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AD chan-stock-analysis

缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）。 Use when: 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告。 NOT for: 实时行情播报、简单股价查询、非股票类金融分析。 触发词：缠论分析、股票分析报告、技术面+基本面、综合研究、投研报告、深度分析、估值分析、财报分析、买卖点分析

LeoYeAI/openclaw-master-skills Agent Skills author: LeoYeAI MIT 8 files body ≈ 2 432 tokens Open the sourcegithub.com↗ analyzed 2 d ago

缠论+基本面+财报+估值综合股票分析技能，生成专业投研报告（含 PDF）。 Use when: 用户提供股票代码，要求进行深度股票分析、缠论技术分析、基本面研究、财报解读、估值分析、综合投研报告。 NOT for: 实时行情播报、简单股价查询、非股票类金融分析。…

As a process D 45/100 · Unfinished process — weak spots: result and completion, inputs and preconditions, failures and branches

AnalyzerSoftware 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
A
96/100
safety, quality, tests
Safety 60%
100
Quality 40%
90
Run on models
none yet
Process rating
D
45/100
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

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: 8. 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 45/100

    • 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
    • 40Consistency. Frontmatter name (chan-stock-analysis) differs from the folder (chanlun-stock-analysis)
    • 50When it triggers. No condition that starts the skill
    • 60Tools and files. Uses tools (python) that frontmatter does not declare
    • 100Steps. 118 steps
    • 100Execution cost. Instruction body is 2432 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
    • +3Output format is not stated: the model decides each time
    • -212 emoji in the instructions: noise for the model
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 186: enough signal without eating the budget
    • +4Structure: 17 headings
    • +3Step-by-step instructions: 118 items
    • +4Has examples (12 code blocks)
    • +4Reference files are cited in the instructions (3 of 3)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 90.