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AB equity-analyst

전문 투자 분석가 AI로, 한국 주식 종목의 재무제표, 뉴스, 차트를 분석하여 Investment Attractiveness Score (0-100)와 BUY/HOLD/AVOID 추천을 제공합니다. 네이버 금융 데이터를 사용하며, 프롬프트에 명시된 엄격한 우선순위(Financial > News > Chart)와 가중치를 따릅니다.

modbender/skill-library-mcp Claude Code author: modbender MIT 10 files body ≈ 1 708 tokens Open the sourcegithub.com↗ analyzed 2 d ago

전문 투자 분석가 AI로, 한국 주식 종목의 재무제표, 뉴스, 차트를 분석하여 Investment Attractiveness Score (0-100)와 BUY/HOLD/AVOID 추천을 제공합니다.

As a process B 68/100 · Nearly there — weak spots: inputs and preconditions, progress reporting

AnalyzerOutlookWriting and documentsData and analyticstype 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
97/100
safety, quality, tests
Safety 60%
100
Quality 40%
92
Run on models
none yet
Process rating
B
68/100
Nearly there
Inputs and preconditions w 11
0
Progress reporting w 2
0
When it triggers w 12
50
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: 10. 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 68/100

    • 0Inputs and preconditions. Does not say what the process needs to start
    • 0Progress reporting. Says nothing while it works
    • 50When it triggers. No condition that starts the skill
    • 50Failures and branches. 0 branches, has a failure section
    • 60Result and completion. Output format stated, no completion criterion
    • 85Steps. 62 steps, 1 vague phrases
    • 100Tools and files. No external tools needed
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1708 tokens
    • 100Running it twice. No mutating operations
    • low 10 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
    • -33 of 5 scripts are never mentioned in SKILL.md
    • +1No license
    • +2Single-language instructions
    • +4Description says when NOT to use the skill
    • +3Description length 185: enough signal without eating the budget
    • +4Structure: 21 headings
    • +3Step-by-step instructions: 62 items
    • +3Output format is stated explicitly
    • +4Has examples (3 code blocks)
    • +4Reference files are cited in the instructions (1 of 1)

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 92.