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AB stock-watcher

Manage and monitor a local Chinese A-share watchlist. Use when the user asks to add, remove, list, clear, or summarize watched stocks using 10jqka structured quote data with HTML fallback.

ClawHub Agent Skills author: Hao v0.1.0 MIT-0 13 files · 2 scripts body ≈ 448 tokens Open the sourceclawhub.ai↗ analyzed 2 d ago

Manage and monitor a local Chinese A-share watchlist.

As a process B 69/100 · Nearly there — weak spots: inputs and preconditions, consistency, progress reporting

ProcedureWriting and documentstype 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
A
92/100
safety, quality, tests
Safety 60%
98
Quality 40%
84
Run on models
none yet
Process rating
B
69/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
Consistency w 8
40
the three weakest of ten parameters · all ten

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 · 2

    ✓ No critical or high findings

    Medium and low: 2
    • low Obfuscation obf-base64-blob scripts/summarize_performance.py:29
      Long base64-looking blob (quoted — discussed, not commanded)
      "eyJh…J9."
      quoted
    • low Secrets in code secret-high-entropy-token scripts/summarize_performance.py:30
      High-entropy token-like string (may be an id, hash or a credential) (quoted — discussed, not commanded)
      "ldrv…Hbk"
      quoted

    Files scanned: 13. 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 69/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 40Consistency. Frontmatter name (stock-watcher) differs from the folder (stock-watcher-publish)
    • 55Failures and branches. 1 branches
    • 60Result and completion. Output format stated, no completion criterion
    • 70When it triggers. States when to use, but not when not to
    • 100Tools and files. No external tools needed
    • 100Steps. 9 steps
    • 100Execution cost. Instruction body is 448 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)
    • -32 of 8 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +3Description length 188: enough signal without eating the budget
    • +4Structure: 6 headings
    • +3Step-by-step instructions: 9 items
    • +3Output format is stated explicitly
    • +4Has examples (5 code blocks)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.

    External checks

    ClawHub: suspicious
    The skill mostly matches its stock-watchlist purpose, but its uninstall script can delete an arbitrary environment-selected directory without validation or confirmation.
    LLM: suspicious (high) · 5 Aug 2026