (3 of 3)

Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.

External checks

ClawHub: suspicious
The skill is a stock-analysis and notification tool, but it includes root-level scheduled execution and defaults that can send stock/watchlist data to a hard-coded WeChat recipient.
LLM: suspicious (high) · VirusTotal: · 30 May 2026